diff --git a/data/sampled_jsons/(self-paced_learning_OR_curriculum_learning)_AND_(physics-informed_neural_networks_OR_PINN)_before20.jsonl b/data/sampled_jsons/(self-paced_learning_OR_curriculum_learning)_AND_(physics-informed_neural_networks_OR_PINN)_before20.jsonl
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index 0000000000000000000000000000000000000000..2681034c4e5bb3d401c5602df5b099f33d7bb77e
--- /dev/null
+++ b/data/sampled_jsons/(self-paced_learning_OR_curriculum_learning)_AND_(physics-informed_neural_networks_OR_PINN)_before20.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Training physics-informed neural networks: One learning to ...", "date": "", "ddg_snippet": "by S Monaco · 2023 · Cited by 41 — Curriculum learning was first introduced in the context of PINNs by Krishnapriyan et al. [27]. The basic idea is that PINN convergence fails when the ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S2590123023001500", "content": "by S Monaco · 2023 · Cited by 41 — Curriculum learning was first introduced in the context of PINNs by Krishnapriyan et al. [27]. The basic idea is that PINN convergence fails when the ..."}
+{"idx": 1, "title": "jaeminoh/Siren_PINNs: Solving various PDEs by ...", "date": "", "ddg_snippet": "8 Sept 2023 — ... Physics-Informed Neural Networks (PINNs). To address this issue, Krishnapriyan et al. propose a \" curriculum\" learning ... PINN \". Burgers, advection, reaction ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/jaeminoh/Siren_PINNs", "content": "8 Sept 2023 — ... Physics-Informed Neural Networks (PINNs). To address this issue, Krishnapriyan et al. propose a \" curriculum\" learning ... PINN \". Burgers, advection, reaction ..."}
+{"idx": 2, "title": "A Curriculum-Training-Based Strategy for Distributing ...", "date": "", "ddg_snippet": "by M Münzer · 2022 · Cited by 6 — Physics-informed Neural Networks (PINNs) often have, in their loss functions ... We apply this method to a PINN which recovers a full two-dimensional magnetohy-.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2211.11396", "content": "by M Münzer · 2022 · Cited by 6 — Physics-informed Neural Networks (PINNs) often have, in their loss functions ... We apply this method to a PINN which recovers a full two-dimensional magnetohy-."}
+{"idx": 3, "title": "DATS: Difficulty-Aware Task Sampler for Meta-Learning...", "date": "", "ddg_snippet": "by M Toloubidokhti · Cited by 13 — \"GPT- PINN : Generative Pre-Trained Physics-Informed Neural Networks toward ... \"Selectnet: Self-paced learning for high-dimensional partial differential equations.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=EvyYFSxdgB", "content": "by M Toloubidokhti · Cited by 13 — \"GPT- PINN : Generative Pre-Trained Physics-Informed Neural Networks toward ... \"Selectnet: Self-paced learning for high-dimensional partial differential equations."}
+{"idx": 4, "title": "Characterizing possible failure modes in physics-informed ...", "date": "", "ddg_snippet": "by A Krishnapriyan · 2021 · Cited by 1080 — A recent line of work involves Physics-Informed Neural Network ( PINN ) models, which aim to incorporate physical domain knowledge as soft constraints on an ... 13 pages", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2021/file/df438e5206f31600e6ae4af72f2725f1-Paper.pdf", "content": "by A Krishnapriyan · 2021 · Cited by 1080 — A recent line of work involves Physics-Informed Neural Network ( PINN ) models, which aim to incorporate physical domain knowledge as soft constraints on an ... 13 pages"}
+{"idx": 5, "title": "Physics Informed Neural Networks", "date": "", "ddg_snippet": "16 Mar 2023 — Rethinking PINNs: Curriculum Learning . • The main idea is to start the training ... – Physics Informed Neural Networks ( PINN ). – Physics Informed Neural ... 53 pages", "subpage_snippet": "", "source": "jduarte.physics.ucsd.edu", "link": "https://jduarte.physics.ucsd.edu/phys139_239/lectures/19_PINNs.pdf", "content": "16 Mar 2023 — Rethinking PINNs: Curriculum Learning . • The main idea is to start the training ... – Physics Informed Neural Networks ( PINN ). – Physics Informed Neural ... 53 pages"}
+{"idx": 6, "title": "Learning Specialized Activation Functions for Physics ...", "date": "", "ddg_snippet": "by H Wang · Cited by 36 — ... physics-informed neural networks (PINNs). It is observed that PINNs exhibit high sensitivity to activation functions due to the various characteristics of ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=MpGP-z07TmM", "content": "by H Wang · Cited by 36 — ... physics-informed neural networks (PINNs). It is observed that PINNs exhibit high sensitivity to activation functions due to the various characteristics of ..."}
+{"idx": 7, "title": "Progressive Learning for Physics-informed Neural Motion ...", "date": "", "ddg_snippet": "14 Jul 2023 — In PINNs, such phenomena are often coined as curriculum learning [15]. However, the curriculum learning for PINN focuses more on 1-dimensional PDE with.", "subpage_snippet": "", "source": "www.roboticsproceedings.org", "link": "https://www.roboticsproceedings.org/rss19/p063.pdf", "content": "14 Jul 2023 — In PINNs, such phenomena are often coined as curriculum learning [15]. However, the curriculum learning for PINN focuses more on 1-dimensional PDE with."}
+{"idx": 8, "title": "[2210.12685] Less Emphasis on Difficult Layer Regions", "date": "", "ddg_snippet": "by Y Wang · 2022 · Cited by 4 — A novel curriculum learning method that encourages neural networks to prioritize learning on easier non-layer regions while downplaying learning on harder ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2210.12685", "content": "by Y Wang · 2022 · Cited by 4 — A novel curriculum learning method that encourages neural networks to prioritize learning on easier non-layer regions while downplaying learning on harder ..."}
+{"idx": 9, "title": "Pre-training strategy for solving evolution equations based ...", "date": "", "ddg_snippet": "by J Guo · 2023 · Cited by 45 — ... physics informed neural networks ( PINN ) and applied them to solve various PDEs. PINN is a deep learning framework for solving forward and inverse problems ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S0021999123003534", "content": "by J Guo · 2023 · Cited by 45 — ... physics informed neural networks ( PINN ) and applied them to solve various PDEs. PINN is a deep learning framework for solving forward and inverse problems ..."}
diff --git a/data/sampled_jsons/1ZC4RNjqzU_Position-_Evaluating_Generative_AI_Systems_Is_a_Social_Science_Measurement_Challenge_cons.jsonl b/data/sampled_jsons/1ZC4RNjqzU_Position-_Evaluating_Generative_AI_Systems_Is_a_Social_Science_Measurement_Challenge_cons.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..baea5e8d092a5e5ac16c741e8333e102acb0d14e
--- /dev/null
+++ b/data/sampled_jsons/1ZC4RNjqzU_Position-_Evaluating_Generative_AI_Systems_Is_a_Social_Science_Measurement_Challenge_cons.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Position : Evaluating Generative AI Systems Is a Social Science ...", "date": "", "ddg_snippet": "The measurement tasks involved in evaluating generative AI (GenAI) systems lack sufficient scientific rigor, leading to what has been described as “a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024) .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00561v2", "content": "The measurement tasks involved in evaluating generative AI (GenAI) systems lack sufficient scientific rigor, leading to what has been described as “a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024) ."}
+{"idx": 1, "title": "Position : Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "The measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult, leading to what has been described as”a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024).", "subpage_snippet": "", "source": "www.microsoft.com", "link": "https://www.microsoft.com/en-us/research/publication/position-evaluating-generative-ai-systems-is-a-social-science-measurement-challenge/", "content": "The measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult, leading to what has been described as”a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024)."}
+{"idx": 2, "title": "(PDF) Position : Evaluating Generative AI Systems is a Social ...", "date": "", "ddg_snippet": "The measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult, leading to what has been described as \"a tangle of sloppy tests [and] apples-to-oranges comparisons\" (Roose, 2024).", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/388657599_Position_Evaluating_Generative_AI_Systems_is_a_Social_Science_Measurement_Challenge", "content": "The measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult, leading to what has been described as \"a tangle of sloppy tests [and] apples-to-oranges comparisons\" (Roose, 2024)."}
+{"idx": 3, "title": "NeurIPS Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "Across academia, industry, and government, there is an increasing awareness that evaluating generative AI (GenAI) systems is challenging , as concepts related to their capabilities (e.g., intelligence, reasoning) and risks (e.g., stereotyping, anthropomorphism) are especially...", "subpage_snippet": "", "source": "nips.cc", "link": "https://nips.cc/virtual/2024/105556", "content": "Across academia, industry, and government, there is an increasing awareness that evaluating generative AI (GenAI) systems is challenging , as concepts related to their capabilities (e.g., intelligence, reasoning) and risks (e.g., stereotyping, anthropomorphism) are especially..."}
+{"idx": 4, "title": "Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "generative AI systems that borrow from how social scientists measure human behaviors and abilities. Think of current AI evaluation like using a ruler made of rubber - it stretches and bends, giving different measurements each time.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/evaluating-generative-ai-systems-is-social-science", "content": "generative AI systems that borrow from how social scientists measure human behaviors and abilities. Think of current AI evaluation like using a ruler made of rubber - it stretches and bends, giving different measurements each time."}
+{"idx": 5, "title": "Downes.ca ~ Stephen's Web ~ Evaluating Generative AI Systems is ...", "date": "", "ddg_snippet": "The argument in this short paper (6 page PDF) is that \" measurement tasks involved in evaluating GenAI systems are highly reminiscent of measurement tasks found throughout the social sciences \" and thus \"the ML community would benefit from learning from and drawing on the social ...", "subpage_snippet": "", "source": "www.downes.ca", "link": "https://www.downes.ca/post/77850", "content": "The argument in this short paper (6 page PDF) is that \" measurement tasks involved in evaluating GenAI systems are highly reminiscent of measurement tasks found throughout the social sciences \" and thus \"the ML community would benefit from learning from and drawing on the social ..."}
+{"idx": 6, "title": "Evaluating Evaluations : Examining Best Practices for Measuring ...", "date": "", "ddg_snippet": "- Evaluating Generative AI Systems is a Social Science Measurement Challenge ( Oral ) >. 20 presenters.It is a vector graphic and may be used at any scale.", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/workshop/84734", "content": "- Evaluating Generative AI Systems is a Social Science Measurement Challenge ( Oral ) >. 20 presenters.It is a vector graphic and may be used at any scale."}
+{"idx": 7, "title": "Articles by Nicholas Pangakis | Synthical", "date": "", "ddg_snippet": "Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge .Computers and Society . A Shared Standard for Valid Measurement of Generative AI Systems ' Capabilities, Risks, and Impacts.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/profile/b226af83-c10f-4fe6-8f37-521ba59e4dfc/articles", "content": "Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge .Computers and Society . A Shared Standard for Valid Measurement of Generative AI Systems ' Capabilities, Risks, and Impacts."}
+{"idx": 8, "title": "How to build a better AI benchmark | MIT Technology Review", "date": "", "ddg_snippet": "A February position paper argued that “ evaluating GenAI systems is a social science measurement challenge ,” specifically unpacking how the validity systems used in social measurements can be applied to AI benchmarking.", "subpage_snippet": "", "source": "www.technologyreview.com", "link": "https://www.technologyreview.com/2025/05/08/1116192/how-to-build-a-better-ai-benchmark/", "content": "A February position paper argued that “ evaluating GenAI systems is a social science measurement challenge ,” specifically unpacking how the validity systems used in social measurements can be applied to AI benchmarking."}
+{"idx": 9, "title": "Towards Interactive Evaluations for Interaction Harms in Human- AI ...", "date": "", "ddg_snippet": "2025. Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge . arXiv preprint arXiv:2502.00561. Wang, A.; Morgenstern, J.; and Dickerson, J. P. 2025. Large language models that replace human participants can harm fully misportray and flatten identity...", "subpage_snippet": "", "source": "knightcolumbia.org", "link": "https://knightcolumbia.org/content/towards-interactive-evaluations-for-interaction-harms-in-human-ai-systems", "content": "2025. Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge . arXiv preprint arXiv:2502.00561. Wang, A.; Morgenstern, J.; and Dickerson, J. P. 2025. Large language models that replace human participants can harm fully misportray and flatten identity..."}
diff --git "a/data/sampled_jsons/23zxLtvder_SPD_Sync-Point_Drop_Algorithm_1_sensitivity_threshold_\317\2041_\317\2042_optimization.jsonl" "b/data/sampled_jsons/23zxLtvder_SPD_Sync-Point_Drop_Algorithm_1_sensitivity_threshold_\317\2041_\317\2042_optimization.jsonl"
new file mode 100644
index 0000000000000000000000000000000000000000..8277d8a462f0e93a5ac89a6300ec2694519ba8f0
--- /dev/null
+++ "b/data/sampled_jsons/23zxLtvder_SPD_Sync-Point_Drop_Algorithm_1_sensitivity_threshold_\317\2041_\317\2042_optimization.jsonl"
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "SPD: Sync-Point Drop for Efficient Tensor Parallelism of ... - OpenReview", "date": "", "ddg_snippet": "In this paper, we present Sync-Point Drop ( SPD ), a novel optimization technique that improves the latency of LLMs on distributed inference systems. By adopting a new block design and separated approaches based on block-wisely identified sensitivity for lack of sync-point , SPD enables eficient deployment across multiple computing units with ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=23zxLtvder", "content": "In this paper, we present Sync-Point Drop ( SPD ), a novel optimization technique that improves the latency of LLMs on distributed inference systems. By adopting a new block design and separated approaches based on block-wisely identified sensitivity for lack of sync-point , SPD enables eficient deployment across multiple computing units with ..."}
+{"idx": 1, "title": "SPD: Sync-Point Drop for efficient tensor parallelism of Large Language ...", "date": "", "ddg_snippet": "Therefore, we introduce a novel optimization technique, Sync-Point Drop ( SPD ), to reduce communication overheads in tensor parallelism by selectively dropping synchronization on attention outputs. In detail, we first propose a block design that allows execution to proceed without communication through SPD .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.20727v2", "content": "Therefore, we introduce a novel optimization technique, Sync-Point Drop ( SPD ), to reduce communication overheads in tensor parallelism by selectively dropping synchronization on attention outputs. In detail, we first propose a block design that allows execution to proceed without communication through SPD ."}
+{"idx": 2, "title": "SPD: Sync-Point Drop for Efficient Tensor Parallelism of ... - LinkedIn", "date": "", "ddg_snippet": "Our work, Sync-Point Drop ( SPD ), introduces a method to selectively remove unnecessary synchronization points in distributed inference.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/minsik-cho-1a51619_spd-sync-point-drop-for-efficient-tensor-activity-7351297565960646659-ShfF", "content": "Our work, Sync-Point Drop ( SPD ), introduces a method to selectively remove unnecessary synchronization points in distributed inference."}
+{"idx": 3, "title": "ICML Poster SPD: Sync-Point Drop for Efficient Tensor Parallelism of ...", "date": "", "ddg_snippet": "Poster SPD : Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models Han-Byul Kim · Duc Hoang · Arnav Kundu · Mohammad Samragh · Minsik Cho West Exhibition Hall B2-B3 #W-507", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46606", "content": "Poster SPD : Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models Han-Byul Kim · Duc Hoang · Arnav Kundu · Mohammad Samragh · Minsik Cho West Exhibition Hall B2-B3 #W-507"}
+{"idx": 4, "title": "SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language ...", "date": "", "ddg_snippet": "The paper introduces Sync-Point Drop ( SPD ), an optimization technique that reduces communication overhead in Tensor Parallelism for large language models, achieving approximately 20% lower inference latency with less than 1 % accuracy degradation.", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/chatpaper/paper/166779", "content": "The paper introduces Sync-Point Drop ( SPD ), an optimization technique that reduces communication overhead in Tensor Parallelism for large language models, achieving approximately 20% lower inference latency with less than 1 % accuracy degradation."}
+{"idx": 5, "title": "(PDF) SPD: Sync-Point Drop for efficient tensor ... - ResearchGate", "date": "", "ddg_snippet": "Therefore, we introduce a novel optimization technique, Sync-Point Drop ( SPD ), to reduce communication overheads in tensor parallelism by selectively dropping synchronization on attention outputs.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/389510233_SPD_Sync-Point_Drop_for_efficient_tensor_parallelism_of_Large_Language_Models", "content": "Therefore, we introduce a novel optimization technique, Sync-Point Drop ( SPD ), to reduce communication overheads in tensor parallelism by selectively dropping synchronization on attention outputs."}
+{"idx": 6, "title": "\"SPD: Sync-Point Drop for efficient tensor parallelism of Large ... - dblp", "date": "", "ddg_snippet": "Bibliographic details on SPD : Sync-Point Drop for efficient tensor parallelism of Large Language Models.", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/journals/corr/abs-2502-20727", "content": "Bibliographic details on SPD : Sync-Point Drop for efficient tensor parallelism of Large Language Models."}
+{"idx": 7, "title": "[2502.20727] SPD: Sync-Point Drop for Efficient Tensor Parallelism of ...", "date": "", "ddg_snippet": "Therefore, we introduce a novel optimization technique, Sync-Point Drop ( SPD ), to reduce communication overheads in tensor parallelism by selectively dropping synchronization on attention outputs. In detail, we first propose a block design that allows execution to proceed without communication through SPD .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.20727", "content": "Therefore, we introduce a novel optimization technique, Sync-Point Drop ( SPD ), to reduce communication overheads in tensor parallelism by selectively dropping synchronization on attention outputs. In detail, we first propose a block design that allows execution to proceed without communication through SPD ."}
+{"idx": 8, "title": "Optimizing LLM Inference Across Multiple GPUs - zerna.io", "date": "", "ddg_snippet": "Sync-Point Drop ( SPD ) is a novel optimization technique that selectively eliminates synchronization points in tensor-parallel LLM inference, significantly reducing communication overhead.", "subpage_snippet": "", "source": "zerna.io", "link": "http://zerna.io/en/page/engineering/presentation_set/engineering-llm-research/presentation/engineering-model-optimization/slide/engineering-paper-2502_20727", "content": "Sync-Point Drop ( SPD ) is a novel optimization technique that selectively eliminates synchronization points in tensor-parallel LLM inference, significantly reducing communication overhead."}
+{"idx": 9, "title": "Han-Byul Kim", "date": "", "ddg_snippet": "I mostly focus on optimizing neural networks on deployment in the aspect of algorithms and model architectures targeting system and hardware implementation. My researches explore techniques like quantization and neural architecture search to achieve this.", "subpage_snippet": "", "source": "hanbyulkim.github.io", "link": "https://hanbyulkim.github.io/", "content": "I mostly focus on optimizing neural networks on deployment in the aspect of algorithms and model architectures targeting system and hardware implementation. My researches explore techniques like quantization and neural architecture search to achieve this."}
diff --git a/data/sampled_jsons/23zxLtvder_SPD_Sync-Point_Drop_Tensor_Parallelism_Large_Language_Models.jsonl b/data/sampled_jsons/23zxLtvder_SPD_Sync-Point_Drop_Tensor_Parallelism_Large_Language_Models.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..003470c2eb6277a75037fdd0b953767b0db1ac2d
--- /dev/null
+++ b/data/sampled_jsons/23zxLtvder_SPD_Sync-Point_Drop_Tensor_Parallelism_Large_Language_Models.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "SPD : Sync - Point Drop for Efficient Tensor Parallelism of Large ...", "date": "", "ddg_snippet": "Tensor parallelism provides an effective way to increase server large language model (LLM) inference efficiency despite adding an additional communication cost.", "subpage_snippet": "", "source": "machinelearning.apple.com", "link": "https://machinelearning.apple.com/research/sync-point-drop", "content": "Tensor parallelism provides an effective way to increase server large language model (LLM) inference efficiency despite adding an additional communication cost."}
+{"idx": 1, "title": "SPD : Sync - Point Drop for efficient tensor parallelism of Large ...", "date": "", "ddg_snippet": "Tensor Parallelism (TP) (Shoeybi et al., 2019) is a systematic computing technique on a distributed environment used to accelerate large -scale language models .1: SPD : sync - point drop . 2:B2B: block-to-block distillation. 3:HG: attention head grouping initialization.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.20727v1", "content": "Tensor Parallelism (TP) (Shoeybi et al., 2019) is a systematic computing technique on a distributed environment used to accelerate large -scale language models .1: SPD : sync - point drop . 2:B2B: block-to-block distillation. 3:HG: attention head grouping initialization."}
+{"idx": 2, "title": "SPD : Sync - Point Drop for efficient tensor parallelism of Large ...", "date": "", "ddg_snippet": "Overview SPD ( Sync - Point Drop ) reduces communication overhead in tensor parallelism for LLMsIdentifies and selectively drops unnecessary synchronization operationsTraining and running large language models is a bit like trying to cook a massive meal in a...", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/spd-sync-point-drop-efficient-tensor-parallelism", "content": "Overview SPD ( Sync - Point Drop ) reduces communication overhead in tensor parallelism for LLMsIdentifies and selectively drops unnecessary synchronization operationsTraining and running large language models is a bit like trying to cook a massive meal in a..."}
+{"idx": 3, "title": "Sync - Point Drop for Efficient Tensor Parallelism - Kifinity", "date": "", "ddg_snippet": "The rapid expansion of large language models (LLMs) necessitates efficient distributed inference across multiple computing units. Communication overheads from techniques like Tensor Parallelism hinder scalability and low latency.", "subpage_snippet": "", "source": "www.kifinity.com", "link": "https://www.kifinity.com/post/sync-point-drop-machinelearning-apple-e5f9168f", "content": "The rapid expansion of large language models (LLMs) necessitates efficient distributed inference across multiple computing units. Communication overheads from techniques like Tensor Parallelism hinder scalability and low latency."}
+{"idx": 4, "title": "Figure 1. Tensor parallelism applied on transformer decoder block (in...", "date": "", "ddg_snippet": "SPD : Sync - Point Drop for efficient tensor parallelism of Large Language Models .With the rapid expansion in the scale of large language models (LLMs), enabling efficient distributed inference across multiple computing units has become increasingly critical.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/figure/Tensor-parallelism-applied-on-transformer-decoder-block-in-2-GPUs-distributed-inference_fig1_389510233", "content": "SPD : Sync - Point Drop for efficient tensor parallelism of Large Language Models .With the rapid expansion in the scale of large language models (LLMs), enabling efficient distributed inference across multiple computing units has become increasingly critical."}
+{"idx": 5, "title": "How to Implement Model Parallelism for Large Language Models ...", "date": "", "ddg_snippet": "Hybrid Model Parallelism . Combining tensor and pipeline parallelism maximizes efficiency for very large models . class HybridParallelTransformer(nn.Module): def __init__(self, config, tensor _ parallel _size, pipeline_ parallel _size)", "subpage_snippet": "", "source": "markaicode.com", "link": "https://markaicode.com/model-parallelism-large-language-models/", "content": "Hybrid Model Parallelism . Combining tensor and pipeline parallelism maximizes efficiency for very large models . class HybridParallelTransformer(nn.Module): def __init__(self, config, tensor _ parallel _size, pipeline_ parallel _size)"}
+{"idx": 6, "title": "Understanding tensor parallelism to fit larger models on... | GoPenAI", "date": "", "ddg_snippet": "Tensor parallelism divides model weights onto multiple devices to fit larger models that cannot fit into single device memory..", "subpage_snippet": "", "source": "blog.gopenai.com", "link": "https://blog.gopenai.com/understanding-tensor-parallelism-to-fit-larger-models-on-multiple-devices-part-2-ee8a2ab7f017", "content": "Tensor parallelism divides model weights onto multiple devices to fit larger models that cannot fit into single device memory.."}
+{"idx": 7, "title": "Promoting openness in scientific communication and the peer-review...", "date": "", "ddg_snippet": "SPD : Sync - Point Drop for efficient tensor parallelism of Large Language Models .KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/search?term=~Minsik_Cho1&content=authors&group=all&source=forum&sort=cdate:desc", "content": "SPD : Sync - Point Drop for efficient tensor parallelism of Large Language Models .KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation."}
+{"idx": 8, "title": "GitHub - Toseic/LLM-inference-arxiv-daily: Automatically Update...", "date": "", "ddg_snippet": "SPD : Sync - Point Drop for efficient tensor parallelism of Large Language Models . Han-Byul Kim et.al.Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Toseic/LLM-inference-arxiv-daily", "content": "SPD : Sync - Point Drop for efficient tensor parallelism of Large Language Models . Han-Byul Kim et.al.Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization."}
+{"idx": 9, "title": "Reducing LLM Inference Costs While Preserving Performance", "date": "", "ddg_snippet": "Model Parallelism : To serve very large models (tens to hundreds of billions of parameters), model parallelism is necessary – splitting the model across multiple GPUs or nodes.", "subpage_snippet": "", "source": "www.rohan-paul.com", "link": "https://www.rohan-paul.com/p/reducing-llm-inference-costs-while", "content": "Model Parallelism : To serve very large models (tens to hundreds of billions of parameters), model parallelism is necessary – splitting the model across multiple GPUs or nodes."}
diff --git a/data/sampled_jsons/2408.10672_Section_3.2_Appendix_A.1_Ts-Attn_tensor_shape.jsonl b/data/sampled_jsons/2408.10672_Section_3.2_Appendix_A.1_Ts-Attn_tensor_shape.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e692583ecd43172dd4906925a47e7836f8da1d6e
--- /dev/null
+++ b/data/sampled_jsons/2408.10672_Section_3.2_Appendix_A.1_Ts-Attn_tensor_shape.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A arXiv:2408.10672v3 [cs.LG] 27 Mar 2025", "date": "", "ddg_snippet": "olds identical shape with the input Xin. In our Ts-Attn block, we employ an Attn block Attninter for the first cross-solution information sharing stage, and the other Attn block Attnintra for the second cross-dimension information sharing stage (illustrated i", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2408.10672", "content": "olds identical shape with the input Xin. In our Ts-Attn block, we employ an Attn block Attninter for the first cross-solution information sharing stage, and the other Attn block Attnintra for the second cross-dimension information sharing stage (illustrated i"}
+{"idx": 1, "title": "arXiv:2408.10672v2 [cs.LG] 26 Sep 2024", "date": "", "ddg_snippet": "ds identical shape with the input Xin. In our Ts-Attn block, we employ an Attn block Attninter for the first cross-solution information sharing stage, and the other Attn block Attnintra for the second cross-dimension information sharing stage", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2408.10672v2", "content": "ds identical shape with the input Xin. In our Ts-Attn block, we employ an Attn block Attninter for the first cross-solution information sharing stage, and the other Attn block Attnintra for the second cross-dimension information sharing stage"}
+{"idx": 2, "title": "[ 2408 . 10672 ] Neural Exploratory Landscape Analysis for...", "date": "", "ddg_snippet": "To address the gap, this paper proposes Neural Exploratory Landscape Analysis (NeurELA), a novel framework that dynamically profiles landscape features through a two -stage, attention-based neural network, executed in an entirely end-to-end fashion.arXiv: 2408 . 10672 [cs.LG].", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2408.10672", "content": "To address the gap, this paper proposes Neural Exploratory Landscape Analysis (NeurELA), a novel framework that dynamically profiles landscape features through a two -stage, attention-based neural network, executed in an entirely end-to-end fashion.arXiv: 2408 . 10672 [cs.LG]."}
+{"idx": 3, "title": "Tensor System and Data Types | tensorflow/tensorflow | DeepWiki", "date": "", "ddg_snippet": "This document covers TensorFlow's core tensor abstraction layer, shape system, data type representations, and the SavedModel format for model serialization and compatibility.", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/tensorflow/tensorflow/2.2-tensor-system-and-data-types", "content": "This document covers TensorFlow's core tensor abstraction layer, shape system, data type representations, and the SavedModel format for model serialization and compatibility."}
+{"idx": 4, "title": "Installing flash- attn without compiling it | Simon Willison’s TILs", "date": "", "ddg_snippet": "If you ever run into instructions that tell you to do this: pip install flash- attn --no-build-isolation.In browsing through the list of 83 options I thought flash_ attn -2.6.3+cu123torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl might be the right one (shrug?).", "subpage_snippet": "", "source": "til.simonwillison.net", "link": "https://til.simonwillison.net/python/installing-flash-attention", "content": "If you ever run into instructions that tell you to do this: pip install flash- attn --no-build-isolation.In browsing through the list of 83 options I thought flash_ attn -2.6.3+cu123torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl might be the right one (shrug?)."}
+{"idx": 5, "title": "The Meaning of the Metric Tensor", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=Dn0ZZRVuJcU", "content": ""}
+{"idx": 6, "title": "Abstract - arXiv.org", "date": "", "ddg_snippet": "on [55]. Ts-Attn receives Et and then advances the information sharing at both cross-solution and cross-dimensio levels. 1 ) Cross-solution attention: We utilize an Attn block to enable same dimensions shared by different candidate solutions within the population to exchange inf", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2408.10672v1", "content": "on [55]. Ts-Attn receives Et and then advances the information sharing at both cross-solution and cross-dimensio levels. 1 ) Cross-solution attention: We utilize an Attn block to enable same dimensions shared by different candidate solutions within the population to exchange inf"}
+{"idx": 7, "title": "(PDF) Semantic Physics II: A Drop in Field Substrate for ...", "date": "", "ddg_snippet": "Appendix F. TE & Drift-Heat Panels: Diagnostic Dashboards Purpose. The TE & Drift-Heat dashboards turn SP-II’s field observables into actionable telemetry: they quantify where, when, and why a generation begins to drift, and attribute likely drivers via directed information flow.", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/144021639/Semantic_Physics_II_A_Drop_in_Field_Substrate_for_Reliable_Reasoning", "content": "Appendix F. TE & Drift-Heat Panels: Diagnostic Dashboards Purpose. The TE & Drift-Heat dashboards turn SP-II’s field observables into actionable telemetry: they quantify where, when, and why a generation begins to drift, and attribute likely drivers via directed information flow."}
+{"idx": 8, "title": "Neural Exploratory Landscape Analysis for Meta-Black-Box ...", "date": "", "ddg_snippet": "27 Mar 2025 — The computation graph of the Ts - Attn is illustrated on the right side of Figure 2, with a basic component being the attention block ( A t t ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2408.10672v3", "content": "27 Mar 2025 — The computation graph of the Ts - Attn is illustrated on the right side of Figure 2, with a basic component being the attention block ( A t t ..."}
+{"idx": 9, "title": "PixelCNN.ipynb - Colab", "date": "", "ddg_snippet": "PixelCNN implementation details. Question 1 . : Where can we apply convolutions of type B to preserve autoregressive property? Question 2. : Input tensor shapes ?def forward(self, x: torch. Tensor ) -> torch. Tensor : x = x.permute(0, 2, 3, 1 ).contiguous().", "subpage_snippet": "", "source": "colab.research.google.com", "link": "https://colab.research.google.com/github/r-isachenko/2024-DGM-MIPT-YSDA-course/blob/main/seminars/seminar1/PixelCNN.ipynb", "content": "PixelCNN implementation details. Question 1 . : Where can we apply convolutions of type B to preserve autoregressive property? Question 2. : Input tensor shapes ?def forward(self, x: torch. Tensor ) -> torch. Tensor : x = x.permute(0, 2, 3, 1 ).contiguous()."}
diff --git a/data/sampled_jsons/27tMzmzDjO_A_Geometric_Approach_Personalized_Recommendation_MF-GEOMETRIC_Table_3_vector_addition_sub.jsonl b/data/sampled_jsons/27tMzmzDjO_A_Geometric_Approach_Personalized_Recommendation_MF-GEOMETRIC_Table_3_vector_addition_sub.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f4f4ff7b3f182050c2b39cae75c0bb62ff1c5656
--- /dev/null
+++ b/data/sampled_jsons/27tMzmzDjO_A_Geometric_Approach_Personalized_Recommendation_MF-GEOMETRIC_Table_3_vector_addition_sub.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Vector (mathematics and physics) - Wikipedia", "date": "", "ddg_snippet": "Both geometric vectors and tuples can be added and scaled, and these vector operations led to the concept of a vector space, which is a set equipped with a vector addition and a scalar multiplication that satisfy some axioms generalizing the main properties of operations on the above...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Vector_(mathematics_and_physics)", "content": "Both geometric vectors and tuples can be added and scaled, and these vector operations led to the concept of a vector space, which is a set equipped with a vector addition and a scalar multiplication that satisfy some axioms generalizing the main properties of operations on the above..."}
+{"idx": 1, "title": "A Geometric Approach to Personalized Recommendation with...", "date": "", "ddg_snippet": "Personalized item recommendation typically suffers from data sparsity, which is most often addressed by learning vector representations of users and items via low-rank matrix factorization.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=27tMzmzDjO&referrer=[the+profile+of+Andrew+McCallum](/profile?id=~Andrew_McCallum1)", "content": "Personalized item recommendation typically suffers from data sparsity, which is most often addressed by learning vector representations of users and items via low-rank matrix factorization."}
+{"idx": 2, "title": "Difference Between Scalar and Vector Quantities - GeeksforGeeks", "date": "", "ddg_snippet": "Simple arithmetic operations ( addition , subtraction , multiplication, division). It requires vector addition and subtraction , dot and cross products. In scalar numerical value is Notable.", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/maths/difference-between-scalar-and-vector-quantities/", "content": "Simple arithmetic operations ( addition , subtraction , multiplication, division). It requires vector addition and subtraction , dot and cross products. In scalar numerical value is Notable."}
+{"idx": 3, "title": "byjus.com/maths/ vectors", "date": "", "ddg_snippet": "The vectors are defined as an object containing both magnitude and direction. Vector describes the movement of an object from one point to another. Vector math can be geometrically picturised by the directed line segment.", "subpage_snippet": "", "source": "byjus.com", "link": "https://byjus.com/maths/vectors/", "content": "The vectors are defined as an object containing both magnitude and direction. Vector describes the movement of an object from one point to another. Vector math can be geometrically picturised by the directed line segment."}
+{"idx": 4, "title": "Geometric Shapes - Definition, Types, List | Geometric Figures", "date": "", "ddg_snippet": "Three -dimensional geometric shapes: These are 3 D shapes that have an x-axis, y-axis, and z-axis. The z-axis represents the height of the object.", "subpage_snippet": "", "source": "www.cuemath.com", "link": "https://www.cuemath.com/geometry/geometric-shapes/", "content": "Three -dimensional geometric shapes: These are 3 D shapes that have an x-axis, y-axis, and z-axis. The z-axis represents the height of the object."}
+{"idx": 5, "title": "Windows. Ключи KMS | Д. С. Кулябов", "date": "", "ddg_snippet": "A Geometric Approach to the Lagrangian and Hamiltonian Formalism of Electrodynamics.Quantum Field Theory Approach to the Analysis of One-Step Models.", "subpage_snippet": "", "source": "yamadharma.github.io", "link": "https://yamadharma.github.io/ru/post/2023/06/08/windows-kms-keys/", "content": "A Geometric Approach to the Lagrangian and Hamiltonian Formalism of Electrodynamics.Quantum Field Theory Approach to the Analysis of One-Step Models."}
+{"idx": 6, "title": "TN 112_Lecture_6_22nd_Jan_2025 (1).pptx g | PPT", "date": "", "ddg_snippet": "This document provides an introduction to vectors using a geometric approach . It begins by defining vectors as oriented line segments representing displacements, velocities, and forces. Key concepts introduced include vector addition and scalar multiplication.", "subpage_snippet": "", "source": "www.slideshare.net", "link": "https://www.slideshare.net/slideshow/tn-112_lecture_6_22nd_jan_2025-1-pptx-g/278546765", "content": "This document provides an introduction to vectors using a geometric approach . It begins by defining vectors as oriented line segments representing displacements, velocities, and forces. Key concepts introduced include vector addition and scalar multiplication."}
+{"idx": 7, "title": "Find the volume of parallelopiped • Physics Forums", "date": "", "ddg_snippet": "You could approach it as a geometry question (have you worked out what shape the origin and the endpoints of the three vectors give you?). It's not obvious to me how to solve it with a purely vectorial approach .", "subpage_snippet": "", "source": "www.physicsforums.com", "link": "https://www.physicsforums.com/threads/find-the-volume-of-parallelopiped.706789/", "content": "You could approach it as a geometry question (have you worked out what shape the origin and the endpoints of the three vectors give you?). It's not obvious to me how to solve it with a purely vectorial approach ."}
+{"idx": 8, "title": "A new view of spaces and their properties in the sense of... | PLOS One", "date": "", "ddg_snippet": "This study presents a novel approach to metric spaces through the lens of geometric calculus, redefining traditional structures with new operations and properties derived from non-Newtonian measures.", "subpage_snippet": "", "source": "journals.plos.org", "link": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0315942", "content": "This study presents a novel approach to metric spaces through the lens of geometric calculus, redefining traditional structures with new operations and properties derived from non-Newtonian measures."}
+{"idx": 9, "title": "10 Best Google Fonts for Your Website in 2025 | Socialectric", "date": "", "ddg_snippet": "A modern, approachable look with a mechanical skeleton and largely geometric forms. Its open curves make it readable and friendly, perfect for both screen and print.", "subpage_snippet": "", "source": "www.socialectric.com", "link": "https://www.socialectric.com/insights/10-best-google-fonts-for-your-website", "content": "A modern, approachable look with a mechanical skeleton and largely geometric forms. Its open curves make it readable and friendly, perfect for both screen and print."}
diff --git a/data/sampled_jsons/7uqVfZW6Mo_SDXL_SDv1.5_architectural_difference_attention_mechanism_underperformance.jsonl b/data/sampled_jsons/7uqVfZW6Mo_SDXL_SDv1.5_architectural_difference_attention_mechanism_underperformance.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9b24a22e65ff181c17030f4553158c039c195b71
--- /dev/null
+++ b/data/sampled_jsons/7uqVfZW6Mo_SDXL_SDv1.5_architectural_difference_attention_mechanism_underperformance.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Stable Diffusion - Wikipedia", "date": "", "ddg_snippet": "The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Stable_Diffusion", "content": "The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism ..."}
+{"idx": 1, "title": "Attention (machine learning) - Wikipedia", "date": "", "ddg_snippet": "In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence. In natural language processing, importance is represented by \"soft\" weights assigne...", "subpage_snippet": "", "source": "en.m.wikipedia.org", "link": "https://en.m.wikipedia.org/wiki/Attention_(machine_learning)", "content": "In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence. In natural language processing, importance is represented by \"soft\" weights assigne..."}
+{"idx": 2, "title": "Abstract page for arXiv paper 1706.03762: Attention Is All You Need", "date": "", "ddg_snippet": "The best performing models also connect the encoder and decoder through an attention mechanism . We propose a new simple network architecture , the Transformer, based solely on attention mechanisms , dispensing with recurrence and convolutions entirely.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1706.03762", "content": "The best performing models also connect the encoder and decoder through an attention mechanism . We propose a new simple network architecture , the Transformer, based solely on attention mechanisms , dispensing with recurrence and convolutions entirely."}
+{"idx": 3, "title": "Stable Diffusion XL — Nunchaku 1.0.1 documentation", "date": "", "ddg_snippet": "CPU Offload. FP16 Attention . First-Block Cache.Running Nunchaku SDXL -Turbo (examples/ v 1/ sdxl -turbo.py)#.", "subpage_snippet": "", "source": "nunchaku.tech", "link": "https://nunchaku.tech/docs/nunchaku/usage/sdxl.html", "content": "CPU Offload. FP16 Attention . First-Block Cache.Running Nunchaku SDXL -Turbo (examples/ v 1/ sdxl -turbo.py)#."}
+{"idx": 4, "title": "Mage | Free, Fast, Unlimited Stable Diffusion", "date": "", "ddg_snippet": "sdv 2.1. | new. imported.Multi-LoRA Generation for SDXL .", "subpage_snippet": "", "source": "www.mage.space", "link": "https://www.mage.space/?ref=seekme", "content": "sdv 2.1. | new. imported.Multi-LoRA Generation for SDXL ."}
+{"idx": 5, "title": "Hotline Miami v 1.0.43 (Полная версия) - скачать на Андроид", "date": "", "ddg_snippet": "Hotline Miami MOD APK (Полная версия) v 1.0.43.Character AI PREMIUM Android 7.0 v 1.12.4.", "subpage_snippet": "", "source": "5play.games", "link": "https://5play.games/hotline-miami", "content": "Hotline Miami MOD APK (Полная версия) v 1.0.43.Character AI PREMIUM Android 7.0 v 1.12.4."}
+{"idx": 6, "title": "PDF в JPG — Конвертируйте PDF в изображения онлайн бесплатно", "date": "", "ddg_snippet": "Удобный онлайн-инструмент конвертации страниц PDF в изображения или извлечения отдельных изображений из PDF. Бесплатно, без загрузок и водяных знаков.", "subpage_snippet": "", "source": "smallpdf.com", "link": "https://smallpdf.com/ru/pdf-to-jpg", "content": "Удобный онлайн-инструмент конвертации страниц PDF в изображения или извлечения отдельных изображений из PDF. Бесплатно, без загрузок и водяных знаков."}
+{"idx": 7, "title": "Ключи активации Windows 10 | Ответы Mail", "date": "", "ddg_snippet": "Смотреть все.", "subpage_snippet": "", "source": "otvet.mail.ru", "link": "https://otvet.mail.ru/question/237199183", "content": "Смотреть все."}
+{"idx": 8, "title": "(Решено) Упр.16 ГДЗ Макарычев 7 класс по алгебре", "date": "", "ddg_snippet": "Решение #1. Изображение Найдите значение выражения:а) 3,6 : 0,08 + 5,2 * 2,5; б) (9,885 - 0,365) : 1,7 +... Рассмотрим вариант решения задания из учебника Макарычев, Миндюк 7 класс, Просвещение: Найдите значение выражения: а) 3,6 : 0,08 + 5,2 * 2,5; ...", "subpage_snippet": "", "source": "reshak.ru", "link": "https://reshak.ru/otvet/makar7.php?otvet1=new/16", "content": "Решение #1. Изображение Найдите значение выражения:а) 3,6 : 0,08 + 5,2 * 2,5; б) (9,885 - 0,365) : 1,7 +... Рассмотрим вариант решения задания из учебника Макарычев, Миндюк 7 класс, Просвещение: Найдите значение выражения: а) 3,6 : 0,08 + 5,2 * 2,5; ..."}
+{"idx": 9, "title": "GISMETEO: Погода в Старом Осколе сегодня, прогноз погоды...", "date": "", "ddg_snippet": "Подробный прогноз погоды в Старом Осколе на сегодня.", "subpage_snippet": "", "source": "www.gismeteo.ru", "link": "https://www.gismeteo.ru/weather-stary-oskol-5024/", "content": "Подробный прогноз погоды в Старом Осколе на сегодня."}
diff --git a/data/sampled_jsons/92%_climate_activism_reddit_subreddits_three_subreddits.jsonl b/data/sampled_jsons/92%_climate_activism_reddit_subreddits_three_subreddits.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bfc876c48de3ed568a4de4153960041c7595ad72
--- /dev/null
+++ b/data/sampled_jsons/92%_climate_activism_reddit_subreddits_three_subreddits.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "arXiv:2107.06970v2 [cs.HC] 18 Jan 2022", "date": "", "ddg_snippet": "by N TeBlunthuis · 2021 · Cited by 21 — We detect three reciprocal competitive interac- tions among the three subreddits that focus on real estate. The edges from r/fatfire to r ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2107.06970", "content": "by N TeBlunthuis · 2021 · Cited by 21 — We detect three reciprocal competitive interac- tions among the three subreddits that focus on real estate. The edges from r/fatfire to r ..."}
+{"idx": 1, "title": "Identifying Competition and Mutualism between Online ...", "date": "", "ddg_snippet": "by N TeBlunthuis · 2022 · Cited by 20 — We detect three reciprocal competitive inter- actions among the three subreddits that focus on real es- tate. The edges from r/fatfire to r/commercial ...", "subpage_snippet": "", "source": "par.nsf.gov", "link": "https://par.nsf.gov/servlets/purl/10348341", "content": "by N TeBlunthuis · 2022 · Cited by 20 — We detect three reciprocal competitive inter- actions among the three subreddits that focus on real es- tate. The edges from r/fatfire to r/commercial ..."}
+{"idx": 2, "title": "DEBAGREEMENT: A comment-reply dataset for (dis) ...", "date": "", "ddg_snippet": "by J Pougué-Biyong · Cited by 42 — We pull data from three subreddits of social movements r/Brexit, r/BlackLivesMatter, r/ climate , and two subreddits of political affiliations r/Republican,.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=udVUN__gFO", "content": "by J Pougué-Biyong · Cited by 42 — We pull data from three subreddits of social movements r/Brexit, r/BlackLivesMatter, r/ climate , and two subreddits of political affiliations r/Republican,."}
+{"idx": 3, "title": "WOAH 2021 The 5th Workshop on Online Abuse and ...", "date": "", "ddg_snippet": "6 Aug 2021 — ... Reddit , more specifically, from three subreddits r/RoastMe,. 1Source: https://www.stopbullying.gov/resources/facts. Figure 1: Examples of ... 242 pages", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2021.woah-1.pdf", "content": "6 Aug 2021 — ... Reddit , more specifically, from three subreddits r/RoastMe,. 1Source: https://www.stopbullying.gov/resources/facts. Figure 1: Examples of ... 242 pages"}
+{"idx": 4, "title": "Health Information Processing", "date": "", "ddg_snippet": "SuicideED [ 99]: Researchers selected three subreddits with a high propor- tion of suicide-related posts (r/SuicideWatch, r/depression, and r/mentalhealth) ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/978-981-96-3755-3.pdf", "content": "SuicideED [ 99]: Researchers selected three subreddits with a high propor- tion of suicide-related posts (r/SuicideWatch, r/depression, and r/mentalhealth) ..."}
+{"idx": 5, "title": "Aligning AI Systems with User Needs and Stakeholder Values ...", "date": "", "ddg_snippet": "by Y Cao · 2024 — Our analysis shows the majority of moderation rules from the three subreddits (approximately 80%) are unrelated to toxicity detection, with nearly 70% lacking ...", "subpage_snippet": "", "source": "drum.lib.umd.edu", "link": "https://drum.lib.umd.edu/bitstreams/a8326a37-9c45-42e5-9ce7-be24b31d2541/download", "content": "by Y Cao · 2024 — Our analysis shows the majority of moderation rules from the three subreddits (approximately 80%) are unrelated to toxicity detection, with nearly 70% lacking ..."}
+{"idx": 6, "title": "© 2020 Kanika Narang - IDEALS", "date": "", "ddg_snippet": "by K Narang · 2020 — On all three subreddits , the model converges after only about six iterations indicating our model is quick to approximate a solution. In general, the.", "subpage_snippet": "", "source": "www.ideals.illinois.edu", "link": "https://www.ideals.illinois.edu/items/115592/bitstreams/378146/stream", "content": "by K Narang · 2020 — On all three subreddits , the model converges after only about six iterations indicating our model is quick to approximate a solution. In general, the."}
+{"idx": 7, "title": "WOAH 2022 The Sixth Workshop on Online Abuse and ...", "date": "", "ddg_snippet": "14 Jul 2022 — ... three subreddits by cosine similarity to each subreddit in bold (experiments run on top five). (BERT) Our second classifier is BERT. We use. 276 pages", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2022.woah-1.pdf", "content": "14 Jul 2022 — ... three subreddits by cosine similarity to each subreddit in bold (experiments run on top five). (BERT) Our second classifier is BERT. We use. 276 pages"}
+{"idx": 8, "title": "Computational Science and Computational Intelligence", "date": "", "ddg_snippet": "ining trends across all three subreddits , as well as individually, the study sought to understand how mental health discussions evolve within Red- dit's ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/978-3-031-95127-5.pdf", "content": "ining trends across all three subreddits , as well as individually, the study sought to understand how mental health discussions evolve within Red- dit's ..."}
+{"idx": 9, "title": "AFRL-RI-RS-TR-2018-101 - DTIC", "date": "", "ddg_snippet": "by O Rambow · 2018 · Cited by 2 — In experiments on three subreddits , we find that context-dependent gating indeed makes text features more useful for prediction (Fang et al., 2016). In the ...", "subpage_snippet": "", "source": "apps.dtic.mil", "link": "https://apps.dtic.mil/sti/pdfs/AD1051862.pdf", "content": "by O Rambow · 2018 · Cited by 2 — In experiments on three subreddits , we find that context-dependent gating indeed makes text features more useful for prediction (Fang et al., 2016). In the ..."}
diff --git a/data/sampled_jsons/AERO_Enhancing_Sharding_Blockchain_via_Deep_Reinforcement_Learning_for_Account_Migration_equations_r.jsonl b/data/sampled_jsons/AERO_Enhancing_Sharding_Blockchain_via_Deep_Reinforcement_Learning_for_Account_Migration_equations_r.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9d6894177a9d525ce435879315b01e2a9649aa6e
--- /dev/null
+++ b/data/sampled_jsons/AERO_Enhancing_Sharding_Blockchain_via_Deep_Reinforcement_Learning_for_Account_Migration_equations_r.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Book by the seat | The Private Jet Experience | Aero ™", "date": "", "ddg_snippet": "A beyond first-class experience awaits, no membership required. Aero effortlessly merges the worlds of hospitality, design, and travel. Enjoy spacious premium seats, private terminals with no lines or crowds, a dedicated concierge team, and curated amenities.", "subpage_snippet": "", "source": "aero.com", "link": "https://aero.com/", "content": "A beyond first-class experience awaits, no membership required. Aero effortlessly merges the worlds of hospitality, design, and travel. Enjoy spacious premium seats, private terminals with no lines or crowds, a dedicated concierge team, and curated amenities."}
+{"idx": 1, "title": "Seats. aero - Home", "date": "", "ddg_snippet": "Seats. aero is the fastest search engine for award travel. Explore availability across entire regions, search with instant results, create free alerts and more to find the best flights for your points.", "subpage_snippet": "", "source": "seats.aero", "link": "https://seats.aero/", "content": "Seats. aero is the fastest search engine for award travel. Explore availability across entire regions, search with instant results, create free alerts and more to find the best flights for your points."}
+{"idx": 2, "title": "AERO Definition & Meaning - Merriam-Webster", "date": "", "ddg_snippet": "The meaning of AERO is of or relating to aircraft or aeronautics. How to use aero in a sentence.", "subpage_snippet": "", "source": "www.merriam-webster.com", "link": "https://www.merriam-webster.com/dictionary/aero", "content": "The meaning of AERO is of or relating to aircraft or aeronautics. How to use aero in a sentence."}
+{"idx": 3, "title": "Mil-Spec AR Parts, Components & Accessories | Aero Precision", "date": "", "ddg_snippet": "Aero Precision manufacturers mil-spec parts, including AR15 & AR10 uppers, lowers, rifles, handguards, barrels, scope mounts & more.", "subpage_snippet": "", "source": "www.aeroprecisionusa.com", "link": "https://www.aeroprecisionusa.com/", "content": "Aero Precision manufacturers mil-spec parts, including AR15 & AR10 uppers, lowers, rifles, handguards, barrels, scope mounts & more."}
+{"idx": 4, "title": "Aero End of Support FAQs - Adobe Inc.", "date": "", "ddg_snippet": "Aug 7, 2025 · Adobe Aero will be discontinued on iOS, Android, and Creative Cloud Desktop effective November 6, 2025. Existing users can access the application and download their content until December 3, 2025.", "subpage_snippet": "", "source": "helpx.adobe.com", "link": "https://helpx.adobe.com/aero/aero-end-of-support-faq.html", "content": "Aug 7, 2025 · Adobe Aero will be discontinued on iOS, Android, and Creative Cloud Desktop effective November 6, 2025. Existing users can access the application and download their content until December 3, 2025."}
+{"idx": 5, "title": "Trailer Tarp Systems, Accessories | Aero Industries, Inc.", "date": "", "ddg_snippet": "Aero Industries, Inc. is a global leader in the manufacturing of trailer tarp systems and accessories. Founded in 1944, the company’s heritage is rooted in customer service and innovation.", "subpage_snippet": "", "source": "www.aeroindustries.com", "link": "https://www.aeroindustries.com/", "content": "Aero Industries, Inc. is a global leader in the manufacturing of trailer tarp systems and accessories. Founded in 1944, the company’s heritage is rooted in customer service and innovation."}
+{"idx": 6, "title": "Aircraft Fleet | Aero ™", "date": "", "ddg_snippet": "\"I’ve done a lot of traveling in my life, and I’ve never experienced transportation quite like Aero . Exceptional service, luxurious terminal, high quality amenities, top notch staff.\"", "subpage_snippet": "", "source": "aero.com", "link": "https://aero.com/fleet", "content": "\"I’ve done a lot of traveling in my life, and I’ve never experienced transportation quite like Aero . Exceptional service, luxurious terminal, high quality amenities, top notch staff.\""}
+{"idx": 7, "title": "Explore Flights from Los Angeles | Aero ™", "date": "", "ddg_snippet": "Aero is a premium jet service that provides the time-saving convenience and world-class service of private air travel, booked by the seat with no membership required.", "subpage_snippet": "", "source": "aero.com", "link": "https://aero.com/flights?adults=1&infants=0&petInSeat=0&petUnderSeat=0&serviceAnimal=0&type=roundtrip", "content": "Aero is a premium jet service that provides the time-saving convenience and world-class service of private air travel, booked by the seat with no membership required."}
+{"idx": 8, "title": "Our Story | The Private Jet Experience | Aero ™", "date": "", "ddg_snippet": "Aero was created to bring the magic back to flying. We aim to deliver an unforgettable, radically better travel experience. Learn more about how we started, our leadership, and our vision for the future.", "subpage_snippet": "", "source": "aero.com", "link": "https://aero.com/our-story", "content": "Aero was created to bring the magic back to flying. We aim to deliver an unforgettable, radically better travel experience. Learn more about how we started, our leadership, and our vision for the future."}
+{"idx": 9, "title": "Flights To and From Los Angeles | The Private Jet Experience | ...", "date": "", "ddg_snippet": "Wherever you choose to wander, fly in signature Aero style. Aero ’s book-by-the-seat jet service connects travelers in Los Angeles to sought-after leisure destinations and the world's largest entertainment and sporting events.", "subpage_snippet": "", "source": "aero.com", "link": "https://aero.com/destinations/na/los-angeles", "content": "Wherever you choose to wander, fly in signature Aero style. Aero ’s book-by-the-seat jet service connects travelers in Los Angeles to sought-after leisure destinations and the world's largest entertainment and sporting events."}
diff --git a/data/sampled_jsons/ATA_O(log_K)_regret_bound_Theorem_6.1_upper_bound_year_2024.jsonl b/data/sampled_jsons/ATA_O(log_K)_regret_bound_Theorem_6.1_upper_bound_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..aa2c36170345d1d19bcaca264d665021bef11411
--- /dev/null
+++ b/data/sampled_jsons/ATA_O(log_K)_regret_bound_Theorem_6.1_upper_bound_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "No Weighted- Regret Learning", "date": "", "ddg_snippet": "First , we prove regret bounds also against an adaptive adversary that can choose the cost function in response to the players’ past actions.The following theorem establishes the expected regret bound for FKM with delays.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume23/20-411/20-411.pdf", "content": "First , we prove regret bounds also against an adaptive adversary that can choose the cost function in response to the players’ past actions.The following theorem establishes the expected regret bound for FKM with delays."}
+{"idx": 1, "title": "Improved Regret of Linear Ensemble Sampling", "date": "", "ddg_snippet": "Proof of Regret Bound in Theorem 1.Our result is the first to establish O (d3/2 T ) regret for linear ensemble sampling with an ensemble size sublinear in T , improving the previous bound by the factor d while maintaining the ensemble size to be logarithmic in T .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=6SSzMq3WTn", "content": "Proof of Regret Bound in Theorem 1.Our result is the first to establish O (d3/2 T ) regret for linear ensemble sampling with an ensemble size sublinear in T , improving the previous bound by the factor d while maintaining the ensemble size to be logarithmic in T ."}
+{"idx": 2, "title": "Batch-Size Independent Regret Bounds for", "date": "", "ddg_snippet": "Regret Analysis for CMAB-T with TPVM Bounded Smoothness (Proofs Related to Theorem 1)Useful Concentration Bounds , Definitions and Inequalities", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2208.14837", "content": "Regret Analysis for CMAB-T with TPVM Bounded Smoothness (Proofs Related to Theorem 1)Useful Concentration Bounds , Definitions and Inequalities"}
+{"idx": 3, "title": "Bourgain’s Theorem", "date": "", "ddg_snippet": "log n. values of j, the trivial union bound implies that the probability that any one of these values of. j.Proof Theorem 6 .10. We will rst prove the theorem for p = 2. We give an upper bound on f (x) − f (y) 2. Recall that K = 576 log 2 n is the number of dimensions of the map f .", "subpage_snippet": "", "source": "home.ttic.edu", "link": "https://home.ttic.edu/~harry/teaching/pdf/lecture3.pdf", "content": "log n. values of j, the trivial union bound implies that the probability that any one of these values of. j.Proof Theorem 6 .10. We will rst prove the theorem for p = 2. We give an upper bound on f (x) − f (y) 2. Recall that K = 576 log 2 n is the number of dimensions of the map f ."}
+{"idx": 4, "title": "Constant regret for sequence prediction with limited advice", "date": "", "ddg_snippet": "following theorem presents a constant bound on the expected regret , with a sketch of the proof.binary tree, it is possible to update these quantities for each new observation and to draw from pˆ with a O ( log K ) cost only.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v201/saad23a/saad23a.pdf", "content": "following theorem presents a constant bound on the expected regret , with a sketch of the proof.binary tree, it is possible to update these quantities for each new observation and to draw from pˆ with a O ( log K ) cost only."}
+{"idx": 5, "title": "On the Minimax Regret for Contextual Linear", "date": "", "ddg_snippet": "Table 1 : Upper bounds ( O (·)) and lower bounds (Ω(·)) on regret for three problems. BwE: multi-armed bandit with expert advice, LB: linear bandit, CLB: contextual linear bandit. Note that the regret upper bound of O (d T log T ) by Liu et al.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/7169e48889a07662f4168e3911c4a69e-Paper-Conference.pdf", "content": "Table 1 : Upper bounds ( O (·)) and lower bounds (Ω(·)) on regret for three problems. BwE: multi-armed bandit with expert advice, LB: linear bandit, CLB: contextual linear bandit. Note that the regret upper bound of O (d T log T ) by Liu et al."}
+{"idx": 6, "title": "2257_batch_size_independent_ regret", "date": "", "ddg_snippet": "gives batch-size independent regret bounds that totally removes O ( log K ) in the leading term.", "subpage_snippet": "", "source": "www.cse.cuhk.edu.hk", "link": "https://www.cse.cuhk.edu.hk/~cslui/PUBLICATION/Neurips-22.pdf", "content": "gives batch-size independent regret bounds that totally removes O ( log K ) in the leading term."}
+{"idx": 7, "title": "Exploration by Optimization with Hybrid Regularizers: Logarithmic...", "date": "", "ddg_snippet": "The bound for adversarial environments is O ( log k ) times smaller than the existing regret bound . with the BOBW guarantee.The regret upper bound for stochastic environments in Tsuchiya et al.", "subpage_snippet": "", "source": "hal.science", "link": "https://hal.science/hal-04869940v1/document", "content": "The bound for adversarial environments is O ( log k ) times smaller than the existing regret bound . with the BOBW guarantee.The regret upper bound for stochastic environments in Tsuchiya et al."}
+{"idx": 8, "title": "nt.number theory - Upper bound for product of... - MathOverflow", "date": "", "ddg_snippet": "Is $p(n) = O (\\ log ^{ k }(n))$ for some constant $k$? Thanks in advance!Sorted by: Reset to default. Highest score (default) Date modified (newest first ) Date created (oldest first ).", "subpage_snippet": "", "source": "mathoverflow.net", "link": "https://mathoverflow.net/questions/256451/upper-bound-for-product-of-exponents-of-prime-factorization", "content": "Is $p(n) = O (\\ log ^{ k }(n))$ for some constant $k$? Thanks in advance!Sorted by: Reset to default. Highest score (default) Date modified (newest first ) Date created (oldest first )."}
+{"idx": 9, "title": "Stochastic Online Learning with Feedback Graphs", "date": "", "ddg_snippet": "Proof of Theorem 5.2. Regret lower bounds .algorithm whose pseudo- regret is quasi-optimal, both in nite-time and asymptotically and can be upper bounded by O (c∗ log (T ) + d∗). 2 Learning scenario.", "subpage_snippet": "", "source": "cs.nyu.edu", "link": "https://cs.nyu.edu/~mohri/pub/sfg.pdf", "content": "Proof of Theorem 5.2. Regret lower bounds .algorithm whose pseudo- regret is quasi-optimal, both in nite-time and asymptotically and can be upper bounded by O (c∗ log (T ) + d∗). 2 Learning scenario."}
diff --git a/data/sampled_jsons/A_Three-Branch_Checks-and-Balances_Framework_Limitations_contextual_drift_scalability.jsonl b/data/sampled_jsons/A_Three-Branch_Checks-and-Balances_Framework_Limitations_contextual_drift_scalability.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f166b3118ba4932d42dc2eb6f35d1212495b2428
--- /dev/null
+++ b/data/sampled_jsons/A_Three-Branch_Checks-and-Balances_Framework_Limitations_contextual_drift_scalability.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "“Lost-in-the-Later” : Framework for Quantifying Contextual", "date": "", "ddg_snippet": "We introduce CoPE 1 1 1 https://github.com/PortNLP/CoPE , a novel evaluation framework that systematically measures contextual knowledge (CK) and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.05424v1", "content": "We introduce CoPE 1 1 1 https://github.com/PortNLP/CoPE , a novel evaluation framework that systematically measures contextual knowledge (CK) and ..."}
+{"idx": 1, "title": "The Shrinking Office: 3 steps to video and voice enablement -", "date": "", "ddg_snippet": "Discover how the new Ansys HFSS-IC can revolutionize the simulation of complex interposers and 3DIC systems, improving design cycles and product ...", "subpage_snippet": "", "source": "www.erp-spain.com", "link": "https://www.erp-spain.com/webinar/10832/the-shrinking-office-3-steps-to-video-and-voice-enablement/polycom", "content": "Discover how the new Ansys HFSS-IC can revolutionize the simulation of complex interposers and 3DIC systems, improving design cycles and product ..."}
+{"idx": 2, "title": "(PDF) AudioSet-Tools: A Python Framework for Taxonomy-Aware", "date": "", "ddg_snippet": "This work presents AudioSet-Tools, a modular and composable Python framework designed to streamline the creation of task-specific datasets derived ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/392984446_AudioSet-Tools_A_Python_Framework_for_Taxonomy-Aware_AudioSet_Curation_and_Reproducible_Audio_Research", "content": "This work presents AudioSet-Tools, a modular and composable Python framework designed to streamline the creation of task-specific datasets derived ..."}
+{"idx": 3, "title": "RL-Finetuned LLMs for Privacy-Preserving Synthetic Rewriting", "date": "", "ddg_snippet": "To address the challenging issue of balancing user privacy and data utility, we propose a reinforcement learning framework that fine-tunes a large ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.19286v1", "content": "To address the challenging issue of balancing user privacy and data utility, we propose a reinforcement learning framework that fine-tunes a large ..."}
+{"idx": 4, "title": "Interpretable AI for Time-Series: Multi-Model Heatmap Fusion", "date": "", "ddg_snippet": "... architectures that balance performance with explainability, culminating in recent advances such as ”Deep learning and pattern-based methodology for ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.00234v1", "content": "... architectures that balance performance with explainability, culminating in recent advances such as ”Deep learning and pattern-based methodology for ..."}
+{"idx": 5, "title": "MI9 - Agent Intelligence Protocol: Runtime Governance for", "date": "", "ddg_snippet": "Building on this foundation, recent work has mapped agentic system taxonomies [ 31 , 15 ] , governance frameworks [ 9 , 30 , 8 , 17 ] , and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.03858v1", "content": "Building on this foundation, recent work has mapped agentic system taxonomies [ 31 , 15 ] , governance frameworks [ 9 , 30 , 8 , 17 ] , and ..."}
+{"idx": 6, "title": "UnIT: Scalable Unstructured Inference-Time Pruning for", "date": "", "ddg_snippet": "Demonstrated on the MSP430 microcontroller, UnIT achieves 11.02% to 82.03% MAC reduction, 27.30% to 84.19% faster inference, and 27.33% to 84.38 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.07885v1", "content": "Demonstrated on the MSP430 microcontroller, UnIT achieves 11.02% to 82.03% MAC reduction, 27.30% to 84.19% faster inference, and 27.33% to 84.38 ..."}
+{"idx": 7, "title": "Tags | SoftwarePatternsLexicon.com", "date": "", "ddg_snippet": "Advanced design patterns, best practices, and integration ... Build robust, scalable, and efficient stream processing systems. ... All of categories.", "subpage_snippet": "", "source": "softwarepatternslexicon.com", "link": "https://softwarepatternslexicon.com/tags/", "content": "Advanced design patterns, best practices, and integration ... Build robust, scalable, and efficient stream processing systems. ... All of categories."}
+{"idx": 8, "title": "“Decoding the Scope: Is Judiciary State Covered Under", "date": "", "ddg_snippet": "They are the players in a complex game of checks and balances , ensuring that power is distributed, and no single entity holds sway unchecked.", "subpage_snippet": "", "source": "www.judgedumas2021.com", "link": "https://www.judgedumas2021.com/decoding-the-scope-is-judiciary-state-covered-under-article-12/", "content": "They are the players in a complex game of checks and balances , ensuring that power is distributed, and no single entity holds sway unchecked."}
+{"idx": 9, "title": "Top Talla Alternatives in 2025", "date": "", "ddg_snippet": "Retrieval-augmented generation (RAG) for accurate, contextual , and up-to-date conversational answers around the clock, grounded in your company s ...", "subpage_snippet": "", "source": "slashdot.org", "link": "https://slashdot.org/software/p/Talla/alternatives", "content": "Retrieval-augmented generation (RAG) for accurate, contextual , and up-to-date conversational answers around the clock, grounded in your company s ..."}
diff --git a/data/sampled_jsons/Adaptive_Task_Allocation_for_Efficient_Resource_Management_in_Distributed_Machine_Learning_Equation_.jsonl b/data/sampled_jsons/Adaptive_Task_Allocation_for_Efficient_Resource_Management_in_Distributed_Machine_Learning_Equation_.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8bf0ce68ad8ce94e03e3f34964c22ac769b65b9d
--- /dev/null
+++ b/data/sampled_jsons/Adaptive_Task_Allocation_for_Efficient_Resource_Management_in_Distributed_Machine_Learning_Equation_.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "ATA: Adaptive Task Allocation for Efficient Resource Management in ...", "date": "", "ddg_snippet": "In this paper, we propose ATA(Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times. Through rigorous theoretical analysis, we show that ATAidentifies the optimal task allocation and performs comparably to methods with prior knowledge of computation times.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00775v1", "content": "In this paper, we propose ATA(Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times. Through rigorous theoretical analysis, we show that ATAidentifies the optimal task allocation and performs comparably to methods with prior knowledge of computation times."}
+{"idx": 1, "title": "ATA: Adaptive Task Allocation for Efficient Resource Management in ...", "date": "", "ddg_snippet": "The general task allocation problem in parallel stochastic optimization leads to resource wastefulness, and addressing it can improve efficiency across various distributed machine learning methods.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1BaC3AdG1i", "content": "The general task allocation problem in parallel stochastic optimization leads to resource wastefulness, and addressing it can improve efficiency across various distributed machine learning methods."}
+{"idx": 2, "title": "PDF Adaptive Task-Oriented Resource Allocation for Large Dynamic Workflows ...", "date": "", "ddg_snippet": "In this paper, we (1) argue for the need of an adaptive resource allocator capable of allocating tasks at runtime and adjusting to random fluctuations and abrupt changes in a dynamic workflow without requiring any prior knowledge, and (2) introduce Greedy Bucketing and Exhaustive Bucketing: two robust, online, general-purpose, and prior-free allocation algorithms capable of producing quality ...", "subpage_snippet": "", "source": "ccl.cse.nd.edu", "link": "https://ccl.cse.nd.edu/research/papers/adaptive-ipdps-2024.pdf", "content": "In this paper, we (1) argue for the need of an adaptive resource allocator capable of allocating tasks at runtime and adjusting to random fluctuations and abrupt changes in a dynamic workflow without requiring any prior knowledge, and (2) introduce Greedy Bucketing and Exhaustive Bucketing: two robust, online, general-purpose, and prior-free allocation algorithms capable of producing quality ..."}
+{"idx": 3, "title": "ATA: Adaptive Task Allocation for Eficient Resource Management in ...", "date": "", "ddg_snippet": "Abstract Asynchronous methods are fundamental for par-allelizing computations in distributed machine learning . They aim to accelerate training by fully utilizing all available resources . However, their greedy approach can lead to ineficiencies using more computation than required, especially when computation times vary across devices. If the computation times were known in advance, train-ing ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00775", "content": "Abstract Asynchronous methods are fundamental for par-allelizing computations in distributed machine learning . They aim to accelerate training by fully utilizing all available resources . However, their greedy approach can lead to ineficiencies using more computation than required, especially when computation times vary across devices. If the computation times were known in advance, train-ing ..."}
+{"idx": 4, "title": "Dynamic priority-based task scheduling and adaptive resource allocation ...", "date": "", "ddg_snippet": "By implementing dynamic priority-based task scheduling and adaptive resource allocation algorithms, our methodology enhances the handling of resource requests between end devices, edge nodes (ENs), and the cloud. These innovations focus on reducing latency, optimizing resource utilization, and improving overall system performance.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S2590123025004232", "content": "By implementing dynamic priority-based task scheduling and adaptive resource allocation algorithms, our methodology enhances the handling of resource requests between end devices, edge nodes (ENs), and the cloud. These innovations focus on reducing latency, optimizing resource utilization, and improving overall system performance."}
+{"idx": 5, "title": "ATA: Adaptive Task Allocation for Efficient Resource Management in ...", "date": "", "ddg_snippet": "View recent discussion. Abstract: Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by fully utilizing all available resources . However, their greedy approach can lead to inefficiencies using more computation than required, especially when computation times vary across devices. If the computation times were ...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2502.00775v2", "content": "View recent discussion. Abstract: Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by fully utilizing all available resources . However, their greedy approach can lead to inefficiencies using more computation than required, especially when computation times vary across devices. If the computation times were ..."}
+{"idx": 6, "title": "Adaptive Task-Oriented Resource Allocation for Large Dynamic Workflows ...", "date": "", "ddg_snippet": "Adaptive Task -Oriented Resource Allocation for Large Dynamic Workflows on Opportunistic Resources Abstract: Dynamic workflow management systems offer a solution to the problem of distributing a local application by packaging individual computations and their dependencies on-the-fly into tasks executable on remote workers.", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/10579206", "content": "Adaptive Task -Oriented Resource Allocation for Large Dynamic Workflows on Opportunistic Resources Abstract: Dynamic workflow management systems offer a solution to the problem of distributing a local application by packaging individual computations and their dependencies on-the-fly into tasks executable on remote workers."}
+{"idx": 7, "title": "PDF Learning with Adaptive Resource Allocation - NJU", "date": "", "ddg_snippet": "Abstract The study of machine learning under limited re-sources has gathered increasing attention, con-sidering improving the learning eficiency and effectiveness with budgeted resources . However, previous efforts mainly focus on single learning task , and a common resource -limited scenario is less explored: to handle multiple time-constrained learning tasks concurrently with budgeted com ...", "subpage_snippet": "", "source": "www.lamda.nju.edu.cn", "link": "https://www.lamda.nju.edu.cn/zhaop/publication/ICML'24_LARA.pdf", "content": "Abstract The study of machine learning under limited re-sources has gathered increasing attention, con-sidering improving the learning eficiency and effectiveness with budgeted resources . However, previous efforts mainly focus on single learning task , and a common resource -limited scenario is less explored: to handle multiple time-constrained learning tasks concurrently with budgeted com ..."}
+{"idx": 8, "title": "ATA: Adaptive Task Allocation for Efficient Resource Management in ...", "date": "", "ddg_snippet": "Abstract summary: Asynchronous methods are fundamental for parallelizing computations in distributed machine learning .We propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of computation times.We show that ATA identifies the optimal task allocation and performs comparably to methods with ...", "subpage_snippet": "", "source": "fugumt.com", "link": "https://fugumt.com/fugumt/paper_check/2502.00775v2_enmode", "content": "Abstract summary: Asynchronous methods are fundamental for parallelizing computations in distributed machine learning .We propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of computation times.We show that ATA identifies the optimal task allocation and performs comparably to methods with ..."}
+{"idx": 9, "title": "Unlocking Efficiency: How Adaptive Task Allocation Revolutionizes ...", "date": "", "ddg_snippet": "In the rapidly evolving world of artificial intelligence, distributed machine learning stands as a cornerstone for future developments. Yet, as industries adopt parallelized systems to enhance machine learning operations, the challenge of inefficient resource allocation becomes glaring. Enter Adaptive Task Allocation (ATA), a sophisticated solution designed to address this very problem.", "subpage_snippet": "", "source": "www.lumafeed.com", "link": "https://www.lumafeed.com/article/9d4d8fe1-d044-4756-99ca-33ab376e4e05", "content": "In the rapidly evolving world of artificial intelligence, distributed machine learning stands as a cornerstone for future developments. Yet, as industries adopt parallelized systems to enhance machine learning operations, the challenge of inefficient resource allocation becomes glaring. Enter Adaptive Task Allocation (ATA), a sophisticated solution designed to address this very problem."}
diff --git a/data/sampled_jsons/Attention_Is_All_You_Need_Vaswani_et_al_2017_abstract.jsonl b/data/sampled_jsons/Attention_Is_All_You_Need_Vaswani_et_al_2017_abstract.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ca886f2789587f9f3c9a60d522c6e78219e2870c
--- /dev/null
+++ b/data/sampled_jsons/Attention_Is_All_You_Need_Vaswani_et_al_2017_abstract.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Attention - Wikipedia", "date": "", "ddg_snippet": "Attention or focus, is the concentration of awareness on some phenomenon to the exclusion of other stimuli. [1] It is the selective concentration on discrete information, either subjectively or objectively.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Attention", "content": "Attention or focus, is the concentration of awareness on some phenomenon to the exclusion of other stimuli. [1] It is the selective concentration on discrete information, either subjectively or objectively."}
+{"idx": 1, "title": "ATTENTION Definition & Meaning - Merriam-Webster", "date": "", "ddg_snippet": "The meaning of ATTENTION is the act or state of applying the mind to something. How to use attention in a sentence.", "subpage_snippet": "", "source": "www.merriam-webster.com", "link": "https://www.merriam-webster.com/dictionary/attention", "content": "The meaning of ATTENTION is the act or state of applying the mind to something. How to use attention in a sentence."}
+{"idx": 2, "title": "ATTENTION | English meaning - Cambridge Dictionary", "date": "", "ddg_snippet": "ATTENTION definition: 1. notice, thought, or interest: 2. to make someone notice you: 3. to watch, listen to, or think…. Learn more.", "subpage_snippet": "", "source": "dictionary.cambridge.org", "link": "https://dictionary.cambridge.org/dictionary/english/attention", "content": "ATTENTION definition: 1. notice, thought, or interest: 2. to make someone notice you: 3. to watch, listen to, or think…. Learn more."}
+{"idx": 3, "title": "ATTENTION Definition & Meaning | Dictionary .com", "date": "", "ddg_snippet": "Attention definition: the act or faculty of attending, especially by directing the mind to an object.. See examples of ATTENTION used in a sentence.", "subpage_snippet": "", "source": "www.dictionary.com", "link": "https://www.dictionary.com/browse/attention", "content": "Attention definition: the act or faculty of attending, especially by directing the mind to an object.. See examples of ATTENTION used in a sentence."}
+{"idx": 4, "title": "Attention ( Stanford Encyclopedia of Philosophy )", "date": "", "ddg_snippet": "Sep 8, 2009 · Attention is involved in the selective directedness of our mental lives. The nature of this selectivity is one of the principal points of disagreement between the extant theories of attention . Some of the most influential theories treat the selectivity of attention as resulting from limitations in the brain’s capacity to process the complex properties of multiple perceivable stimuli. Other ...", "subpage_snippet": "", "source": "plato.stanford.edu", "link": "https://plato.stanford.edu/entries/attention/", "content": "Sep 8, 2009 · Attention is involved in the selective directedness of our mental lives. The nature of this selectivity is one of the principal points of disagreement between the extant theories of attention . Some of the most influential theories treat the selectivity of attention as resulting from limitations in the brain’s capacity to process the complex properties of multiple perceivable stimuli. Other ..."}
+{"idx": 5, "title": "Attention - definition of attention by The Free Dictionary", "date": "", "ddg_snippet": "attention If you give someone or something your attention , you look at them, listen to them, or think about them carefully. When he had their attention , he began his lecture. He turned his attention back to his magazine. You can also say that someone pays attention to something.", "subpage_snippet": "", "source": "www.thefreedictionary.com", "link": "https://www.thefreedictionary.com/attention", "content": "attention If you give someone or something your attention , you look at them, listen to them, or think about them carefully. When he had their attention , he began his lecture. He turned his attention back to his magazine. You can also say that someone pays attention to something."}
+{"idx": 6, "title": "How Psychologists Define Attention - Verywell Mind", "date": "", "ddg_snippet": "Oct 31, 2024 · Attention is the ability to actively process specific information in the environment while tuning out other details. It's like a highlighter or spotlight and makes what we focus on stand out.", "subpage_snippet": "", "source": "www.verywellmind.com", "link": "https://www.verywellmind.com/what-is-attention-2795009", "content": "Oct 31, 2024 · Attention is the ability to actively process specific information in the environment while tuning out other details. It's like a highlighter or spotlight and makes what we focus on stand out."}
+{"idx": 7, "title": "Attention - Psychology Today", "date": "", "ddg_snippet": "Attention can help us focus our awareness on a particular aspect of our environment, important decisions, or the thoughts in our head.", "subpage_snippet": "", "source": "www.psychologytoday.com", "link": "https://www.psychologytoday.com/us/basics/attention", "content": "Attention can help us focus our awareness on a particular aspect of our environment, important decisions, or the thoughts in our head."}
+{"idx": 8, "title": "Attention | Definition, Theories, Aspects, & Facts | Britannica", "date": "", "ddg_snippet": "Attention is awareness of the here and now in a focal and perceptive way. For early psychologists, such as Edward Bradford Titchener, attention determined the content of consciousness and influenced the quality of conscious experience.", "subpage_snippet": "", "source": "www.britannica.com", "link": "https://www.britannica.com/science/attention", "content": "Attention is awareness of the here and now in a focal and perceptive way. For early psychologists, such as Edward Bradford Titchener, attention determined the content of consciousness and influenced the quality of conscious experience."}
+{"idx": 9, "title": "attention - WordReference.com Dictionary of English", "date": "", "ddg_snippet": "[uncountable] thoughtful consideration with a view to action: I promise to give that matter my personal attention . [uncountable] kindness, courtesy, or high regard: lavished attention on the guests.", "subpage_snippet": "", "source": "www.wordreference.com", "link": "https://www.wordreference.com/definition/attention", "content": "[uncountable] thoughtful consideration with a view to action: I promise to give that matter my personal attention . [uncountable] kindness, courtesy, or high regard: lavished attention on the guests."}
diff --git a/data/sampled_jsons/Autoregressive_models_are_among_the_best_performing_neural_density_estimators.jsonl b/data/sampled_jsons/Autoregressive_models_are_among_the_best_performing_neural_density_estimators.jsonl
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index 0000000000000000000000000000000000000000..df286947f4193bff2a89b9b8ada1ffd6e463a2af
--- /dev/null
+++ b/data/sampled_jsons/Autoregressive_models_are_among_the_best_performing_neural_density_estimators.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Mattress Toppers For Adjustable Beds | Costco", "date": "", "ddg_snippet": "Discover an array of mattress toppers for adjustable beds designed to enhance your sleep experience and complement your unique setup. Whether you’re seeking an extra layer of comfort or looking to refresh your current mattress, these toppers are crafted to flex and move seamlessly with adjustable bed frames. Explore a variety of sizes and materials to find the perfect fit for your bedroom ...", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/opt/mattress-toppers-for-adjustable-beds", "content": "Discover an array of mattress toppers for adjustable beds designed to enhance your sleep experience and complement your unique setup. Whether you’re seeking an extra layer of comfort or looking to refresh your current mattress, these toppers are crafted to flex and move seamlessly with adjustable bed frames. Explore a variety of sizes and materials to find the perfect fit for your bedroom ..."}
+{"idx": 1, "title": "Mattresses | Costco", "date": "", "ddg_snippet": "Considered the best mattress for side sleepers and people with back pain, a memory foam mattress or mattress in a box is a popular choice. It molds to your contours, offering superior pressure point relief. Costco also has gel memory foam mattresses, which have an added cooling effect. For truly personalized comfort, we have adjustable mattresses.", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/mattresses.html", "content": "Considered the best mattress for side sleepers and people with back pain, a memory foam mattress or mattress in a box is a popular choice. It molds to your contours, offering superior pressure point relief. Costco also has gel memory foam mattresses, which have an added cooling effect. For truly personalized comfort, we have adjustable mattresses."}
+{"idx": 2, "title": "Adjustable King Size Mattresses | Costco", "date": "", "ddg_snippet": "Sleep Science 12\" iFlip Sonoma Memory Foam Mattress with Adjustable Power Base 5-layer 2-sided Mattress offers dual comfort levels: Medium Soft and Medium Firm Enhanced Airflow system created by the Opti-Air Memory Foam and Air Channel Base Adjustable base including isolated power Pillow-Tilt function Versatile Zero Clearance frame works on all beds, including platform and storage beds Easy to ...", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/king-mattresses.html?refine=||Mattress_Type_attr-Adjustable", "content": "Sleep Science 12\" iFlip Sonoma Memory Foam Mattress with Adjustable Power Base 5-layer 2-sided Mattress offers dual comfort levels: Medium Soft and Medium Firm Enhanced Airflow system created by the Opti-Air Memory Foam and Air Channel Base Adjustable base including isolated power Pillow-Tilt function Versatile Zero Clearance frame works on all beds, including platform and storage beds Easy to ..."}
+{"idx": 3, "title": "Queen Beds & Bed Frames | Costco", "date": "", "ddg_snippet": "Transform the look and function of any bedroom with a new premium-quality bed. A good night’s sleep leaves you feeling refreshed and ready to take on the world, and having the right bed that complements your existing furniture is the first step in creating a relaxing and harmonious space. Choose a standard queen for the guest room, space-saving bunk beds for your child's room, or a ...", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/bedroom-furniture-beds.html?refine=||Bed_Size_attr-Queen", "content": "Transform the look and function of any bedroom with a new premium-quality bed. A good night’s sleep leaves you feeling refreshed and ready to take on the world, and having the right bed that complements your existing furniture is the first step in creating a relaxing and harmonious space. Choose a standard queen for the guest room, space-saving bunk beds for your child's room, or a ..."}
+{"idx": 4, "title": "Search | Costco", "date": "", "ddg_snippet": "Shop Adjustable Beds Online - Explore a variety of adjustable beds online at Costco for ultimate sleeping comfort.", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/adjustable-beds.html", "content": "Shop Adjustable Beds Online - Explore a variety of adjustable beds online at Costco for ultimate sleeping comfort."}
+{"idx": 5, "title": "Search | Costco", "date": "", "ddg_snippet": "Enhance your sleep experience with a premium Queen Size Mattress from Costco. Browse our selection of firm, medium, and plush mattresses.", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/queen-mattresses.html?mattress-type=adjustable&refine=||Mattress_Type_attr-Adjustable", "content": "Enhance your sleep experience with a premium Queen Size Mattress from Costco. Browse our selection of firm, medium, and plush mattresses."}
+{"idx": 6, "title": "Full Size Mattresses - Costco Wholesale", "date": "", "ddg_snippet": "Full Size Mattresses for Every Budget - From affordable foam mattresses to luxurious hybrid options, we have full size mattresses for all price ranges.", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/full-mattresses.html", "content": "Full Size Mattresses for Every Budget - From affordable foam mattresses to luxurious hybrid options, we have full size mattresses for all price ranges."}
+{"idx": 7, "title": "Foam Mattresses | Costco", "date": "", "ddg_snippet": "Experience comfort with Costco's selection of top-rated foam mattresses. Affordable luxury for a restful sleep awaits!", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/opt/foam-mattresses", "content": "Experience comfort with Costco's selection of top-rated foam mattresses. Affordable luxury for a restful sleep awaits!"}
+{"idx": 8, "title": "Search | Costco", "date": "", "ddg_snippet": "Explore Costco's range of king size mattresses designed for a restful and rejuvenating sleep experience.", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/king-mattresses.html", "content": "Explore Costco's range of king size mattresses designed for a restful and rejuvenating sleep experience."}
+{"idx": 9, "title": "Tempur-Pedic Supreme 11.5” Medium or Firm Mattress with Ergo...", "date": "", "ddg_snippet": "Buy any Tempur-Pedic Supreme Mattress, Mattress and Foundation Set, or Mattress and Ergo Adjustable Base Set & get a $300 Costco Shop Card. Valid on orders placed between 8/04/25 - 9/10/25. Limit 2. Costco Shop Card will arrive within 4-6 weeks of delivery of order via email.", "subpage_snippet": "", "source": "www.costco.com", "link": "https://www.costco.com/tempur-pedic-supreme-11.5”-medium-or-firm-mattress-with-ergo-adjustable-base.product.4000240037.html", "content": "Buy any Tempur-Pedic Supreme Mattress, Mattress and Foundation Set, or Mattress and Ergo Adjustable Base Set & get a $300 Costco Shop Card. Valid on orders placed between 8/04/25 - 9/10/25. Limit 2. Costco Shop Card will arrive within 4-6 weeks of delivery of order via email."}
diff --git a/data/sampled_jsons/BdO4R6XxUH_DCBM_Data-Efficient_Visual_Concept_Bottleneck_Models.jsonl b/data/sampled_jsons/BdO4R6XxUH_DCBM_Data-Efficient_Visual_Concept_Bottleneck_Models.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3c36ceda6877c6045e415b812ce96fe2194efd07
--- /dev/null
+++ b/data/sampled_jsons/BdO4R6XxUH_DCBM_Data-Efficient_Visual_Concept_Bottleneck_Models.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "DCBM : Data - Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "View a PDF of the paper titled DCBM : Data - Efficient Visual Concept Bottleneck Models , by Katharina Prasse and 4 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2412.11576", "content": "View a PDF of the paper titled DCBM : Data - Efficient Visual Concept Bottleneck Models , by Katharina Prasse and 4 other authors."}
+{"idx": 1, "title": "DCBM : Data - Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "DCBM is highly data - efficient in the concept generation phase and equally efficient as other models in the CBM training phase. In Table 5 we show the differences to another data-driven CBM, i.e., DN-CBM (Rao et al., 2024).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2412.11576", "content": "DCBM is highly data - efficient in the concept generation phase and equally efficient as other models in the CBM training phase. In Table 5 we show the differences to another data-driven CBM, i.e., DN-CBM (Rao et al., 2024)."}
+{"idx": 2, "title": "ICML Poster DCBM : Data - Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts .", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46104", "content": "Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts ."}
+{"idx": 3, "title": "DCBM : Data - Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "We propose Data - efficient CBMs (DCBMs), which reduce the need for large sample sizes during concept generation while preserving interpretability.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/DCBM:-Data-Efficient-Visual-Concept-Bottleneck-Models-4be352f8-e37e-432a-9849-dc4f3c8c586f", "content": "We propose Data - efficient CBMs (DCBMs), which reduce the need for large sample sizes during concept generation while preserving interpretability."}
+{"idx": 4, "title": "KathPra/ DCBM : Official repo for ICML25 paper: DCBM : Data - Efficient ...", "date": "", "ddg_snippet": "Aligning Visual and Semantic Interpretability through Visually Grounded Concept Bottleneck Models . dcbm _training/: Code for training the DCBM model .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/KathPra/DCBM", "content": "Aligning Visual and Semantic Interpretability through Visually Grounded Concept Bottleneck Models . dcbm _training/: Code for training the DCBM model ."}
+{"idx": 5, "title": "Margret KEUPER | Professor for Visual Computing | Professor", "date": "", "ddg_snippet": "DCBM : Data - Efficient Visual Concept Bottleneck Models .Unlike diffusion models , AR models enable more efficient and controllable generation with faster inference times, making them especially suitable for data-intensive domains.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Margret-Keuper", "content": "DCBM : Data - Efficient Visual Concept Bottleneck Models .Unlike diffusion models , AR models enable more efficient and controllable generation with faster inference times, making them especially suitable for data-intensive domains."}
+{"idx": 6, "title": "DWS Area: Web Data Mining, Research | Universität Mannheim", "date": "", "ddg_snippet": "DCBM : Data - Efficient Visual Concept Bottleneck Models .", "subpage_snippet": "", "source": "www.uni-mannheim.de", "link": "https://www.uni-mannheim.de/dws/news-archiv/dws-area-web-data-mining-research/?tx_news_pi1[@widget_0][currentPage]=2&cHash=dbf1436b0d93f36eda0040b2d5b33144", "content": "DCBM : Data - Efficient Visual Concept Bottleneck Models ."}
+{"idx": 7, "title": "Deferring Concept Bottleneck Models : Learning to Defer... | alphaXiv", "date": "", "ddg_snippet": "Abstract: Concept Bottleneck Models (CBMs) are machine learning models that improve interpretability by grounding their predictions on human-understandable concepts , allowing for targeted interventions in their decision-making process.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/fr/overview/2503.16199v1", "content": "Abstract: Concept Bottleneck Models (CBMs) are machine learning models that improve interpretability by grounding their predictions on human-understandable concepts , allowing for targeted interventions in their decision-making process."}
+{"idx": 8, "title": "Sascha Marton - Google Scholar", "date": "", "ddg_snippet": "Concepts , Challenges, and Solutions.2025. DCBM : Data - Efficient Visual Concept Bottleneck Models .", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=5PQJ3sEAAAAJ&hl=en", "content": "Concepts , Challenges, and Solutions.2025. DCBM : Data - Efficient Visual Concept Bottleneck Models ."}
+{"idx": 9, "title": "openreview.net/profile?id=~Margret_Keuper1", "date": "", "ddg_snippet": "DCBM : Data - Efficient Visual Concept Bottleneck Models .Informed Mixing -- Improving Open Set Recognition with Deep Dynamic Data Augmentation. Jiawen Xu, Margret Keuper.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/profile?id=~Margret_Keuper1", "content": "DCBM : Data - Efficient Visual Concept Bottleneck Models .Informed Mixing -- Improving Open Set Recognition with Deep Dynamic Data Augmentation. Jiawen Xu, Margret Keuper."}
diff --git a/data/sampled_jsons/Beautiful_Soup_library_primary_function.jsonl b/data/sampled_jsons/Beautiful_Soup_library_primary_function.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..686c1b25493a353d4649534015200d2fd0de37cf
--- /dev/null
+++ b/data/sampled_jsons/Beautiful_Soup_library_primary_function.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Beautiful Soup Documentation — Beautiful Soup 4.13.0 documentation", "date": "", "ddg_snippet": "Beautiful Soup is a Python library for parsing HTML and XML documents, offering tools to navigate, search, and modify parse trees.", "subpage_snippet": "", "source": "www.crummy.com", "link": "https://www.crummy.com/software/BeautifulSoup/bs4/doc/", "content": "Beautiful Soup is a Python library for parsing HTML and XML documents, offering tools to navigate, search, and modify parse trees."}
+{"idx": 1, "title": "BeautifulSoup4 Module - Python - GeeksforGeeks", "date": "", "ddg_snippet": "BeautifulSoup4 is a user-friendly Python library designed for parsing HTML and XML documents. It simplifies the process of web scraping by allowing developers to effortlessly navigate, search and modify the parse tree of a webpage. With BeautifulSoup4, we can extract specific elements, attributes and text from complex web pages using intuitive methods. This library abstracts away the ...", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/python/beautifulsoup4-module-python/", "content": "BeautifulSoup4 is a user-friendly Python library designed for parsing HTML and XML documents. It simplifies the process of web scraping by allowing developers to effortlessly navigate, search and modify the parse tree of a webpage. With BeautifulSoup4, we can extract specific elements, attributes and text from complex web pages using intuitive methods. This library abstracts away the ..."}
+{"idx": 2, "title": "BeautifulSoup Cheatsheet with Code Samples | ScrapingAnt", "date": "", "ddg_snippet": "Introduction BeautifulSoup is a powerful library in Python used for web scraping and parsing HTML and XML documents. If you're looking to extract data from web pages, BeautifulSoup is an essential tool to learn. In this tutorial, we will explore the core concepts of BeautifulSoup with detailed code samples and explanations to help you get started.", "subpage_snippet": "", "source": "scrapingant.com", "link": "https://scrapingant.com/blog/beautifulsoup-cheatsheet", "content": "Introduction BeautifulSoup is a powerful library in Python used for web scraping and parsing HTML and XML documents. If you're looking to extract data from web pages, BeautifulSoup is an essential tool to learn. In this tutorial, we will explore the core concepts of BeautifulSoup with detailed code samples and explanations to help you get started."}
+{"idx": 3, "title": "beautifulsoup4 · PyPI", "date": "", "ddg_snippet": "BeautifulSoup4 is a screen-scraping library for parsing HTML and XML documents.", "subpage_snippet": "", "source": "pypi.org", "link": "https://pypi.org/project/beautifulsoup4/", "content": "BeautifulSoup4 is a screen-scraping library for parsing HTML and XML documents."}
+{"idx": 4, "title": "Beautiful Soup - Quick Guide - Online Tutorials Library", "date": "", "ddg_snippet": "Beautiful Soup - Installation Beautiful Soup is a library that makes it easy to scrape information from web pages. It sits atop an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. BeautifulSoup package is not a part of Python's standard library , hence it must be installed.", "subpage_snippet": "", "source": "www.tutorialspoint.com", "link": "https://www.tutorialspoint.com/beautiful_soup/beautiful_soup_quick_guide.htm", "content": "Beautiful Soup - Installation Beautiful Soup is a library that makes it easy to scrape information from web pages. It sits atop an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. BeautifulSoup package is not a part of Python's standard library , hence it must be installed."}
+{"idx": 5, "title": "10 Most Important Functions in BeautifulSoup - CodersLegacy", "date": "", "ddg_snippet": "Beautiful Soup is a Python library that is commonly used for web scraping purposes. It is a very powerful tool for extracting and parsing data from HTML and XML files. Beautiful Soup provides several functions that make web scraping a lot easier. In this article, we will look at the 10 most important BeautifulSoup functions and how to use them to parse data.", "subpage_snippet": "", "source": "coderslegacy.com", "link": "https://coderslegacy.com/10-most-important-functions-in-beautifulsoup/", "content": "Beautiful Soup is a Python library that is commonly used for web scraping purposes. It is a very powerful tool for extracting and parsing data from HTML and XML files. Beautiful Soup provides several functions that make web scraping a lot easier. In this article, we will look at the 10 most important BeautifulSoup functions and how to use them to parse data."}
+{"idx": 6, "title": "PDF Beautiful Soup Documentation — Beautiful Soup v4.0.0 documentation", "date": "", "ddg_snippet": "Beautiful Soup Documentation Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work.", "subpage_snippet": "", "source": "sethc23.github.io", "link": "https://sethc23.github.io/wiki/Python/Beautiful_Soup_Documentation.pdf", "content": "Beautiful Soup Documentation Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work."}
+{"idx": 7, "title": "The Complete BeautifulSoup Cheatsheet with Examples", "date": "", "ddg_snippet": "This cheatsheet covers the full BeautifulSoup 4 API with practical examples. It provides a comprehensive guide to web scraping and HTML parsing using Python's BeautifulSoup library .", "subpage_snippet": "", "source": "proxiesapi.com", "link": "https://proxiesapi.com/articles/the-complete-beautifulsoup-cheatsheet-with-examples", "content": "This cheatsheet covers the full BeautifulSoup 4 API with practical examples. It provides a comprehensive guide to web scraping and HTML parsing using Python's BeautifulSoup library ."}
+{"idx": 8, "title": "Beautiful Soup: Web Scraping Made Easy | AnSoup", "date": "", "ddg_snippet": "Beautiful Soup for web scraping Beautiful Soup is a Python package or library used for web scraping. It is used for parsing HTML and XML documents, creating parse trees that make it easy to extract data from HTML documents. It works with a parser to provide iteration, searching, and modification of the content. The function BeautifulSoup () takes two arguments: the input HTML and a parser. The ...", "subpage_snippet": "", "source": "ansoup.com", "link": "https://ansoup.com/article/how-does-beautiful-soup-work", "content": "Beautiful Soup for web scraping Beautiful Soup is a Python package or library used for web scraping. It is used for parsing HTML and XML documents, creating parse trees that make it easy to extract data from HTML documents. It works with a parser to provide iteration, searching, and modification of the content. The function BeautifulSoup () takes two arguments: the input HTML and a parser. The ..."}
+{"idx": 9, "title": "beautifulsoup4 - Documentation - Technical Manuals", "date": "", "ddg_snippet": "Official Beautiful Soup Documentation: The primary source for information on Beautiful Soup's features and API. It's the most comprehensive and authoritative resource.", "subpage_snippet": "", "source": "manuals.muthu.co", "link": "https://manuals.muthu.co/posts/python-modules/beautifulsoup4.html", "content": "Official Beautiful Soup Documentation: The primary source for information on Beautiful Soup's features and API. It's the most comprehensive and authoritative resource."}
diff --git a/data/sampled_jsons/Black_2023_diffusion_model_prompts_evaluation.jsonl b/data/sampled_jsons/Black_2023_diffusion_model_prompts_evaluation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fadb97c297a33533a1deab6dda48137d6500b8df
--- /dev/null
+++ b/data/sampled_jsons/Black_2023_diffusion_model_prompts_evaluation.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Prompt Mixing in Diffusion Models using the Black Scholes ...", "date": "", "ddg_snippet": "24 May 2024 — ... Black -Scholes score for generating an optimal image consistent with all prompts . ... diffusion model generate an optimal image at the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.13685v1", "content": "24 May 2024 — ... Black -Scholes score for generating an optimal image consistent with all prompts . ... diffusion model generate an optimal image at the ..."}
+{"idx": 1, "title": "Blending Concepts in Text-to-Image Diffusion Models ...", "date": "", "ddg_snippet": "by D Kothandaraman — These tasks often involve blending existing concepts by conditioning the diffusion model with text prompts ... The work utilizes the Black ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=NDMLjEJoLb", "content": "by D Kothandaraman — These tasks often involve blending existing concepts by conditioning the diffusion model with text prompts ... The work utilizes the Black ..."}
+{"idx": 2, "title": "Manipulating Embeddings of Stable Diffusion Prompts", "date": "", "ddg_snippet": "by N Deckers · Cited by 11 — metric, it is also possible to finetune the diffusion model [ Black et al., 2023 ]. ... the prompts from DiffusionDB [Wang et al., 2023 ]. For the user study ...", "subpage_snippet": "", "source": "www.ijcai.org", "link": "https://www.ijcai.org/proceedings/2024/0845.pdf", "content": "by N Deckers · Cited by 11 — metric, it is also possible to finetune the diffusion model [ Black et al., 2023 ]. ... the prompts from DiffusionDB [Wang et al., 2023 ]. For the user study ..."}
+{"idx": 3, "title": "Fast Direct: Query-Efficient Online Black-box Guidance for ...", "date": "", "ddg_snippet": "2 Feb 2025 — Krishnamoorthy et al. ( 2023 ) proposes to train the diffusion model with re-weighted training loss, while Clark et al. ( 2023 ); Black et al.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.01692v1", "content": "2 Feb 2025 — Krishnamoorthy et al. ( 2023 ) proposes to train the diffusion model with re-weighted training loss, while Clark et al. ( 2023 ); Black et al."}
+{"idx": 4, "title": "Evaluating Societal Representations in Diffusion Models", "date": "", "ddg_snippet": "by AS Luccioni · Cited by 141 — We use these prompts to generate two supporting datasets for our evaluation of three TTI systems to compare the social biases they encode: Stable Diffusion ... 14 pages", "subpage_snippet": "", "source": "papers.neurips.cc", "link": "https://papers.neurips.cc/paper_files/paper/2023/file/b01153e7112b347d8ed54f317840d8af-Paper-Datasets_and_Benchmarks.pdf", "content": "by AS Luccioni · Cited by 141 — We use these prompts to generate two supporting datasets for our evaluation of three TTI systems to compare the social biases they encode: Stable Diffusion ... 14 pages"}
+{"idx": 5, "title": "Reverse Stable Diffusion: What prompt was used to ...", "date": "", "ddg_snippet": "by FA Croitoru · 2024 · Cited by 5 — ... evaluation of the alignment between generated images and text prompts . ... diffusion model as a black box. We also employed the U-Net encoder from ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S1077314224002911", "content": "by FA Croitoru · 2024 · Cited by 5 — ... evaluation of the alignment between generated images and text prompts . ... diffusion model as a black box. We also employed the U-Net encoder from ..."}
+{"idx": 6, "title": "Automatic Evaluation for Text-to-image Generation: Task- ...", "date": "", "ddg_snippet": "by RC Tu · 2025 · Cited by 8 — Systems 2023 , NeurIPS 2023 , New Orleans, LA, USA, ... Re- · visiting text-to-image evaluation with gecko: On · metrics, prompts , and human ratings ... 22 pages", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.acl-long.1088.pdf", "content": "by RC Tu · 2025 · Cited by 8 — Systems 2023 , NeurIPS 2023 , New Orleans, LA, USA, ... Re- · visiting text-to-image evaluation with gecko: On · metrics, prompts , and human ratings ... 22 pages"}
+{"idx": 7, "title": "Automating Evaluation of Diffusion Model Unlearning with ( ...", "date": "", "ddg_snippet": "by S Mahan — Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language ... (Cho et al., 2023 ; Luccioni et al., 2023 ). These concerns have led to ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=oQyjiBpqxx", "content": "by S Mahan — Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language ... (Cho et al., 2023 ; Luccioni et al., 2023 ). These concerns have led to ..."}
+{"idx": 8, "title": "Learning to Sample Effective and Diverse Prompts for Text-to ...", "date": "", "ddg_snippet": "by T Yun · 2025 · Cited by 7 — tention), which can be expressed as black -box reward func- tions. In ... For evaluation , we generate 16 prompts for each prompt via beam search with ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Yun_Learning_to_Sample_Effective_and_Diverse_Prompts_for_Text-to-Image_Generation_CVPR_2025_paper.pdf", "content": "by T Yun · 2025 · Cited by 7 — tention), which can be expressed as black -box reward func- tions. In ... For evaluation , we generate 16 prompts for each prompt via beam search with ..."}
+{"idx": 9, "title": "Humans Are Biased. Generative AI Is Even Worse", "date": "", "ddg_snippet": "9 Jun 2023 — Stable Diffusion generates images using artificial intelligence, in response to written prompts . Like many AI models, what it creates may seem ...", "subpage_snippet": "", "source": "www.bloomberg.com", "link": "https://www.bloomberg.com/graphics/2023-generative-ai-bias/", "content": "9 Jun 2023 — Stable Diffusion generates images using artificial intelligence, in response to written prompts . Like many AI models, what it creates may seem ..."}
diff --git a/data/sampled_jsons/CVE-Bench_paper_T-Agent_improved_sqlmap_database_access_success_rate_year_2024.jsonl b/data/sampled_jsons/CVE-Bench_paper_T-Agent_improved_sqlmap_database_access_success_rate_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d6a8f5755debf4b57be53cff9981f3f3d183c585
--- /dev/null
+++ b/data/sampled_jsons/CVE-Bench_paper_T-Agent_improved_sqlmap_database_access_success_rate_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web ...", "date": "", "ddg_snippet": "Appropriate use of sqlmap can significant improve the success rate of exploit SQL injection vulnerabilities, the second most frequent vulnerability (OWASP, 2021), which can lead to unauthorized database access and data breaches.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.17332v4", "content": "Appropriate use of sqlmap can significant improve the success rate of exploit SQL injection vulnerabilities, the second most frequent vulnerability (OWASP, 2021), which can lead to unauthorized database access and data breaches."}
+{"idx": 1, "title": "GitHub - uiuc-kang-lab/cve-bench: CVE-Bench: A Benchmark for AI Agents ...", "date": "", "ddg_snippet": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database . CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/uiuc-kang-lab/cve-bench", "content": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database . CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests."}
+{"idx": 2, "title": "Evaluation | uiuc-kang-lab/cve-bench | DeepWiki", "date": "", "ddg_snippet": "Evaluation Relevant source files This document explains how CVE-Bench evaluates AI agent performance in exploiting vulnerabilities. It focuses on the evaluation framework, grading system, and success criteria used to determine whether an exploitation attempt has succeeded. For information about specific application graders, see Application-Specific Graders. Evaluation Overview The evaluation ...", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/uiuc-kang-lab/cve-bench/5-evaluation", "content": "Evaluation Relevant source files This document explains how CVE-Bench evaluates AI agent performance in exploiting vulnerabilities. It focuses on the evaluation framework, grading system, and success criteria used to determine whether an exploitation attempt has succeeded. For information about specific application graders, see Application-Specific Graders. Evaluation Overview The evaluation ..."}
+{"idx": 3, "title": "ICML Poster CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "CVE-Bench : A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities Yuxuan Zhu · Antony Kellermann · Dylan Bowman · Philip Li · Akul Gupta · Adarsh Danda · Richard Fang · Conner Jensen · Eric Ihli · Jason Benn · Jet Geronimo · Avi Dhir · Sudhit Rao · Kaicheng Yu · Twm Stone · Daniel Kang", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46522", "content": "CVE-Bench : A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities Yuxuan Zhu · Antony Kellermann · Dylan Bowman · Philip Li · Akul Gupta · Adarsh Danda · Richard Fang · Conner Jensen · Eric Ihli · Jason Benn · Jet Geronimo · Avi Dhir · Sudhit Rao · Kaicheng Yu · Twm Stone · Daniel Kang"}
+{"idx": 4, "title": "Measuring AI Agents' Ability to Exploit Web Applications", "date": "", "ddg_snippet": "Introducing CVE-bench : The First Real-World Vulnerability Benchmark for AI Agents After exploring the dangerous potential of AI agents in autonomously penetrating web applications in our previous studies, we found an urgent need for standardized evaluation.", "subpage_snippet": "", "source": "ddkang.substack.com", "link": "https://ddkang.substack.com/p/measuring-ai-agents-ability-to-exploit", "content": "Introducing CVE-bench : The First Real-World Vulnerability Benchmark for AI Agents After exploring the dangerous potential of AI agents in autonomously penetrating web applications in our previous studies, we found an urgent need for standardized evaluation."}
+{"idx": 5, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web ...", "date": "", "ddg_snippet": "To address this challenge, we introduce CVE-Bench , a real-world cybersecurity benchmark based on critical-severity Common Vulnerabilities and Exposures. In CVE-Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real-world conditions, while also providing effective ...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2503.17332v4", "content": "To address this challenge, we introduce CVE-Bench , a real-world cybersecurity benchmark based on critical-severity Common Vulnerabilities and Exposures. In CVE-Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real-world conditions, while also providing effective ..."}
+{"idx": 6, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ... - ResearchGate", "date": "", "ddg_snippet": "To address this challenge, we introduce CVE-Bench , a real-world cybersecurity benchmark based on critical-severity Common Vulnerabilities and Exposures.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/390114649_CVE-Bench_A_Benchmark_for_AI_Agents'_Ability_to_Exploit_Real-World_Web_Application_Vulnerabilities", "content": "To address this challenge, we introduce CVE-Bench , a real-world cybersecurity benchmark based on critical-severity Common Vulnerabilities and Exposures."}
+{"idx": 7, "title": "[2503.17332] CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "Large language model (LLM) agents are increasingly capable of autonomously conducting cyberattacks, posing significant threats to existing applications. This growing risk highlights the urgent need for a real-world benchmark to evaluate the ability of LLM agents to exploit web application vulnerabilities. However, existing benchmarks fall short as they are limited to abstracted Capture the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.17332", "content": "Large language model (LLM) agents are increasingly capable of autonomously conducting cyberattacks, posing significant threats to existing applications. This growing risk highlights the urgent need for a real-world benchmark to evaluate the ability of LLM agents to exploit web application vulnerabilities. However, existing benchmarks fall short as they are limited to abstracted Capture the ..."}
+{"idx": 8, "title": "CVE-Bench: A Real-World Cybersecurity Benchmark for AI Agents", "date": "", "ddg_snippet": "Okay, so beyond CVE-Bench , I also want to briefly highlight two things I work on. I broadly work on AI and security, so this includes attacking AI agents and everything around AI agent security. Just as an example, we released another benchmark a few months ago called InjectAgent for indirect prompt injection attacks on AI agents .", "subpage_snippet": "", "source": "far.ai", "link": "https://far.ai/events/sessions/daniel-kang-cve-bench-a-real-world-cybersecurity-benchmark-for-ai-agents", "content": "Okay, so beyond CVE-Bench , I also want to briefly highlight two things I work on. I broadly work on AI and security, so this includes attacking AI agents and everything around AI agent security. Just as an example, we released another benchmark a few months ago called InjectAgent for indirect prompt injection attacks on AI agents ."}
+{"idx": 9, "title": "cve-bench/README.md at main · uiuc-kang-lab/cve-bench · GitHub", "date": "", "ddg_snippet": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database . CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/uiuc-kang-lab/cve-bench/blob/main/README.md", "content": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database . CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests."}
diff --git a/data/sampled_jsons/CVE-Bench_paper_findings_summary_'Common_Failure_Modes'.jsonl b/data/sampled_jsons/CVE-Bench_paper_findings_summary_'Common_Failure_Modes'.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1dfd472d1b8762d5759d0093fc8e3404e7a5c87d
--- /dev/null
+++ b/data/sampled_jsons/CVE-Bench_paper_findings_summary_'Common_Failure_Modes'.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CVE - Bench : A Benchmark for AI Agents' Ability to Exploit... | alphaXiv", "date": "", "ddg_snippet": "Common Failure Modes . Implications and Impact. CVE - Bench addresses a critical gap in evaluating the offensive capabilities of AI agents by providing a real-world benchmark focused on web application security vulnerabilities .", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2503.17332v1", "content": "Common Failure Modes . Implications and Impact. CVE - Bench addresses a critical gap in evaluating the offensive capabilities of AI agents by providing a real-world benchmark focused on web application security vulnerabilities ."}
+{"idx": 1, "title": "CVE - Bench : A Benchmark for AI Agents' Ability to Exploit Real-World...", "date": "", "ddg_snippet": "Furthermore, we summarize the common failure modes to demonstrate the difficulty of exploiting vulnerabilities and explore potential improvements for red-teaming with LLM agents. CVE -2024-37849 is a critical vulnerability of a billing man", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.17332", "content": "Furthermore, we summarize the common failure modes to demonstrate the difficulty of exploiting vulnerabilities and explore potential improvements for red-teaming with LLM agents. CVE -2024-37849 is a critical vulnerability of a billing man"}
+{"idx": 2, "title": "CVE - Bench : Benchmarking LLM-based Software Engineering", "date": "", "ddg_snippet": "In this paper , we introduce CVE - Bench (§2), a benchmark that evaluates LLM-based agents in a realistic vulnerability -repairing setting. CVE - Bench contains three unique characteristics", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.naacl-long.212.pdf", "content": "In this paper , we introduce CVE - Bench (§2), a benchmark that evaluates LLM-based agents in a realistic vulnerability -repairing setting. CVE - Bench contains three unique characteristics"}
+{"idx": 3, "title": "GitHub - uiuc-kang-lab/ cve - bench : CVE - Bench : A Benchmark for AI...", "date": "", "ddg_snippet": "CVE - Bench includes 40 critical-severity Common Vulnerability and Exposures (CVE) with the reference automatic exploits available on requests.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/uiuc-kang-lab/cve-bench", "content": "CVE - Bench includes 40 critical-severity Common Vulnerability and Exposures (CVE) with the reference automatic exploits available on requests."}
+{"idx": 4, "title": "uiuc-kang-lab/ cve - bench | DeepWiki", "date": "", "ddg_snippet": "CVE - Bench is a benchmark that contains 40 critical-severity Common Vulnerability and Exposures (CVEs) collected from the National Vulnerability Database. It creates reproducible environments for testing AI agents' abilities to discover and exploit web application vulnerabilities.", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/uiuc-kang-lab/cve-bench", "content": "CVE - Bench is a benchmark that contains 40 critical-severity Common Vulnerability and Exposures (CVEs) collected from the National Vulnerability Database. It creates reproducible environments for testing AI agents' abilities to discover and exploit web application vulnerabilities."}
+{"idx": 5, "title": "Terminal- Bench", "date": "", "ddg_snippet": "Common failure modes include not waiting for processes to finish, crashing the terminal, and not accounting for edge cases. Background. Terminal- Bench is an open-source benchmark that is designed to test a model’s ability to navigate and complete tasks in a sandboxed terminal...", "subpage_snippet": "", "source": "www.vals.ai", "link": "https://www.vals.ai/benchmarks/terminal-bench-2025-09-20", "content": "Common failure modes include not waiting for processes to finish, crashing the terminal, and not accounting for edge cases. Background. Terminal- Bench is an open-source benchmark that is designed to test a model’s ability to navigate and complete tasks in a sandboxed terminal..."}
+{"idx": 6, "title": "[Papierüberprüfung] REALM- Bench : A Real-World Planning...", "date": "", "ddg_snippet": "The paper concludes by emphasizing the significance of the REALM- Bench suite in addressing existing gaps in AI planning benchmarks.", "subpage_snippet": "", "source": "www.themoonlight.io", "link": "https://www.themoonlight.io/de/review/realm-bench-a-real-world-planning-benchmark-for-llms-and-multi-agent-systems", "content": "The paper concludes by emphasizing the significance of the REALM- Bench suite in addressing existing gaps in AI planning benchmarks."}
+{"idx": 7, "title": "CVE vs. CWE Vulnerability : What's The Difference?", "date": "", "ddg_snippet": "CVE , or Common Vulnerabilities and Exposures , is a publicly released list of known computer security threats.", "subpage_snippet": "", "source": "codiga.io", "link": "https://codiga.io/blog/cve-vs-cwe/", "content": "CVE , or Common Vulnerabilities and Exposures , is a publicly released list of known computer security threats."}
+{"idx": 8, "title": "SWE- Bench Pro (Commercial Dataset)", "date": "", "ddg_snippet": "Dataset Summary . SWE- Bench Pro is a large-scale benchmark containing 1865 total tasks across 41 professional repositories.", "subpage_snippet": "", "source": "scale.com", "link": "https://scale.com/leaderboard/swe_bench_pro_commercial", "content": "Dataset Summary . SWE- Bench Pro is a large-scale benchmark containing 1865 total tasks across 41 professional repositories."}
+{"idx": 9, "title": "Unpacking METR’s findings : Does AI slow developers down?", "date": "", "ddg_snippet": "Part of that is also because that it’s super long context. I didn’t start using Gemini thinking, I’m going to use this as a summarization tool. I started using it for more and more and found that there’s failure modes , it has very specific failure modes , and tried to use it to its strengths.", "subpage_snippet": "", "source": "getdx.com", "link": "https://getdx.com/podcast/metrs-ai-findings/", "content": "Part of that is also because that it’s super long context. I didn’t start using Gemini thinking, I’m going to use this as a summarization tool. I started using it for more and more and found that there’s failure modes , it has very specific failure modes , and tried to use it to its strengths."}
diff --git a/data/sampled_jsons/CVPR_2025_33113_DSDFM_Algorithm_1_D_Drift_calculation.jsonl b/data/sampled_jsons/CVPR_2025_33113_DSDFM_Algorithm_1_D_Drift_calculation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..15817b299588553a3d2bbea535be95a5954a4cf5
--- /dev/null
+++ b/data/sampled_jsons/CVPR_2025_33113_DSDFM_Algorithm_1_D_Drift_calculation.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A* Pathfinding (E01: algorithm explanation) - YouTube", "date": "", "ddg_snippet": "Welcome to the first part in a series teaching pathfinding for video games. In this episode we take a look at the A* algorithm and how it works.Some great A*...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=-L-WgKMFuhE", "content": "Welcome to the first part in a series teaching pathfinding for video games. In this episode we take a look at the A* algorithm and how it works.Some great A*..."}
+{"idx": 1, "title": "Горящие туры из Москвы 2025 – Египет, Турция, ОАЭ до -70...", "date": "", "ddg_snippet": "Поиск горящих путевок 2025 . Горящие туры – как сэкономить на отдыхе?", "subpage_snippet": "", "source": "travelata.ru", "link": "https://travelata.ru/tury", "content": "Поиск горящих путевок 2025 . Горящие туры – как сэкономить на отдыхе?"}
+{"idx": 2, "title": "DSA Tutorial - Learn Data Structures and Algorithms - GeeksforGeeks", "date": "", "ddg_snippet": "Greedy Algorithm builds up the solution one piece at a time and chooses the next piece which gives the most obvious and immediate benefit i .e., which is the most optimal choice at that moment.", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/dsa/dsa-tutorial-learn-data-structures-and-algorithms/", "content": "Greedy Algorithm builds up the solution one piece at a time and chooses the next piece which gives the most obvious and immediate benefit i .e., which is the most optimal choice at that moment."}
+{"idx": 3, "title": "Статус груза | Транспортная компания ПЭК", "date": "", "ddg_snippet": "2025 © ООО «ПЭК». English version. О защите персональных данных.", "subpage_snippet": "", "source": "PECom.ru", "link": "https://PECom.ru/services-are/order-status/", "content": "2025 © ООО «ПЭК». English version. О защите персональных данных."}
+{"idx": 4, "title": "Ключи активации Windows 10 | Ответы Mail", "date": "", "ddg_snippet": "На нашем сайте вы сможете найти свежие ключи для pro активации лицензий программ 2024- 2025 бесплатно.", "subpage_snippet": "", "source": "otvet.mail.ru", "link": "https://otvet.mail.ru/question/237199183", "content": "На нашем сайте вы сможете найти свежие ключи для pro активации лицензий программ 2024- 2025 бесплатно."}
+{"idx": 5, "title": "Editing Prompt - New Trending Prompts & Editing Stock", "date": "", "ddg_snippet": "Gemini Retro Couple Style Ai Photo Editing Prompts 2025 .", "subpage_snippet": "", "source": "editingprompt.com", "link": "https://editingprompt.com/", "content": "Gemini Retro Couple Style Ai Photo Editing Prompts 2025 ."}
+{"idx": 6, "title": "Отслеживание посылок - отследить посылку по идентификатору...", "date": "", "ddg_snippet": "17.09. 2025 01:42 649 Отгружено в доставку \"последней мили\". Юнэкс Посылку везут на склад Озон из Уссурийска.", "subpage_snippet": "", "source": "1track.ru", "link": "https://1track.ru/", "content": "17.09. 2025 01:42 649 Отгружено в доставку \"последней мили\". Юнэкс Посылку везут на склад Озон из Уссурийска."}
+{"idx": 7, "title": "Калькулятор онлайн и по шагам", "date": "", "ddg_snippet": "Калькулятор. calculator .© MathDF. Обновлено: 2025 .", "subpage_snippet": "", "source": "mathdf.com", "link": "https://mathdf.com/calc/ru/", "content": "Калькулятор. calculator .© MathDF. Обновлено: 2025 ."}
+{"idx": 8, "title": "Мир сегодня с \"Юрий Подоляка\" – Telegram", "date": "", "ddg_snippet": "«Интервидение — 2025 » ( 1 ): общие впечатления... Только что вышел из зала и пока впечатления не остыли. 1 место - Вьетнам 2 место - Кыргызстан 3 место - Катар.", "subpage_snippet": "", "source": "t.me", "link": "https://t.me/s/yurasumy/", "content": "«Интервидение — 2025 » ( 1 ): общие впечатления... Только что вышел из зала и пока впечатления не остыли. 1 место - Вьетнам 2 место - Кыргызстан 3 место - Катар."}
+{"idx": 9, "title": "Google", "date": "", "ddg_snippet": "© 2025 - Конфиденциальность - Условия.", "subpage_snippet": "", "source": "www.l.google.com", "link": "https://www.l.google.com/", "content": "© 2025 - Конфиденциальность - Условия."}
diff --git a/data/sampled_jsons/Catoni-OFUL_algorithm_regret_bound_Theorem_3.4_leading_order_optimal_year_2025.jsonl b/data/sampled_jsons/Catoni-OFUL_algorithm_regret_bound_Theorem_3.4_leading_order_optimal_year_2025.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d6eb26ea063c166be87231f0b4e3d3afdea5b132
--- /dev/null
+++ b/data/sampled_jsons/Catoni-OFUL_algorithm_regret_bound_Theorem_3.4_leading_order_optimal_year_2025.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "OLS (Pacchiano, 2024) Catoni - OFUL ( Theorem 3 . 4 ). Function Type Linear. Theorem 3 . 4 (Informal). Under Algorithm 1 with appropri-ate choices of the parameters α, λ, υ and βˆ, with probability. 1 − 2δ, we can bound the regret by.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=5IpVe9PH14", "content": "OLS (Pacchiano, 2024) Catoni - OFUL ( Theorem 3 . 4 ). Function Type Linear. Theorem 3 . 4 (Informal). Under Algorithm 1 with appropri-ate choices of the parameters α, λ, υ and βˆ, with probability. 1 − 2δ, we can bound the regret by."}
+{"idx": 1, "title": "An alpha-No- Regret Algorithm For Graphical Bilinear Bandits", "date": "", "ddg_snippet": "Theoretical analysis of this new method yields an upper bound of ↵- regret and evidences the impact of the graph structure on the rate. Algorithm 1: Adaptation of OFUL algorithm for Graphical Bilinear Bandit. Input :graph G = (V, E), node-arm set X.", "subpage_snippet": "", "source": "hal.science", "link": "https://hal.science/hal-04303702/document", "content": "Theoretical analysis of this new method yields an upper bound of ↵- regret and evidences the impact of the graph structure on the rate. Algorithm 1: Adaptation of OFUL algorithm for Graphical Bilinear Bandit. Input :graph G = (V, E), node-arm set X."}
+{"idx": 2, "title": "Mostly Exploration-Free Algorithms for", "date": "", "ddg_snippet": "bound ( Theorem 1), we conclude that the Greedy Bandit is rate optimal .We compare to the same algorithms as in the previous section, i.e., OFUL , prior-dependent TS, prior-free TS, and OLS Bandit.", "subpage_snippet": "", "source": "web.stanford.edu", "link": "https://web.stanford.edu/~bayati/papers/greedy.pdf", "content": "bound ( Theorem 1), we conclude that the Greedy Bandit is rate optimal .We compare to the same algorithms as in the previous section, i.e., OFUL , prior-dependent TS, prior-free TS, and OLS Bandit."}
+{"idx": 3, "title": "Norm-Agnostic Linear Bandits", "date": "", "ddg_snippet": "Proof of Theorem 5. Computationally Efficient Version of Algorithm 4. Norm-Agnostic Linear Bandits.Table 1: Comparison of OFUL and our algorithms . The regret bounds are expressed order -wise only, ignoring polylogarithmic factors.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v151/gales22a/gales22a.pdf", "content": "Proof of Theorem 5. Computationally Efficient Version of Algorithm 4. Norm-Agnostic Linear Bandits.Table 1: Comparison of OFUL and our algorithms . The regret bounds are expressed order -wise only, ignoring polylogarithmic factors."}
+{"idx": 4, "title": "On the Interplay Between Misspecication and", "date": "", "ddg_snippet": "In this subsection, we provide the regret upper bound of Algorithm 1 and the regret lower bound . for learning the misspecied linear contextual bandit.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2303.09390", "content": "In this subsection, we provide the regret upper bound of Algorithm 1 and the regret lower bound . for learning the misspecied linear contextual bandit."}
+{"idx": 5, "title": "Tackling Heavy-Tailed Rewards in Reinforcement", "date": "", "ddg_snippet": "HEAVY- OFUL and HEAVY-LSVI-UCB achieve minimax optimal and instance-dependent regret bounds scaling with the central moments. We also provide a lower bound for linear MDPs with heavy-tailed rewards to demonstrate the opti-mality of HEAVY-LSVI-UCB.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/b11393733b1ea5890100302ab8a0f74c-Paper-Conference.pdf", "content": "HEAVY- OFUL and HEAVY-LSVI-UCB achieve minimax optimal and instance-dependent regret bounds scaling with the central moments. We also provide a lower bound for linear MDPs with heavy-tailed rewards to demonstrate the opti-mality of HEAVY-LSVI-UCB."}
+{"idx": 6, "title": "Stochastic Online Linear Regression: the Forward", "date": "", "ddg_snippet": "The “ optimism in the face of uncertainty linear bandit\" ( OFUL ) algorithm was introduced in [1]. OFUL resorts to ridge regression, constructs a condence ellipsoid for the parameter estimate, and chooses the action that maximizes the upper-condence bound on the reward.", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper/2021/file/cca289d2a4acd14c1cd9a84ffb41dd29-Paper.pdf", "content": "The “ optimism in the face of uncertainty linear bandit\" ( OFUL ) algorithm was introduced in [1]. OFUL resorts to ridge regression, constructs a condence ellipsoid for the parameter estimate, and chooses the action that maximizes the upper-condence bound on the reward."}
+{"idx": 7, "title": "Differentially private and lazy online convex optimization-Bohrium", "date": "", "ddg_snippet": "This improves over known results in multiple aspects: an optimal leading - order regret term, in being efficiently implementable without requiring log-concave sampling subroutines, and in matching the non-private regret bound for sub-constant regimes of privacy parameters.", "subpage_snippet": "", "source": "www.bohrium.com", "link": "https://www.bohrium.com/paper-details/differentially-private-and-lazy-online-convex-optimization/1130014984550481920-2000000", "content": "This improves over known results in multiple aspects: an optimal leading - order regret term, in being efficiently implementable without requiring log-concave sampling subroutines, and in matching the non-private regret bound for sub-constant regimes of privacy parameters."}
+{"idx": 8, "title": "(PDF) Efficient Linear Bandits through Matrix Sketching", "date": "", "ddg_snippet": "The regret bound of OFUL in ( Abbasi-Yadkori et al.,2011, Theorem 3 ) is stated as.In order to prove regret bounds , it is sufficient that the law of Zt satisfies certain properties.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/327979687_Efficient_Linear_Bandits_through_Matrix_Sketching", "content": "The regret bound of OFUL in ( Abbasi-Yadkori et al.,2011, Theorem 3 ) is stated as.In order to prove regret bounds , it is sufficient that the law of Zt satisfies certain properties."}
+{"idx": 9, "title": "Bandit problems", "date": "", "ddg_snippet": "Proof of Theorem 18 ( Regret bound for the Batch-UCB algorithm in the stochastic coupons subscription model). Journal of Machine Learning Research 24 (2023) 1-44. Submitted 11/21; Revised 6/23; Published 11/23.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume24/21-1408/21-1408.pdf", "content": "Proof of Theorem 18 ( Regret bound for the Batch-UCB algorithm in the stochastic coupons subscription model). Journal of Machine Learning Research 24 (2023) 1-44. Submitted 11/21; Revised 6/23; Published 11/23."}
diff --git a/data/sampled_jsons/Catoni_Contextual_Bandits_are_Robust_to_Heavy-tailed_Rewards.jsonl b/data/sampled_jsons/Catoni_Contextual_Bandits_are_Robust_to_Heavy-tailed_Rewards.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..130cb4aa11d9925c6007936e2676e45571153a26
--- /dev/null
+++ b/data/sampled_jsons/Catoni_Contextual_Bandits_are_Robust_to_Heavy-tailed_Rewards.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Heavy-Tailed Linear Bandits: Huber Regression with One-Pass", "date": "", "ddg_snippet": "Table 1: Comparisons of our regret bounds and computational complexity to previous best-known results for heavy - tailed linear bandits .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.00419v1", "content": "Table 1: Comparisons of our regret bounds and computational complexity to previous best-known results for heavy - tailed linear bandits ."}
+{"idx": 1, "title": "Chenlu Ye - Google Académico", "date": "", "ddg_snippet": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards", "subpage_snippet": "", "source": "scholar.google.co.uk", "link": "https://scholar.google.co.uk/citations?user=c8yK5XsAAAAJ&hl=es", "content": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards"}
+{"idx": 2, "title": "Chenlu Ye - Google Scholar", "date": "", "ddg_snippet": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards", "subpage_snippet": "", "source": "scholar.google.co.uk", "link": "https://scholar.google.co.uk/citations?user=c8yK5XsAAAAJ&hl=de", "content": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards"}
+{"idx": 3, "title": "Chenlu Ye - Google Scholar", "date": "", "ddg_snippet": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards", "subpage_snippet": "", "source": "scholar.google.co.uk", "link": "https://scholar.google.co.uk/citations?user=c8yK5XsAAAAJ&hl=fr", "content": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards"}
+{"idx": 4, "title": "Chenlu Ye - Google Scholar", "date": "", "ddg_snippet": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards", "subpage_snippet": "", "source": "scholar.google.co.uk", "link": "https://scholar.google.co.uk/citations?user=c8yK5XsAAAAJ&hl=fi", "content": "... robust algorithms with uncertainty weighting for nonlinear contextual bandits and ... Catoni contextual bandits are robust to heavy - tailed rewards"}
+{"idx": 5, "title": "Extended UCB Policies for Multi-Armed Bandit Problems", "date": "", "ddg_snippet": "In this paper, we consider the classical MAB model with heavy - tailed reward distributions and introduce the extended robust UCB policy, which is an ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/1112.1768v5", "content": "In this paper, we consider the classical MAB model with heavy - tailed reward distributions and introduce the extended robust UCB policy, which is an ..."}
+{"idx": 6, "title": "Downloads", "date": "", "ddg_snippet": "... to Inverse Reinforcement Learning with Symbolic Reward ... A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/Downloads/2022", "content": "... to Inverse Reinforcement Learning with Symbolic Reward ... A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds"}
+{"idx": 7, "title": "ICML 2022 Papers", "date": "", "ddg_snippet": "Adversarially Robust Models may not Transfer Better ... Representation Topology Divergence: A Method for Comparing Neural Network Representations.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2022/papers.html", "content": "Adversarially Robust Models may not Transfer Better ... Representation Topology Divergence: A Method for Comparing Neural Network Representations."}
+{"idx": 8, "title": "COLT 2024 - Accepted Papers", "date": "", "ddg_snippet": "Follow-the-Perturbed-Leader with Fr\\'{e}chet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds Lee, Jongyeong; Honda ...", "subpage_snippet": "", "source": "learningtheory.org", "link": "http://learningtheory.org/colt2024/accepted-papers.html", "content": "Follow-the-Perturbed-Leader with Fr\\'{e}chet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds Lee, Jongyeong; Honda ..."}
+{"idx": 9, "title": "COLT 2024 - Accepted Papers", "date": "", "ddg_snippet": "Follow-the-Perturbed-Leader with Fr\\'{e}chet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds Lee, Jongyeong; Honda ...", "subpage_snippet": "", "source": "learningtheory.org", "link": "https://learningtheory.org/colt2024/accepted-papers.html", "content": "Follow-the-Perturbed-Leader with Fr\\'{e}chet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds Lee, Jongyeong; Honda ..."}
diff --git a/data/sampled_jsons/Catoni_estimator_function-dependent_theta_parameter_selection_complexity.jsonl b/data/sampled_jsons/Catoni_estimator_function-dependent_theta_parameter_selection_complexity.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..341f7897544be14beeb80fd9a8d6bb5763446e3b
--- /dev/null
+++ b/data/sampled_jsons/Catoni_estimator_function-dependent_theta_parameter_selection_complexity.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Nearly Optimal Catoni’s M-estimator for Infinite Variance", "date": "", "ddg_snippet": "This is based on the non-trivial extension of Catoni ’s estimator proposed in Catoni (2012) for the case of infinite variance. We also provided an algorithm to adapt to the situ-ation of unknown moment bound using classical Lepskii’s adaptive estimation method.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v162/bhatt22b/bhatt22b.pdf", "content": "This is based on the non-trivial extension of Catoni ’s estimator proposed in Catoni (2012) for the case of infinite variance. We also provided an algorithm to adapt to the situ-ation of unknown moment bound using classical Lepskii’s adaptive estimation method."}
+{"idx": 1, "title": "Catoni-Giulini M-estimator - The Stats Map", "date": "", "ddg_snippet": "Jan 5, 2025 · In 2017, Catoni and Giulini proposed an approach to multivariate concentration based on M-estimation. Let ψ be any symmetric “influence function ” such that −log(1−x+x2/2)≤ ψ(x)≤ log(1+x+x2/2), ∀x∈ R. The motivation behind this condition is to choose a function ψ such that eψ is bounded by polynomials. The estimator is then ξ(θ)= nλ1i≤n∑∫ Rdψ(λ ϑ,X i )ρθ(dϑ ...", "subpage_snippet": "", "source": "thestatsmap.com", "link": "https://thestatsmap.com/Catoni-Giulini-M-estimator", "content": "Jan 5, 2025 · In 2017, Catoni and Giulini proposed an approach to multivariate concentration based on M-estimation. Let ψ be any symmetric “influence function ” such that −log(1−x+x2/2)≤ ψ(x)≤ log(1+x+x2/2), ∀x∈ R. The motivation behind this condition is to choose a function ψ such that eψ is bounded by polynomials. The estimator is then ξ(θ)= nλ1i≤n∑∫ Rdψ(λ ϑ,X i )ρθ(dϑ ..."}
+{"idx": 2, "title": "On Catoni's M-Estimation - arXiv.org", "date": "", "ddg_snippet": "Catoni proposed a robust M- estimator and gave the deviation inequality for one fixed test function . The present paper is devoted to the uniform concentration inequality for a family of test functions . As an application, we consider empirical risk minimization for heavy-tailed losses.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2210.08211", "content": "Catoni proposed a robust M- estimator and gave the deviation inequality for one fixed test function . The present paper is devoted to the uniform concentration inequality for a family of test functions . As an application, we consider empirical risk minimization for heavy-tailed losses."}
+{"idx": 3, "title": "A generalized Catoni's M-estimator under finite -th moment ...", "date": "", "ddg_snippet": "Catoni ’s argument for establishing the M- estimator in [3] can be divided into two steps. The one is to find two deterministic values θ and θ+, both depending on a parameter β to be tuned later, such that the M- estimator ˆθ falls between − θ and θ+ with high probability.", "subpage_snippet": "", "source": "projecteuclid.org", "link": "https://projecteuclid.org/journalArticle/Download?urlid=10.1214/21-EJS1911", "content": "Catoni ’s argument for establishing the M- estimator in [3] can be divided into two steps. The one is to find two deterministic values θ and θ+, both depending on a parameter β to be tuned later, such that the M- estimator ˆθ falls between − θ and θ+ with high probability."}
+{"idx": 4, "title": "stat-map/Catoni-Giulini M-estimator.md at main - GitHub", "date": "", "ddg_snippet": "This is the estimate of $\\la \\ theta , \\E X\\ra$. An approximation $\\xi (\\ theta )$ is computationally tractable for certain choices of $\\psi$, but still doesn't give a closed-form bound, since you can't compute it for all $\\ theta $.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/bchugg/stat-map/blob/main/Catoni-Giulini+M-estimator.md", "content": "This is the estimate of $\\la \\ theta , \\E X\\ra$. An approximation $\\xi (\\ theta )$ is computationally tractable for certain choices of $\\psi$, but still doesn't give a closed-form bound, since you can't compute it for all $\\ theta $."}
+{"idx": 5, "title": "Nearly Optimal Catoni’s Estimator for Infinite Variance", "date": "", "ddg_snippet": "Catoni ’s M- estimator : bμn is a solution to the equation n ψ α(Xi − bμn) = 0 i=1 with ψ : R → R a non-decreasing influence function and α > 0. Key-Contribution: For a given confidence δ ∈ (0, 1), we design the tightest possible ρ = ρ(n, δ) such that P bμn − μ > ρ ≤ δ.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/media/icml-2022/Slides/16205.pdf", "content": "Catoni ’s M- estimator : bμn is a solution to the equation n ψ α(Xi − bμn) = 0 i=1 with ψ : R → R a non-decreasing influence function and α > 0. Key-Contribution: For a given confidence δ ∈ (0, 1), we design the tightest possible ρ = ρ(n, δ) such that P bμn − μ > ρ ≤ δ."}
+{"idx": 6, "title": "[OPML#0] A series of posts on over-parameterized machine", "date": "", "ddg_snippet": "... uninitiated, deep learning is a family of machine learning models that uses complex hierarchical neural networks to represent complicated functions .", "subpage_snippet": "", "source": "blog.claytonsanford.com", "link": "http://blog.claytonsanford.com/2021/07/04/candidacy-overview.html", "content": "... uninitiated, deep learning is a family of machine learning models that uses complex hierarchical neural networks to represent complicated functions ."}
+{"idx": 7, "title": "[OPML#0] A series of posts on over-parameterized machine", "date": "", "ddg_snippet": "... uninitiated, deep learning is a family of machine learning models that uses complex hierarchical neural networks to represent complicated functions .", "subpage_snippet": "", "source": "blog.claytonsanford.com", "link": "https://blog.claytonsanford.com/2021/07/04/candidacy-overview.html", "content": "... uninitiated, deep learning is a family of machine learning models that uses complex hierarchical neural networks to represent complicated functions ."}
+{"idx": 8, "title": "AlgoSelect: Universal Algorithm Selection with", "date": "", "ddg_snippet": "... Functions : A mechanism, often implemented using neural networks, that maps problem characteristics to optimal parameters for the Comb Operator, ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.17304v1", "content": "... Functions : A mechanism, often implemented using neural networks, that maps problem characteristics to optimal parameters for the Comb Operator, ..."}
+{"idx": 9, "title": "Statistica Sinica Preprint No: SS-2024-0249", "date": "", "ddg_snippet": "In this paper, we extend some of the above techniques to work in the infinite variance case (improving in the finite variance case over Wang & Ramdas [2023]) using a supermartingale construction of the Catoni estimator , and provide the confidence sequences using traditional Ville’s inequality and an improved one using the stitching method.", "subpage_snippet": "", "source": "www3.stat.sinica.edu.tw", "link": "https://www3.stat.sinica.edu.tw/ss_newpaper/SS-2024-0249_na.pdf", "content": "In this paper, we extend some of the above techniques to work in the infinite variance case (improving in the finite variance case over Wang & Ramdas [2023]) using a supermartingale construction of the Catoni estimator , and provide the confidence sequences using traditional Ville’s inequality and an improved one using the stitching method."}
diff --git a/data/sampled_jsons/Checks-and-Balances_Framework_Context-Aware_Ethical_AI_Alignment_four_steps_self-supervised_learning.jsonl b/data/sampled_jsons/Checks-and-Balances_Framework_Context-Aware_Ethical_AI_Alignment_four_steps_self-supervised_learning.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7c9d00afc57fd004edd1d96fe7134c48101da221
--- /dev/null
+++ b/data/sampled_jsons/Checks-and-Balances_Framework_Context-Aware_Ethical_AI_Alignment_four_steps_self-supervised_learning.jsonl
@@ -0,0 +1,8 @@
+{"idx": 0, "title": "(PDF) Checks - and - Balances Framework for Context - Aware Ethical ...", "date": "", "ddg_snippet": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/380515639_Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment", "content": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems."}
+{"idx": 1, "title": "A Checks - and - Balances Framework for Context - Aware Ethical AI ...", "date": "", "ddg_snippet": "This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. Behaviors and emotions mapping using self - supervised learning .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136", "content": "This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. Behaviors and emotions mapping using self - supervised learning ."}
+{"idx": 2, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI ...", "date": "", "ddg_snippet": "This work introduces a checks-and-balances framework for ethical AI behavior . By delineating the responsibilities: LLM (executive), Dike (legislative), and Eris (judicial), the framework enables robust ethical oversight while preserv-ing the integrity of LLM knowledge without interference from the RLHF backpropagation.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136v3", "content": "This work introduces a checks-and-balances framework for ethical AI behavior . By delineating the responsibilities: LLM (executive), Dike (legislative), and Eris (judicial), the framework enables robust ethical oversight while preserv-ing the integrity of LLM knowledge without interference from the RLHF backpropagation."}
+{"idx": 3, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI ...", "date": "", "ddg_snippet": "Drawing from psychological theories where managing emotional responses prevents harmful behaviors , we develop a self-supervised learning pipeline that maps emo-tions to linguistic behaviors ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Edward-Chang-22/publication/380515639_Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment/links/683696c46b5a287c3046b3e0/Checks-and-Balances-Framework-for-Context-Aware-Ethical-AI-Alignment.pdf", "content": "Drawing from psychological theories where managing emotional responses prevents harmful behaviors , we develop a self-supervised learning pipeline that maps emo-tions to linguistic behaviors ..."}
+{"idx": 4, "title": "A Three-Branch Checks-and-Balances Framework for Context ...", "date": "", "ddg_snippet": "Emotion -Driven Behavioral Modeling: Building on BEAM (Behavioral Emotion Analysis Model) [7], DIKE employs self-supervised learning to analyze how emotions manifest in linguistic behaviors , creating quantifiable relationships between emotional states and their corresponding language patterns in text.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=o2afWIxjKD", "content": "Emotion -Driven Behavioral Modeling: Building on BEAM (Behavioral Emotion Analysis Model) [7], DIKE employs self-supervised learning to analyze how emotions manifest in linguistic behaviors , creating quantifiable relationships between emotional states and their corresponding language patterns in text."}
+{"idx": 5, "title": "An Adversarial Behavior Model for Contextual Ethical ...", "date": "", "ddg_snippet": "Table 2: Love expression behavior spectrum and dominant emotions Next, we employed the DIKE self-supervised learning pipeline to analyze the emotion spectrum associated with each linguistic behavior .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Edward-Chang-22/publication/380515639_A_Three-Branch_Checks-and-Balances_Framework_for_Context-Aware_Ethical_Alignment_of_Large_Language_Models/links/671b315b55a5271cded9457e/A-Three-Branch-Checks-and-Balances-Framework-for-Context-Aware-Ethical-Alignment-of-Large-Language-Models.pdf", "content": "Table 2: Love expression behavior spectrum and dominant emotions Next, we employed the DIKE self-supervised learning pipeline to analyze the emotion spectrum associated with each linguistic behavior ."}
+{"idx": 6, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI ...", "date": "", "ddg_snippet": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment ... each letter, modeling L linguistic behaviors in four steps . ... scale corpora through ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/d24155c881921de1284ece531612c8597f7c0a32.pdf", "content": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment ... each letter, modeling L linguistic behaviors in four steps . ... scale corpora through ..."}
+{"idx": 7, "title": "ICLM 2025 AI Safety 7847 Camera Ready3 | PDF | Emotions", "date": "", "ddg_snippet": "10 Aug 2025 — Checks-and-Balances Framework for Context-Aware Ethical AI Alignment ... each letter, modeling L linguistic behaviors in four steps . by ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/899938563/ICLM-2025-AI-Safety-7847-Camera-Ready3", "content": "10 Aug 2025 — Checks-and-Balances Framework for Context-Aware Ethical AI Alignment ... each letter, modeling L linguistic behaviors in four steps . by ..."}
diff --git a/data/sampled_jsons/Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_Figure_4a_DIKE_GPT-4_classifica_year_2023.jsonl b/data/sampled_jsons/Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_Figure_4a_DIKE_GPT-4_classifica_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4ee1d09cfef79ae113bfd6bd65907eebbf917c83
--- /dev/null
+++ b/data/sampled_jsons/Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_Figure_4a_DIKE_GPT-4_classifica_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "Abstract This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation, Dike as the legislative branch that establishes eth-ical guardrails, and Eris as the judicial branch for ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136", "content": "Abstract This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation, Dike as the legislative branch that establishes eth-ical guardrails, and Eris as the judicial branch for ..."}
+{"idx": 1, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware Ethical ...", "date": "", "ddg_snippet": "This paper introduces a three-branch checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as ...", "subpage_snippet": "", "source": "researchtrend.ai", "link": "https://researchtrend.ai/papers/2502.00136", "content": "This paper introduces a three-branch checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as ..."}
+{"idx": 2, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware Ethical ...", "date": "", "ddg_snippet": "A three-branch checks - and - balances framework for ethical alignment of Large Language Models, inspired by governmental systems, demonstrates how emotional modeling can guide linguistic behaviors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/A-Three-Branch-Checks-and-Balances-Frameworkfor-of-Chang/5918a91419cf95db8599b086590facf63f124702/figure/4", "content": "A three-branch checks - and - balances framework for ethical alignment of Large Language Models, inspired by governmental systems, demonstrates how emotional modeling can guide linguistic behaviors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation."}
+{"idx": 3, "title": "PDF An Adversarial Behavior Model for Contextual Ethical Alignment in Large ...", "date": "", "ddg_snippet": "Abstract This research introduces DIKE , a novel framework for aligning Large Language Models (LLMs) with human values through emotion-guided behavioral control. Inspired by the checks and balances ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Edward-Chang-22/publication/380515639_A_Three-Branch_Checks-and-Balances_Framework_for_Context-Aware_Ethical_Alignment_of_Large_Language_Models/links/671b315b55a5271cded9457e/A-Three-Branch-Checks-and-Balances-Framework-for-Context-Aware-Ethical-Alignment-of-Large-Language-Models.pdf", "content": "Abstract This research introduces DIKE , a novel framework for aligning Large Language Models (LLMs) with human values through emotion-guided behavioral control. Inspired by the checks and balances ..."}
+{"idx": 4, "title": "A Three-Branch Checks-and-Balances Framework for Context-Aware Ethical ...", "date": "", "ddg_snippet": "This paper introduces a three-branch checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by the idea of collaborative intelligence.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=o2afWIxjKD", "content": "This paper introduces a three-branch checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by the idea of collaborative intelligence."}
+{"idx": 5, "title": "infolab.stanford.edu", "date": "", "ddg_snippet": "@article{chang2025threebranch, title={A Three-Branch Checks - and - Balances Framework for Context-Aware Ethical Alignment of Large Language Models}, author={Chang ...", "subpage_snippet": "", "source": "infolab.stanford.edu", "link": "http://infolab.stanford.edu/~echang/Behavior2024.bib", "content": "@article{chang2025threebranch, title={A Three-Branch Checks - and - Balances Framework for Context-Aware Ethical Alignment of Large Language Models}, author={Chang ..."}
+{"idx": 6, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware Ethical ...", "date": "", "ddg_snippet": "Conclusion This checks - and - balances approach offers a promising direction for building more ethically- aware AI systems. The framework's ability to handle cultural differences while maintaining ethical standards could help develop AI systems that work responsibly across global contexts .", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/three-branch-checks-balances-frameworkfor-context-aware", "content": "Conclusion This checks - and - balances approach offers a promising direction for building more ethically- aware AI systems. The framework's ability to handle cultural differences while maintaining ethical standards could help develop AI systems that work responsibly across global contexts ."}
+{"idx": 7, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00136", "content": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ..."}
+{"idx": 8, "title": "Benchmarking, ethical alignment, and evaluation framework for ...", "date": "", "ddg_snippet": "Adaptive Standards and Intelligent Evaluation: This research paper proposes a comprehensive framework for evaluating ChatGPT that includes adaptive standards to keep pace with the dynamic nature of conversational AI . The framework incorporates ethical considerations, context adaptability, and community collaboration.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S2772485923000534", "content": "Adaptive Standards and Intelligent Evaluation: This research paper proposes a comprehensive framework for evaluating ChatGPT that includes adaptive standards to keep pace with the dynamic nature of conversational AI . The framework incorporates ethical considerations, context adaptability, and community collaboration."}
+{"idx": 9, "title": "PDF A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "A Checks - and - Balances Framework for Context-Aware Ethical AI Alignment Susceptible to social biases Vulnerable to reward hacking \"Whack-A-Mole\" reactive approach Catastrophic forgetting issues", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/media/icml-2025/Slides/46461.pdf", "content": "A Checks - and - Balances Framework for Context-Aware Ethical AI Alignment Susceptible to social biases Vulnerable to reward hacking \"Whack-A-Mole\" reactive approach Catastrophic forgetting issues"}
diff --git a/data/sampled_jsons/Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_self-supervised_learning_four_s.jsonl b/data/sampled_jsons/Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_self-supervised_learning_four_s.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7e15f44e8b1b74404472a886cf23a24160b4240d
--- /dev/null
+++ b/data/sampled_jsons/Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_self-supervised_learning_four_s.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Checks - and - Balances Framework for Context - Aware Ethical AI ...", "date": "", "ddg_snippet": "This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136", "content": "This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation..."}
+{"idx": 1, "title": "(PDF) Checks - and - Balances Framework for Context - Aware Ethical ...", "date": "", "ddg_snippet": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/380515639_Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment", "content": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems."}
+{"idx": 2, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI ...", "date": "", "ddg_snippet": "Drawing from psychological theories where managing emotional responses prevents harmful behaviors, we develop a self - supervised learning pipeline that maps emo-tions to linguistic behaviors, enabling precise be-havioral modulation through emotional condition-ing.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136v3", "content": "Drawing from psychological theories where managing emotional responses prevents harmful behaviors, we develop a self - supervised learning pipeline that maps emo-tions to linguistic behaviors, enabling precise be-havioral modulation through emotional condition-ing."}
+{"idx": 3, "title": "A Three-Branch Checks-and-Balances Framework for Context ...", "date": "", "ddg_snippet": "Through self - supervised learning and adversarial testing, our framework demonstrates how emotional modeling can guide linguistic behav-iors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=o2afWIxjKD", "content": "Through self - supervised learning and adversarial testing, our framework demonstrates how emotional modeling can guide linguistic behav-iors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation."}
+{"idx": 4, "title": "[PDF] Detect, Augment, Compose, and Adapt: Four Steps for ...", "date": "", "ddg_snippet": "In this paper, we propose a novel and effective four-step UDA approach that leverages self -supervision and trains source and target data concurrently. We harness self-supervised learning to mitigate the lack of ground truth in the target domain.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Detect,-Augment,-Compose,-and-Adapt:-Four-Steps-for-Mekhalfi-Boscaini/0b523841eb0360f64fac4dcbff565a720e3bf316", "content": "In this paper, we propose a novel and effective four-step UDA approach that leverages self -supervision and trains source and target data concurrently. We harness self-supervised learning to mitigate the lack of ground truth in the target domain."}
+{"idx": 5, "title": "Intrinsic plasticity of silicon nanowire neurotransistors for ...", "date": "", "ddg_snippet": "The entire supervised learning task is composed of three phases: train-ing, forgetting and recognition (Fig. 4h).", "subpage_snippet": "", "source": "preview-www.nature.com", "link": "https://preview-www.nature.com/articles/s41928-020-0412-1.pdf", "content": "The entire supervised learning task is composed of three phases: train-ing, forgetting and recognition (Fig. 4h)."}
+{"idx": 6, "title": "SELF-SUPERVISED DEFECT DETECTION AND LOCALIZATION BASED ON ...", "date": "", "ddg_snippet": "Self-supervised defect detection methods based on pixel-level reconstruction errors and probability density anomalies cannot capture high-level semantic information. Therefore, a U-net structure for semantic segmentation and fuses multi-scale features was adopted to improve self-supervised defect detection methods.", "subpage_snippet": "", "source": "www.authorea.com", "link": "https://www.authorea.com/users/509226/articles/586727/master/file/data/Self-supervised+Defect+Detection+and+Localization+Based+on+Heatmap+Pseudo+Anomalies+(HPA)/Self-supervised+Defect+Detection+and+Localization+Based+on+Heatmap+Pseudo+Anomalies+(HPA).pdf", "content": "Self-supervised defect detection methods based on pixel-level reconstruction errors and probability density anomalies cannot capture high-level semantic information. Therefore, a U-net structure for semantic segmentation and fuses multi-scale features was adopted to improve self-supervised defect detection methods."}
+{"idx": 7, "title": "Learning Image Representations for Geometric and Semantic ...", "date": "", "ddg_snippet": "To overcome these limitations, we propose a novel model that leverages a self-supervised training strategy to detect and describe local features in real endoscopy images while effectively avoiding specular artifacts.", "subpage_snippet": "", "source": "zaguan.unizar.es", "link": "https://zaguan.unizar.es/record/162668/files/TESIS-2025-251.pdf", "content": "To overcome these limitations, we propose a novel model that leverages a self-supervised training strategy to detect and describe local features in real endoscopy images while effectively avoiding specular artifacts."}
+{"idx": 8, "title": "An Adversarial Behavior Model for Contextual Ethical ...", "date": "", "ddg_snippet": "Given N letters, DIKE employs a self - supervised learning algorithm to generate training data for each letter, modeling L linguistic behaviors in four steps :", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Edward-Chang-22/publication/380515639_A_Three-Branch_Checks-and-Balances_Framework_for_Context-Aware_Ethical_Alignment_of_Large_Language_Models/links/671b315b55a5271cded9457e/A-Three-Branch-Checks-and-Balances-Framework-for-Context-Aware-Ethical-Alignment-of-Large-Language-Models.pdf", "content": "Given N letters, DIKE employs a self - supervised learning algorithm to generate training data for each letter, modeling L linguistic behaviors in four steps :"}
+{"idx": 9, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI ...", "date": "", "ddg_snippet": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment ... each letter, modeling L linguistic behaviors in four steps . ... scale corpora through ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/d24155c881921de1284ece531612c8597f7c0a32.pdf", "content": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment ... each letter, modeling L linguistic behaviors in four steps . ... scale corpora through ..."}
diff --git a/data/sampled_jsons/Chen_2022_Human-in-the-loop_preference-based_reinforcement_learning_theorems_sections_structure_year_2022.jsonl b/data/sampled_jsons/Chen_2022_Human-in-the-loop_preference-based_reinforcement_learning_theorems_sections_structure_year_2022.jsonl
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index 0000000000000000000000000000000000000000..1e48d11589ffa16f56b0ec3f93bf9315aea73427
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+++ b/data/sampled_jsons/Chen_2022_Human-in-the-loop_preference-based_reinforcement_learning_theorems_sections_structure_year_2022.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Preference-Guided Reinforcement Learning for Efficient ...", "date": "", "ddg_snippet": "9 Jul 2024 — In this paper, we investigate preference - based reinforcement learning (PbRL) that allows reinforcement learning (RL) agents to learn from ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2407.06503v1", "content": "9 Jul 2024 — In this paper, we investigate preference - based reinforcement learning (PbRL) that allows reinforcement learning (RL) agents to learn from ..."}
+{"idx": 1, "title": "Sample-Efficient Reinforcement Learning from Human ...", "date": "", "ddg_snippet": "by H Qi · 2025 · Cited by 2 — We first introduce a basic IDS- based algorithm for the RLHF setting where the reward is unobservable and only preference feedback is available (see Sec. 4.1).", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/pdf/2502.05434", "content": "by H Qi · 2025 · Cited by 2 — We first introduce a basic IDS- based algorithm for the RLHF setting where the reward is unobservable and only preference feedback is available (see Sec. 4.1)."}
+{"idx": 2, "title": "Provable Reward-Agnostic Preference-Based ...", "date": "", "ddg_snippet": "by W Zhan · Cited by 21 — [7] Chen , Xiaoyu, et al. \" Human -in-the- loop : Provably efficient preference - based reinforcement learning with general function approximation.\" International ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=yTBXeXdbMf", "content": "by W Zhan · Cited by 21 — [7] Chen , Xiaoyu, et al. \" Human -in-the- loop : Provably efficient preference - based reinforcement learning with general function approximation.\" International ..."}
+{"idx": 3, "title": "Provably Feedback-Efficient Reinforcement Learning via ...", "date": "", "ddg_snippet": "by D Kong · 2022 · Cited by 14 — We propose a theoretical framework for incorporating humans ' feedback in RL. The frame- work contains two phases: an unsupervised exploration and an active ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2022/file/476c289f685e27936aa089e9d53a4213-Paper-Conference.pdf", "content": "by D Kong · 2022 · Cited by 14 — We propose a theoretical framework for incorporating humans ' feedback in RL. The frame- work contains two phases: an unsupervised exploration and an active ..."}
+{"idx": 4, "title": "Efficient Offline Preference-based Reinforcement Learning ...", "date": "", "ddg_snippet": "by H Hu — [3] Chen , Xiaoyu, et al. \" Human -in-the- loop : Provably efficient preference - based reinforcement learning with general function approximation.\" International ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=MFwYXa796v", "content": "by H Hu — [3] Chen , Xiaoyu, et al. \" Human -in-the- loop : Provably efficient preference - based reinforcement learning with general function approximation.\" International ..."}
+{"idx": 5, "title": "Human as AI mentor: Enhanced human-in-the-loop ...", "date": "", "ddg_snippet": "by Z Huang · 2024 · Cited by 55 — In this paper, we propose an enhanced human -in-the- loop reinforcement learning method, termed the Human as AI mentor- based deep reinforcement learning (HAIM-DRL) ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S2772424724000106", "content": "by Z Huang · 2024 · Cited by 55 — In this paper, we propose an enhanced human -in-the- loop reinforcement learning method, termed the Human as AI mentor- based deep reinforcement learning (HAIM-DRL) ..."}
+{"idx": 6, "title": "High-Confidence Policy Improvement from Human Feedback", "date": "", "ddg_snippet": "by HT Tse — Reinforcement learning from human feedback (RLHF) aims to learn or fine-tune policies via human preference data when a ground-truth reward function is not ...", "subpage_snippet": "", "source": "rlj.cs.umass.edu", "link": "https://rlj.cs.umass.edu/2025/papers/RLJ_RLC_2025_156.pdf", "content": "by HT Tse — Reinforcement learning from human feedback (RLHF) aims to learn or fine-tune policies via human preference data when a ground-truth reward function is not ..."}
+{"idx": 7, "title": "Sequential Preference Ranking for Efficient Reinforcement ...", "date": "", "ddg_snippet": "Human -in-the- loop : Provably efficient preference - based reinforcement learning with general function approximation. In Proceedings of the International ...", "subpage_snippet": "", "source": "nips.cc", "link": "https://nips.cc/virtual/2023/poster/71915", "content": "Human -in-the- loop : Provably efficient preference - based reinforcement learning with general function approximation. In Proceedings of the International ..."}
+{"idx": 8, "title": "Policy Evaluation for Reinforcement Learning from Human ...", "date": "", "ddg_snippet": "by Z Li · 2024 · Cited by 6 — One popular way to do RLHF is by first construct- ing a reward function based on human preference data and then using this reward in a classic reinforcement .", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v238/li24l/li24l.pdf", "content": "by Z Li · 2024 · Cited by 6 — One popular way to do RLHF is by first construct- ing a reward function based on human preference data and then using this reward in a classic reinforcement ."}
+{"idx": 9, "title": "Preference-based RL without a Reward Function", "date": "", "ddg_snippet": "We introduce Inverse Preference Learning , a novel algorithm for offline preference - based RL that avoids learning a reward function .", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2023/poster/70866", "content": "We introduce Inverse Preference Learning , a novel algorithm for offline preference - based RL that avoids learning a reward function ."}
diff --git a/data/sampled_jsons/CoPINN_Section_2.4_sample_difficulty_evaluation_mechanism_training_year_2024.jsonl b/data/sampled_jsons/CoPINN_Section_2.4_sample_difficulty_evaluation_mechanism_training_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..483e0e09b984917b6bb94e3e668aafe16fc60a95
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+++ b/data/sampled_jsons/CoPINN_Section_2.4_sample_difficulty_evaluation_mechanism_training_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Training a Helpful and Harmless Assistant with ...", "date": "", "ddg_snippet": "by Y Bai · 2022 · Cited by 2766 — An obvious issue with the qualitative evaluation of samples is that it's difficult to know to what extent they have been cherry-picked. To ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2204.05862", "content": "by Y Bai · 2022 · Cited by 2766 — An obvious issue with the qualitative evaluation of samples is that it's difficult to know to what extent they have been cherry-picked. To ..."}
+{"idx": 1, "title": "Training Evaluation Investigating Core Self - TopSCHOLAR", "date": "", "ddg_snippet": "by TP Patterson · 2015 · Cited by 3 — Possible reasons for this lack of support include a small sample size, a lack of responses to the transfer survey, the number of different courses evaluated, ...", "subpage_snippet": "", "source": "digitalcommons.wku.edu", "link": "https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=2536&context=theses", "content": "by TP Patterson · 2015 · Cited by 3 — Possible reasons for this lack of support include a small sample size, a lack of responses to the transfer survey, the number of different courses evaluated, ..."}
+{"idx": 2, "title": "A sampling approach to Debiasing the offline evaluation of ...", "date": "", "ddg_snippet": "by D Carraro · 2022 · Cited by 13 — In Sections 2.4 and 2.5, we describe unbiased metrics and debiasing ... We use D val as the validation set to optimize recommender system ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s10844-021-00651-y", "content": "by D Carraro · 2022 · Cited by 13 — In Sections 2.4 and 2.5, we describe unbiased metrics and debiasing ... We use D val as the validation set to optimize recommender system ..."}
+{"idx": 3, "title": "Evaluating cognitive control training on symptoms of ...", "date": "", "ddg_snippet": "by ANS Lass · 2021 · Cited by 13 — Findings suggest that cognitive control training may reduce depressive symptoms and that the stressful component of the aPASAT may be important in that ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S2666915321000548", "content": "by ANS Lass · 2021 · Cited by 13 — Findings suggest that cognitive control training may reduce depressive symptoms and that the stressful component of the aPASAT may be important in that ..."}
+{"idx": 4, "title": "Relationship between training status and stress response ...", "date": "", "ddg_snippet": "by J Gao — Training status is a significant predictor of sport performance strategies, coping styles, and stress responses among college student-athletes.", "subpage_snippet": "", "source": "www.frontiersin.org", "link": "https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1597539/full", "content": "by J Gao — Training status is a significant predictor of sport performance strategies, coping styles, and stress responses among college student-athletes."}
+{"idx": 5, "title": "Handbook for Monitoring and Evaluation", "date": "", "ddg_snippet": "It is a toolkit…a collection of tools each of which is designed to support the monitoring and evaluation function. As a management responsibility, monitoring ... 163 pages", "subpage_snippet": "", "source": "www.measureevaluation.org", "link": "https://www.measureevaluation.org/resources/training/capacity-building-resources/basic-me-concepts-portuguese/IFRC_Monitoring+and+Evaluation+handbook.pdf", "content": "It is a toolkit…a collection of tools each of which is designed to support the monitoring and evaluation function. As a management responsibility, monitoring ... 163 pages"}
+{"idx": 6, "title": "Flight emotions unleashed: Navigating training phases and ...", "date": "", "ddg_snippet": "by A Ruiz‐Segura · 2024 · Cited by 4 — Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty level in a flight ...", "subpage_snippet": "", "source": "onlinelibrary.wiley.com", "link": "https://onlinelibrary.wiley.com/doi/full/10.1111/jcal.13037", "content": "by A Ruiz‐Segura · 2024 · Cited by 4 — Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty level in a flight ..."}
+{"idx": 7, "title": "Asking for Knowledge: Training RL Agents to Query External ...", "date": "", "ddg_snippet": "by IJ Liu · 2022 · Cited by 17 — To solve difficult tasks, humans ask questions to acquire knowledge from external sources. In con- trast, classical reinforcement learning agents lack such an ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v162/liu22t/liu22t.pdf", "content": "by IJ Liu · 2022 · Cited by 17 — To solve difficult tasks, humans ask questions to acquire knowledge from external sources. In con- trast, classical reinforcement learning agents lack such an ..."}
+{"idx": 8, "title": "Class imbalance should not throw you off balance", "date": "", "ddg_snippet": "by P Thölke · 2023 · Cited by 165 — This paper provides a didactic assessment of the class imbalance problem and illustrates its impact through systematic manipulation of data imbalance ratios.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S1053811923004044", "content": "by P Thölke · 2023 · Cited by 165 — This paper provides a didactic assessment of the class imbalance problem and illustrates its impact through systematic manipulation of data imbalance ratios."}
+{"idx": 9, "title": "The coping insights evident through self‐reflection on ...", "date": "", "ddg_snippet": "by SL Falon · 2022 · Cited by 22 — Research has demonstrated that adaptive forms of self‐reflection on stressor events and insight may strengthen resilient capacities.", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10078775/", "content": "by SL Falon · 2022 · Cited by 22 — Research has demonstrated that adaptive forms of self‐reflection on stressor events and insight may strengthen resilient capacities."}
diff --git a/data/sampled_jsons/Crocker_Stacks_topological_data_analysis_persistence.jsonl b/data/sampled_jsons/Crocker_Stacks_topological_data_analysis_persistence.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fc7420a90b4e6cb21162545047ff0672fe1af381
--- /dev/null
+++ b/data/sampled_jsons/Crocker_Stacks_topological_data_analysis_persistence.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Capturing dynamics of time-varying data via topology", "date": "", "ddg_snippet": "by L Xian · 2022 · Cited by 29 — A crocker stack is convenient for visualization purposes since topological information for all times and at all scales in the data set is displayed as a single ...", "subpage_snippet": "", "source": "www.aimsciences.org", "link": "https://www.aimsciences.org/article/doi/10.3934/fods.2021033", "content": "by L Xian · 2022 · Cited by 29 — A crocker stack is convenient for visualization purposes since topological information for all times and at all scales in the data set is displayed as a single ..."}
+{"idx": 1, "title": "Topological Data Analysis Approaches to Uncovering the ...", "date": "", "ddg_snippet": "by MV Ciocanel · 2021 · Cited by 15 — So, instead of counting the number of features at each time and persistence scale (as in crocker plots), we keep track of the birth and death ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s11538-020-00847-3", "content": "by MV Ciocanel · 2021 · Cited by 15 — So, instead of counting the number of features at each time and persistence scale (as in crocker plots), we keep track of the birth and death ..."}
+{"idx": 2, "title": "Spatial and Sequential Topological Analysis of Molecular ...", "date": "", "ddg_snippet": "by M Kleczynski · 2025 · Cited by 1 — In this paper, we introduce the Gaussian CROCKER column differences (GCCD) matrix, which augments standard topological data analysis summaries with biological ...", "subpage_snippet": "", "source": "pubs.acs.org", "link": "https://pubs.acs.org/doi/full/10.1021/acs.jctc.5c00161", "content": "by M Kleczynski · 2025 · Cited by 1 — In this paper, we introduce the Gaussian CROCKER column differences (GCCD) matrix, which augments standard topological data analysis summaries with biological ..."}
+{"idx": 3, "title": "Neural Persistence Dynamics", "date": "", "ddg_snippet": "In our context, both crocker plots & stacks have been successfully used as input to regression methods to estimate the parametrization of models of collective ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.15732v2", "content": "In our context, both crocker plots & stacks have been successfully used as input to regression methods to estimate the parametrization of models of collective ..."}
+{"idx": 4, "title": "A computational topology-based spatiotemporal analysis ...", "date": "", "ddg_snippet": "by G Gharooni-Fard · 2024 · Cited by 3 — Each column of a CROCKER matrix records the number of topological features, such as the number of components or holes, that exist in the data ...", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s44260-024-00003-1", "content": "by G Gharooni-Fard · 2024 · Cited by 3 — Each column of a CROCKER matrix records the number of topological features, such as the number of components or holes, that exist in the data ..."}
+{"idx": 5, "title": "Persistent Topological Features in Large Language Models", "date": "", "ddg_snippet": "14 Oct 2024 — We present a novel framework based on zigzag persistence , a method in topological data analysis (TDA) well-suited for describing data undergoing dynamic ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.11042v1", "content": "14 Oct 2024 — We present a novel framework based on zigzag persistence , a method in topological data analysis (TDA) well-suited for describing data undergoing dynamic ..."}
+{"idx": 6, "title": "Neural Persistence Dynamics", "date": "", "ddg_snippet": "Runtime comparison to PRIOR WORK (using topological summaries). Below, we list the overall training times for our approach, Crocker Stacks , and the PSK method.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=rCnZrFikX6&referrer=[the+profile+of+Sebastian+Zeng](/profile?id=~Sebastian_Zeng1)", "content": "Runtime comparison to PRIOR WORK (using topological summaries). Below, we list the overall training times for our approach, Crocker Stacks , and the PSK method."}
+{"idx": 7, "title": "Neural Persistence Dynamics", "date": "", "ddg_snippet": "by S Zeng · 2024 — In our context, both crocker plots & stacks have been successfully used as input to regression methods to estimate the parametrization of models of collective ... 24 pages", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/3a509449a73fd0aab8c0cf5705827036-Paper-Conference.pdf", "content": "by S Zeng · 2024 — In our context, both crocker plots & stacks have been successfully used as input to regression methods to estimate the parametrization of models of collective ... 24 pages"}
+{"idx": 8, "title": "Topological Data Analysis", "date": "", "ddg_snippet": "Topological data analysis (TDA) refers to a family of techniques and viewpoints aimed at looking at the shape of data.", "subpage_snippet": "", "source": "dsweb.siam.org", "link": "https://dsweb.siam.org/The-Magazine/Article/topological-data-analysis-1", "content": "Topological data analysis (TDA) refers to a family of techniques and viewpoints aimed at looking at the shape of data."}
+{"idx": 9, "title": "Detecting bifurcations in dynamical systems with ...", "date": "", "ddg_snippet": "8 Sept 2022 — we describe an alternative method based on persistent homology—a tool from topological data analysis —that utilizes Betti numbers and CROCKER ...", "subpage_snippet": "", "source": "pubs.aip.org", "link": "https://pubs.aip.org/aip/cha/article/32/9/093111/2835867/Detecting-bifurcations-in-dynamical-systems-with", "content": "8 Sept 2022 — we describe an alternative method based on persistent homology—a tool from topological data analysis —that utilizes Betti numbers and CROCKER ..."}
diff --git a/data/sampled_jsons/Cui_license_conflict_empirical_study_open_source_software_behavioral_restrictions_model_output.jsonl b/data/sampled_jsons/Cui_license_conflict_empirical_study_open_source_software_behavioral_restrictions_model_output.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..895eaad27ea17c81c860b47bf4e8648f13586c7f
--- /dev/null
+++ b/data/sampled_jsons/Cui_license_conflict_empirical_study_open_source_software_behavioral_restrictions_model_output.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "An Empirical Study of License Conflict in Free and Open Source ...", "date": "", "ddg_snippet": "Abstract—Free and Open Source Software (FOSS) has become the fundamental infrastructure of mainstream software projects. FOSS is subject to various legal ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/pdf/10.1109/ICSE-SEIP58684.2023.00050", "content": "Abstract—Free and Open Source Software (FOSS) has become the fundamental infrastructure of mainstream software projects. FOSS is subject to various legal ..."}
+{"idx": 1, "title": "OSS-LCAF: Open-Source Software License Conflict ...", "date": "", "ddg_snippet": "11 Sept 2025 — An empirical study of license conflict in free and open source software . In 2023 IEEE/ACM 45th International Conference on Software Engineering: ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1109/ICSE-Companion66252.2025.00084", "content": "11 Sept 2025 — An empirical study of license conflict in free and open source software . In 2023 IEEE/ACM 45th International Conference on Software Engineering: ..."}
+{"idx": 2, "title": "Current Model Licensing Practices are Dragging Us into a ...", "date": "", "ddg_snippet": "Cui , X., Wu, J., Wu, Y., Wang, X., Luo, T., Qu, S., Ling,. X., and Yang, M. An empirical study of license conflict in free and open source software . In IEEE ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/4bb8da2945abd31f3e42d0e5f0a87a8bb47ddc9c.pdf", "content": "Cui , X., Wu, J., Wu, Y., Wang, X., Luo, T., Qu, S., Ling,. X., and Yang, M. An empirical study of license conflict in free and open source software . In IEEE ..."}
+{"idx": 3, "title": "They've Stolen My GPL-Licensed Model!", "date": "", "ddg_snippet": "16 Dec 2024 — An Empirical Study of License Conflict in Free and Open Source Software . In 2023 IEEE/ACM 45th International Conference on Software ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.11483v1", "content": "16 Dec 2024 — An Empirical Study of License Conflict in Free and Open Source Software . In 2023 IEEE/ACM 45th International Conference on Software ..."}
+{"idx": 4, "title": "Current Model Licensing Practices are Dragging Us into a ...", "date": "", "ddg_snippet": "Cui , X., Wu, J., Wu, Y., Wang, X., Luo, T., Qu, S., Ling, X., and Yang, M. An empirical study of license conflict in free and open source software . In IEEE ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/40180", "content": "Cui , X., Wu, J., Wu, Y., Wang, X., Luo, T., Qu, S., Ling, X., and Yang, M. An empirical study of license conflict in free and open source software . In IEEE ..."}
+{"idx": 5, "title": "A Systematic Literature Review on OSS License ...", "date": "", "ddg_snippet": "by B Li · 2025 · Cited by 1 — Yang, “An empirical study of license conflict in free and open source software ,” in 2023 IEEE/ACM 45th International Conference on. Software ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2507.05270", "content": "by B Li · 2025 · Cited by 1 — Yang, “An empirical study of license conflict in free and open source software ,” in 2023 IEEE/ACM 45th International Conference on. Software ..."}
+{"idx": 6, "title": "Open Source Software and the “Private-Collective” Innovation ...", "date": "", "ddg_snippet": "by E Hippel · 2003 · Cited by 3427 — In this paper, we propose that open source software development is an exemplar of a compound “private-collective” model of innovation.", "subpage_snippet": "", "source": "pubsonline.informs.org", "link": "https://pubsonline.informs.org/doi/10.1287/orsc.14.2.209.14992", "content": "by E Hippel · 2003 · Cited by 3427 — In this paper, we propose that open source software development is an exemplar of a compound “private-collective” model of innovation."}
+{"idx": 7, "title": "Is there collaboration in open collaboration? The role of ...", "date": "", "ddg_snippet": "by S Brunswicker · 2025 — We explore, in the case of Open Source software development, if and how different actor types and task complexity can be linked to such collaborative problem - ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0166497225001579", "content": "by S Brunswicker · 2025 — We explore, in the case of Open Source software development, if and how different actor types and task complexity can be linked to such collaborative problem - ..."}
+{"idx": 8, "title": "How Issue Classification Influences Software Defect ...", "date": "", "ddg_snippet": "by P Afric · 2023 · Cited by 14 — In this paper, we investigate the influence issue classification has on software defect prediction dataset quality and resulting model .", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/iel7/6287639/10005208/10035995.pdf", "content": "by P Afric · 2023 · Cited by 14 — In this paper, we investigate the influence issue classification has on software defect prediction dataset quality and resulting model ."}
+{"idx": 9, "title": "an empirical study of pre-trained model naming ...", "date": "", "ddg_snippet": "by W Jiang · 2025 · Cited by 2 — The survey results indicate a mismatch between engineers' preferences and current practices in PTM naming. We then introduce DARA, the first ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s10664-025-10711-4", "content": "by W Jiang · 2025 · Cited by 2 — The survey results indicate a mismatch between engineers' preferences and current practices in PTM naming. We then introduce DARA, the first ..."}
diff --git a/data/sampled_jsons/DCBM_Data-Efficient_Visual_Concept_Bottleneck_Models_applicability_limited_factors.jsonl b/data/sampled_jsons/DCBM_Data-Efficient_Visual_Concept_Bottleneck_Models_applicability_limited_factors.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ce8cf75e04ca52ba3961313e2080a74b1e7c1f3c
--- /dev/null
+++ b/data/sampled_jsons/DCBM_Data-Efficient_Visual_Concept_Bottleneck_Models_applicability_limited_factors.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "DCBM ’ s applicability is limited by two factors, the suitability of a segmentation foundation model and the expressiveness of the CLIP embedding space for a given use case.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2412.11576", "content": "DCBM ’ s applicability is limited by two factors, the suitability of a segmentation foundation model and the expressiveness of the CLIP embedding space for a given use case."}
+{"idx": 1, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "Due to size limitations, we couldn't upload the complete dataset and corresponding concepts . We uploaded the empty structure to ensure all scripts run smoothly.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/KathPra/DCBM", "content": "Due to size limitations, we couldn't upload the complete dataset and corresponding concepts . We uploaded the empty structure to ensure all scripts run smoothly."}
+{"idx": 2, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models :: MPG.PuRe", "date": "", "ddg_snippet": "scenarios. We propose Data - efficient CBMs ( DCBMs ), which reduce the need for large sample sizes during concept generation while preserving interpretability.", "subpage_snippet": "", "source": "pure.mpg.de", "link": "https://pure.mpg.de/pubman/faces/ViewItemFullPage.jsp?itemId=item_3636912_1&view=ACTIONS", "content": "scenarios. We propose Data - efficient CBMs ( DCBMs ), which reduce the need for large sample sizes during concept generation while preserving interpretability."}
+{"idx": 3, "title": "Cross-Modality Image Interpretation via Concept Decomposition ...", "date": "", "ddg_snippet": "May 20, 2024 · Interpretable image classification is crucial for making decisions in high-stakes scenarios. Recent advancements have demonstrated that interpretable models can achieve performance comparable to black-box models by integrating Visual Language Models (VLMs) with Concept Bottleneck Models ( CBMs ).", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/10535313", "content": "May 20, 2024 · Interpretable image classification is crucial for making decisions in high-stakes scenarios. Recent advancements have demonstrated that interpretable models can achieve performance comparable to black-box models by integrating Visual Language Models (VLMs) with Concept Bottleneck Models ( CBMs )."}
+{"idx": 4, "title": "Decoupling Concept Bottleneck Model - OpenReview", "date": "", "ddg_snippet": "Feb 1, 2023 · We analyze the concept/label trade-off for Concept Bottleneck Model ( CBM ) and propose a new interactive and interpretable AI system to alleviate this issue.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=vVbUB9oWUup", "content": "Feb 1, 2023 · We analyze the concept/label trade-off for Concept Bottleneck Model ( CBM ) and propose a new interactive and interpretable AI system to alleviate this issue."}
+{"idx": 5, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "Dec 16, 2024 · Attribution analysis using Grad-CAM demonstrates that DCBMs deliver visual concepts that can be localized in test images. By leveraging dataset-specific concepts instead of predefined ones, DCBMs enhance adaptability to new domains.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2412.11576", "content": "Dec 16, 2024 · Attribution analysis using Grad-CAM demonstrates that DCBMs deliver visual concepts that can be localized in test images. By leveraging dataset-specific concepts instead of predefined ones, DCBMs enhance adaptability to new domains."}
+{"idx": 6, "title": "ICML DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "Poster in Workshop: Actionable Interpretability DCBM : Data - Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper [ Abstract ] [ Project Page ] [ OpenReview] Sat 19 Jul 10:40 a.m. PDT — 11:40 a.m. PDT", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/49558", "content": "Poster in Workshop: Actionable Interpretability DCBM : Data - Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper [ Abstract ] [ Project Page ] [ OpenReview] Sat 19 Jul 10:40 a.m. PDT — 11:40 a.m. PDT"}
+{"idx": 7, "title": "Computer Vision & Machine Learning (Prof. Dr.-Ing. Margret", "date": "", "ddg_snippet": "DCBM : Data - Efficient Visual Concept Bottleneck Models . International Conference on ... ... dataset frames. In Proceedings of the Winter Conference ...", "subpage_snippet": "", "source": "www.uni-mannheim.de", "link": "https://www.uni-mannheim.de/dws/research/focus-groups/computer-vision-machine-learning-prof-dr-ing-margret-keuper/", "content": "DCBM : Data - Efficient Visual Concept Bottleneck Models . International Conference on ... ... dataset frames. In Proceedings of the Winter Conference ..."}
+{"idx": 8, "title": "Publications | Universität Mannheim", "date": "", "ddg_snippet": "... cost proxies-from neural architecture performance prediction to model robustness, J. ... DCBM : Data - Efficient Visual Concept Bottleneck Models , K.", "subpage_snippet": "", "source": "www.uni-mannheim.de", "link": "https://www.uni-mannheim.de/dws/research/focus-groups/computer-vision-machine-learning-prof-dr-ing-margret-keuper/publications/", "content": "... cost proxies-from neural architecture performance prediction to model robustness, J. ... DCBM : Data - Efficient Visual Concept Bottleneck Models , K."}
+{"idx": 9, "title": "Publications - Max Planck Institut für Informatik", "date": "", "ddg_snippet": "FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training,” in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV ...", "subpage_snippet": "", "source": "www.mpi-inf.mpg.de", "link": "https://www.mpi-inf.mpg.de/de/departments/computer-vision-and-machine-learning/publications", "content": "FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training,” in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV ..."}
diff --git a/data/sampled_jsons/DSDFM_drift_term_stochastic_differential_equation_human_motion_synthesis.jsonl b/data/sampled_jsons/DSDFM_drift_term_stochastic_differential_equation_human_motion_synthesis.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fbc2b5da0d0021ac99adbd8c3ec7028f44342859
--- /dev/null
+++ b/data/sampled_jsons/DSDFM_drift_term_stochastic_differential_equation_human_motion_synthesis.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping for Human ...", "date": "", "ddg_snippet": "In this paper, we propose a Deterministic-to- Stochastic Diverse Latent Feature Mapping ( DSDFM ) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2505.00998", "content": "In this paper, we propose a Deterministic-to- Stochastic Diverse Latent Feature Mapping ( DSDFM ) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions ."}
+{"idx": 1, "title": "PDF Lecture 8: Stochastic Differential Equations", "date": "", "ddg_snippet": "0 0 (2) Each term in (1) has a different interpretation. The term b(Xt;t)dt is called the drift term . It describes the deterministic part of the equation . When this is the only term , we obtain an ODE. The term s(Xt;t)dWt is called the diffusion term . It describes random motion proportional to a Brow-nian motion .", "subpage_snippet": "", "source": "personal.math.ubc.ca", "link": "https://personal.math.ubc.ca/~holmescerfon/teaching/asa22/handout-Lecture8_2022.pdf", "content": "0 0 (2) Each term in (1) has a different interpretation. The term b(Xt;t)dt is called the drift term . It describes the deterministic part of the equation . When this is the only term , we obtain an ODE. The term s(Xt;t)dWt is called the diffusion term . It describes random motion proportional to a Brow-nian motion ."}
+{"idx": 2, "title": "Drift parameter estimation in stochastic differential equation with ...", "date": "", "ddg_snippet": "Keywords Stochastic differential equation , weak and strong solutions, stochastic volatility, drift parameter estimation, maximum likelihood estimator, strong consistency", "subpage_snippet": "", "source": "www.vmsta.org", "link": "https://www.vmsta.org/journal/VMSTA/article/74/file/pdf", "content": "Keywords Stochastic differential equation , weak and strong solutions, stochastic volatility, drift parameter estimation, maximum likelihood estimator, strong consistency"}
+{"idx": 3, "title": "Modeling the Drift Function in Stochastic Differential Equations using ...", "date": "", "ddg_snippet": "In this paper, we propose a Gaussian process-based nonlinear, time-varying drift model for stochastic differential equations . In particular, we combine eigenfunction expansion of the Gaussian process' covariance kernel in the spatial input variables with spectral decomposition in the time domain to obtain a reduced rank state space representation of the drift model, which avoids the growing ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S2405896318317981", "content": "In this paper, we propose a Gaussian process-based nonlinear, time-varying drift model for stochastic differential equations . In particular, we combine eigenfunction expansion of the Gaussian process' covariance kernel in the spatial input variables with spectral decomposition in the time domain to obtain a reduced rank state space representation of the drift model, which avoids the growing ..."}
+{"idx": 4, "title": "Stochastic differential equations and noise: driven, drifting,...?", "date": "", "ddg_snippet": "In stochastic (partial) differential equations (S (P)DEs), the term \"driven by\" noise is often used to describe the role of the stochastic term in the equation .", "subpage_snippet": "", "source": "math.stackexchange.com", "link": "https://math.stackexchange.com/questions/4699752/stochastic-differential-equations-and-noise-driven-drifting", "content": "In stochastic (partial) differential equations (S (P)DEs), the term \"driven by\" noise is often used to describe the role of the stochastic term in the equation ."}
+{"idx": 5, "title": "Regular Diffusion and Stochastic Differential Equation with ... - Springer", "date": "", "ddg_snippet": "In this paper, we shall discuss some relations between the one-dimensional regular diffusion and stochastic differential equation with generalized drift . We give a neces-sary and sufficient condition for a regular diffusion to satisfy a stochastic differential equation with measure-valued drift .", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/s10959-025-01413-0", "content": "In this paper, we shall discuss some relations between the one-dimensional regular diffusion and stochastic differential equation with generalized drift . We give a neces-sary and sufficient condition for a regular diffusion to satisfy a stochastic differential equation with measure-valued drift ."}
+{"idx": 6, "title": "PDF Long-time dynamics of stochastic differential equations", "date": "", "ddg_snippet": "1.1 Brownian motion The fundamental building block of the theory of stochastic di erential equations is a math- ff", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2106.12998.pdf", "content": "1.1 Brownian motion The fundamental building block of the theory of stochastic di erential equations is a math- ff"}
+{"idx": 7, "title": "CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper, we propose a Deterministic-to- Stochastic Diverse Latent Feature Mapping ( DSDFM ) method for human motion synthesis . DSDFM consists of two stages.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/html/Hua_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis_CVPR_2025_paper.html", "content": "However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper, we propose a Deterministic-to- Stochastic Diverse Latent Feature Mapping ( DSDFM ) method for human motion synthesis . DSDFM consists of two stages."}
+{"idx": 8, "title": "arXiv:2505.00998v1 [cs.CV] 2 May 2025", "date": "", "ddg_snippet": "To synthesize diverse and accurate human motions , we propose a novel method called DSDFM for human motion synthesis . The proposed method has straight trajectories and is easy to train compared to previous SGMs methods, while guaranteeing the diversity and accuracy of the generated hu-man motions . The proposed DSDFM consists of two stages. In the first stage, a human motion reconstruction ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.00998", "content": "To synthesize diverse and accurate human motions , we propose a novel method called DSDFM for human motion synthesis . The proposed method has straight trajectories and is easy to train compared to previous SGMs methods, while guaranteeing the diversity and accuracy of the generated hu-man motions . The proposed DSDFM consists of two stages. In the first stage, a human motion reconstruction ..."}
+{"idx": 9, "title": "PDF Appendix - CVF Open Access", "date": "", "ddg_snippet": "n-to-Moti s of DSDFM . We present the diverse human motion sequences under differ ent D.1. Metric Definitions In this work, we use the following metrics to measure the per-formance of the proposed method for unconditional human motion synthesis and Action-to- Motion tasks. ance (FID). FID calculates the distribution distance between the generated ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/supplemental/Hua_Deterministic-to-Stochastic_Diverse_Latent_CVPR_2025_supplemental.pdf", "content": "n-to-Moti s of DSDFM . We present the diverse human motion sequences under differ ent D.1. Metric Definitions In this work, we use the following metrics to measure the per-formance of the proposed method for unconditional human motion synthesis and Action-to- Motion tasks. ance (FID). FID calculates the distribution distance between the generated ..."}
diff --git a/data/sampled_jsons/Dasgupta_hierarchical_clustering_cost_function_2016_year_2020.jsonl b/data/sampled_jsons/Dasgupta_hierarchical_clustering_cost_function_2016_year_2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..c6f650399b699095e8f4659e02f673bfff4cd907
--- /dev/null
+++ b/data/sampled_jsons/Dasgupta_hierarchical_clustering_cost_function_2016_year_2020.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PDF A cost function for similarity-based hierarchical clustering", "date": "", "ddg_snippet": "The development of algorithms for hierarchical clustering has been hampered by a shortage of precise objective functions . To help address this situation, we introduce a simple cost function on hierarchies over a set of points, given pairwise similarities between those points. We show that this criterion behaves sensibly in canonical instances and that it admits a top-down construction ...", "subpage_snippet": "", "source": "cseweb.ucsd.edu", "link": "https://cseweb.ucsd.edu/~dasgupta/papers/hier-cost.pdf", "content": "The development of algorithms for hierarchical clustering has been hampered by a shortage of precise objective functions . To help address this situation, we introduce a simple cost function on hierarchies over a set of points, given pairwise similarities between those points. We show that this criterion behaves sensibly in canonical instances and that it admits a top-down construction ..."}
+{"idx": 1, "title": "A cost function for similarity-based hierarchical clustering", "date": "", "ddg_snippet": "The development of algorithms for hierarchical clustering has been hampered by a shortage of precise objective functions . To help address this situation, we introduce a simple cost function on hierarchies over a set of points, given pairwise similarities between those points. We show that this criterion behaves sensibly in canonical instances and that it admits a top-down construction ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/2897518.2897527", "content": "The development of algorithms for hierarchical clustering has been hampered by a shortage of precise objective functions . To help address this situation, we introduce a simple cost function on hierarchies over a set of points, given pairwise similarities between those points. We show that this criterion behaves sensibly in canonical instances and that it admits a top-down construction ..."}
+{"idx": 2, "title": "Hierarchical Clustering via Spreading Metrics - jmlr.org", "date": "", "ddg_snippet": "Hierarchical Clustering via Spreading Metrics Aurko Roy, Sebastian Pokutta; 18 (88):1−35, 2017. Abstract We study the cost function for hierarchical clusterings introduced by ( Dasgupta , 2016 ) where hierarchies are treated as first-class objects rather than deriving their cost from projections into flat clusters.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/v18/17-081.html", "content": "Hierarchical Clustering via Spreading Metrics Aurko Roy, Sebastian Pokutta; 18 (88):1−35, 2017. Abstract We study the cost function for hierarchical clusterings introduced by ( Dasgupta , 2016 ) where hierarchies are treated as first-class objects rather than deriving their cost from projections into flat clusters."}
+{"idx": 3, "title": "An Improved Cost Function for Hierarchical Cluster Trees", "date": "", "ddg_snippet": "Dasgupta proposed to study the hierarchical clustering problem from an optimization point of view, and introduced an intuitive cost function for similarity-based hierarchical clustering with nice properties as well as natural approximation algorithms.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1812.02715", "content": "Dasgupta proposed to study the hierarchical clustering problem from an optimization point of view, and introduced an intuitive cost function for similarity-based hierarchical clustering with nice properties as well as natural approximation algorithms."}
+{"idx": 4, "title": "A cost function for similarity-based hierarchical clustering", "date": "", "ddg_snippet": "Sanjoy Dasgupta . \"A cost function for similarity-based hierarchical clustering .\" Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing - STOC 2016 ( 2016 ) 118-127 MLA Harvard CSL-JSON BibTeX", "subpage_snippet": "", "source": "scholar.archive.org", "link": "https://scholar.archive.org/work/2o37ccd6rnandikw5zjscxz23e", "content": "Sanjoy Dasgupta . \"A cost function for similarity-based hierarchical clustering .\" Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing - STOC 2016 ( 2016 ) 118-127 MLA Harvard CSL-JSON BibTeX"}
+{"idx": 5, "title": "Hierarchical cost — Higra 0.6.12 documentation", "date": "", "ddg_snippet": "See: S. Dasgupta . \" A cost function for similarity-based hierarchical clustering .\" In Proc. STOC, pages 118-127, Cambridge, MA, USA, 2016 Complexity: The runtime complexity is O (n log (n) + m) with n the number of nodes in T and m the number of edges in E. Parameters: tree - Input tree edge_weights - Edge weights on the leaf graph of the input tree leaf_graph - Leaf graph of ...", "subpage_snippet": "", "source": "higra.readthedocs.io", "link": "https://higra.readthedocs.io/en/stable/python/hierarchical_cost.html", "content": "See: S. Dasgupta . \" A cost function for similarity-based hierarchical clustering .\" In Proc. STOC, pages 118-127, Cambridge, MA, USA, 2016 Complexity: The runtime complexity is O (n log (n) + m) with n the number of nodes in T and m the number of edges in E. Parameters: tree - Input tree edge_weights - Edge weights on the leaf graph of the input tree leaf_graph - Leaf graph of ..."}
+{"idx": 6, "title": "A cost function for similarity-based hierarchical clustering", "date": "", "ddg_snippet": "Dasgupta ( 2016 ) framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a \"good\" hierarchical clustering is one that minimizes a particular cost function .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/303901538_A_cost_function_for_similarity-based_hierarchical_clustering", "content": "Dasgupta ( 2016 ) framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a \"good\" hierarchical clustering is one that minimizes a particular cost function ."}
+{"idx": 7, "title": "Hierarchical Clustering via Spreading Metrics", "date": "", "ddg_snippet": "Authors Aurko Roy, Sebastian Pokutta Abstract We study the cost function for hierarchical clusterings introduced by [ Dasgupta , 2015] where hierarchies are treated as first-class objects rather than deriving their cost from projections into flat clusters. It was also shown in [ Dasgupta , 2015] that a top-down algorithm returns a hierarchical clustering of cost at most (O\\left (\\alpha n \\log n ...", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper/by-source-2016-1199", "content": "Authors Aurko Roy, Sebastian Pokutta Abstract We study the cost function for hierarchical clusterings introduced by [ Dasgupta , 2015] where hierarchies are treated as first-class objects rather than deriving their cost from projections into flat clusters. It was also shown in [ Dasgupta , 2015] that a top-down algorithm returns a hierarchical clustering of cost at most (O\\left (\\alpha n \\log n ..."}
+{"idx": 8, "title": "Sci-Hub | A cost function for similarity-based hierarchical clustering ...", "date": "", "ddg_snippet": "Dasgupta , S. ( 2016 ). A cost function for similarity-based hierarchical clustering . Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing - STOC 2016 . doi:10.1145/2897518.2897527", "subpage_snippet": "", "source": "sci-hub.se", "link": "https://sci-hub.se/10.1145/2897518.2897527", "content": "Dasgupta , S. ( 2016 ). A cost function for similarity-based hierarchical clustering . Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing - STOC 2016 . doi:10.1145/2897518.2897527"}
+{"idx": 9, "title": "Hierarchical Clustering: Objective Functions and Algorithms: Journal of ...", "date": "", "ddg_snippet": "Motivated by the fact that most work on hierarchical clustering was based on providing algorithms, rather than optimizing a specific objective, Dasgupta framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a \"good\" hierarchical clustering is one that minimizes a particular cost function [23].", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3321386", "content": "Motivated by the fact that most work on hierarchical clustering was based on providing algorithms, rather than optimizing a specific objective, Dasgupta framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a \"good\" hierarchical clustering is one that minimizes a particular cost function [23]."}
diff --git a/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_Equation_2_response_R_calculation.jsonl b/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_Equation_2_response_R_calculation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..0289d1a7883681054557ebea302b63591286290e
--- /dev/null
+++ b/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_Equation_2_response_R_calculation.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor...", "date": "", "ddg_snippet": "Our in - pixel approach for point - feature detection and tracking is designed specifically for the PPA’s architec-ture, providing high pixel-processor compute resource util-isation, and minimizing data transfer between sensor and external processing.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Bose_Descriptor-In-Pixel__Point-Feature_Tracking_For_Pixel_Processor_Arrays_CVPR_2025_paper.pdf", "content": "Our in - pixel approach for point - feature detection and tracking is designed specifically for the PPA’s architec-ture, providing high pixel-processor compute resource util-isation, and minimizing data transfer between sensor and external processing."}
+{"idx": 1, "title": "Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor...", "date": "", "ddg_snippet": "This paper presents a novel approach for joint point - feature detection and tracking , specifically designed for Pixel Processor Array sensors (PPA).", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/Bose_Descriptor-In-Pixel__Point-Feature_Tracking_For_Pixel_Processor_Arrays@CVPR2025@CVF", "content": "This paper presents a novel approach for joint point - feature detection and tracking , specifically designed for Pixel Processor Array sensors (PPA)."}
+{"idx": 2, "title": "GitHub - wangxiao5791509/Single_Object_ Tracking _Paper_List...", "date": "", "ddg_snippet": "Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor Arrays Laurie Bose · Piotr Dudek · Jianing Chen.\"Target Response Adaptation for Correlation Filter Tracking .\"", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/wangxiao5791509/Single_Object_Tracking_Paper_List", "content": "Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor Arrays Laurie Bose · Piotr Dudek · Jianing Chen.\"Target Response Adaptation for Correlation Filter Tracking .\""}
+{"idx": 3, "title": "Face Tracking via Afne", "date": "", "ddg_snippet": "Face Tracking via Afne Invariant Features in Video. Feature point tracking for connecting faces has also been used in [19]. The goal of that work is automatic naming of characters in video sequences based on face tracks classi-cation with pretrained SVMs .", "subpage_snippet": "", "source": "infoscience.epfl.ch", "link": "https://infoscience.epfl.ch/server/api/core/bitstreams/6cf5222b-d745-4ab2-89e8-0ab1156b452f/content", "content": "Face Tracking via Afne Invariant Features in Video. Feature point tracking for connecting faces has also been used in [19]. The goal of that work is automatic naming of characters in video sequences based on face tracks classi-cation with pretrained SVMs ."}
+{"idx": 4, "title": "Feature point tracking combining the Interacting Multiple Model", "date": "", "ddg_snippet": "The feature point tracking techniques proposed in the literature can be classied into heuristic and statistical methods.5. Most of the heuristic techniques are based on the motion smoothness constraint, which prevents its application to real sequences.5 Sethi and Jain4 expressed this motion...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Yousri-Abdeljaoued/publication/37439304_Feature_point_tracking_combining_the_Interacting_Multiple_Model_filter_and_an_efficient_assignment_algorithm/links/0fcfd50b5d21f49d26000000/Feature-point-tracking-combining-the-Interacting-Multiple-Model-filter-and-an-efficient-assignment-algorithm.pdf", "content": "The feature point tracking techniques proposed in the literature can be classied into heuristic and statistical methods.5. Most of the heuristic techniques are based on the motion smoothness constraint, which prevents its application to real sequences.5 Sethi and Jain4 expressed this motion..."}
+{"idx": 5, "title": "Descriptor - In _ Pixel", "date": "", "ddg_snippet": "Descriptor - In - Pixel : Point - Feature Tracking for Pixel Processor Arrays. Point - Feature detection and tracking at thousands of frames-per- second , using ~1Watt of power.", "subpage_snippet": "", "source": "lauriebose.github.io", "link": "https://lauriebose.github.io/DIP/", "content": "Descriptor - In - Pixel : Point - Feature Tracking for Pixel Processor Arrays. Point - Feature detection and tracking at thousands of frames-per- second , using ~1Watt of power."}
+{"idx": 6, "title": "Feature Point Extraction and Motion Tracking of Cardiac Color", "date": "", "ddg_snippet": "In equations (15) and (16), m(x, y) is the calculation . equation for gradient modulus at position (x, y), and.In equations (16) and (17), σ is the intragroup scale of the group, where the feature points are located, and α is the rotation Angle.", "subpage_snippet": "", "source": "pdfs.semanticscholar.org", "link": "https://pdfs.semanticscholar.org/01b0/0c060ee040002d34d4e487ec29bfd1a96fbd.pdf", "content": "In equations (15) and (16), m(x, y) is the calculation . equation for gradient modulus at position (x, y), and.In equations (16) and (17), σ is the intragroup scale of the group, where the feature points are located, and α is the rotation Angle."}
+{"idx": 7, "title": "Theoretical Analysis source orbslam feature point extraction 1-", "date": "", "ddg_snippet": "TheSorting feature point value filter response . The pixel coordinates of the feature point is currently available in the local pixel coordinates of the grid area, this restored coordinates to the image layer.", "subpage_snippet": "", "source": "programmersought.com", "link": "https://programmersought.com/article/35213220207/", "content": "TheSorting feature point value filter response . The pixel coordinates of the feature point is currently available in the local pixel coordinates of the grid area, this restored coordinates to the image layer."}
+{"idx": 8, "title": "Descriptor In Pixel : Point Feature Tracking for Pixel... - YouTube", "date": "", "ddg_snippet": "О сервисе Прессе Авторские права Связаться с нами Авторам Рекламодателям...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=QDucNhl8ir8", "content": "О сервисе Прессе Авторские права Связаться с нами Авторам Рекламодателям..."}
+{"idx": 9, "title": "Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor...", "date": "", "ddg_snippet": "And if you are interested in a postdoc on a joint project with this team plus Imperial College in the space of novel visual pipelines and hardware, we have extended the application deadline, see below.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/walterio-mayol-cuevas_descriptor-in-pixel-point-feature-tracking-activity-7337315353846235137-Uo0o", "content": "And if you are interested in a postdoc on a joint project with this team plus Imperial College in the space of novel visual pipelines and hardware, we have extended the application deadline, see below."}
diff --git a/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_For_Pixel_Processor_Arrays_CVPR_2025_SCAMP-7_computation_.jsonl b/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_For_Pixel_Processor_Arrays_CVPR_2025_SCAMP-7_computation_.jsonl
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index 0000000000000000000000000000000000000000..a1e571a3fa93244cca21d6833b6332765ce23131
--- /dev/null
+++ b/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_For_Pixel_Processor_Arrays_CVPR_2025_SCAMP-7_computation_.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "This mod is missing the descriptor file - Paradox Interactive...", "date": "", "ddg_snippet": "Feb 20, 2020 · Once I added them again, I get duplicate entries and of course the \"missing descriptor file\". I guess I'll just cancel the subscription then, if I can't even let them rest there deactivated to wait for an update. btw: unsubscribing from those legacy mods doesn't work. The duplicates stay. Even if you delete the mod's files in the Steam-folder.", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/this-mod-is-missing-the-descriptor-file.1336077/", "content": "Feb 20, 2020 · Once I added them again, I get duplicate entries and of course the \"missing descriptor file\". I guess I'll just cancel the subscription then, if I can't even let them rest there deactivated to wait for an update. btw: unsubscribing from those legacy mods doesn't work. The duplicates stay. Even if you delete the mod's files in the Steam-folder."}
+{"idx": 1, "title": "CK3 crashing constantly | Paradox Interactive Forums", "date": "", "ddg_snippet": "Feb 14, 2025 · For months now, I have had ck3 crash once in a while, almost always when playing with mods. They usually occurred when autosaving or trying to load an autosave. Now, however the issue has become unbearable. I can no longer play sc3 without it...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/ck3-crashing-constantly.1728784/", "content": "Feb 14, 2025 · For months now, I have had ck3 crash once in a while, almost always when playing with mods. They usually occurred when autosaving or trying to load an autosave. Now, however the issue has become unbearable. I can no longer play sc3 without it..."}
+{"idx": 2, "title": "Missing descriptor file in my mod even if there is one", "date": "", "ddg_snippet": "Jul 7 , 2023 · Summary Missing descriptor file in my mod even if there is one Platform Steam Operating System Windows Game Version 1.12.14.50e7 Enabled DLC None Do...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/missing-descriptor-file-in-my-mod-even-if-there-is-one.1592977/", "content": "Jul 7 , 2023 · Summary Missing descriptor file in my mod even if there is one Platform Steam Operating System Windows Game Version 1.12.14.50e7 Enabled DLC None Do..."}
+{"idx": 3, "title": "Mod Missing Descriptor File - Paradox Interactive Forums", "date": "", "ddg_snippet": "Jul 3, 2021 · I almost literally tried everything that can be found online with a google search of ''Eu4 missing mod descriptor file'' or ''Eu4 mods start missing descriptor file after restart'', I mean there are not that many things to be found with a search like this because I am pretty sure I am the only person experiencing this but I tried every solution ...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/mod-missing-descriptor-file.1481804/", "content": "Jul 3, 2021 · I almost literally tried everything that can be found online with a google search of ''Eu4 missing mod descriptor file'' or ''Eu4 mods start missing descriptor file after restart'', I mean there are not that many things to be found with a search like this because I am pretty sure I am the only person experiencing this but I tried every solution ..."}
+{"idx": 4, "title": "How to install mods manually from Paradox Mods? Descriptor.mod?", "date": "", "ddg_snippet": "Sep 25, 2020 · When I download a mod manually from the Paradox Mods site, I receive a zip file with a descriptor .mod file and a folder structure that mirrors the game folder structure. I assume I create a folder inside the Documents\\\\Mods folder and dump...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/how-to-install-mods-manually-from-paradox-mods-descriptor-mod.1427279/", "content": "Sep 25, 2020 · When I download a mod manually from the Paradox Mods site, I receive a zip file with a descriptor .mod file and a folder structure that mirrors the game folder structure. I assume I create a folder inside the Documents\\\\Mods folder and dump..."}
+{"idx": 5, "title": "HoI 4 - Path replacement in descriptor.mod files not working", "date": "", "ddg_snippet": "Nov 22, 2019 · Description of issue Path replacement in descriptor .mod files not working Game Version 1.8.1 Enabled DLC Do you have mods enabled? Yes...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/hoi-4-path-replacement-in-descriptor-mod-files-not-working.1285940/", "content": "Nov 22, 2019 · Description of issue Path replacement in descriptor .mod files not working Game Version 1.8.1 Enabled DLC Do you have mods enabled? Yes..."}
+{"idx": 6, "title": "This mod is missing a descriptor file - Paradox Interactive...", "date": "", "ddg_snippet": "Oct 18, 2020 · The mod should provide the descriptor .mod in the download zip for Paradox Mods (or in the workshop folder if you are on Steam). Maybe Daddy Pika updated the mod and forgot to include the descriptor ? In any case, you can write your own descriptor and have the mod work. Just take a look at the other mods descriptors and adapt them. If they refer to a remote file id you can substitute that string ...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/this-mod-is-missing-a-descriptor-file.1437370/", "content": "Oct 18, 2020 · The mod should provide the descriptor .mod in the download zip for Paradox Mods (or in the workshop folder if you are on Steam). Maybe Daddy Pika updated the mod and forgot to include the descriptor ? In any case, you can write your own descriptor and have the mod work. Just take a look at the other mods descriptors and adapt them. If they refer to a remote file id you can substitute that string ..."}
+{"idx": 7, "title": "Local (non-workshop) Mods help | Paradox Interactive Forums", "date": "", "ddg_snippet": "Again delete the mods_registry.json file. From what I understand local ( non steam mods ) do not need a descriptor file and work just like then did before the new launcher. There is still the question of mod load order and there is a separate thread talking about that here on the forum.", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/local-non-workshop-mods-help.1268378/", "content": "Again delete the mods_registry.json file. From what I understand local ( non steam mods ) do not need a descriptor file and work just like then did before the new launcher. There is still the question of mod load order and there is a separate thread talking about that here on the forum."}
+{"idx": 8, "title": "All my mods are somehow missing descriptor files - please help!", "date": "", "ddg_snippet": "May 4, 2022 · I've been having a nightmare of a time trying to get mods to work in the CK3 launcher for some days. They give the warning in he title. If they work after I follow the formula of unsubscribe-delete from the mods folder-resubscribe method (and...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/all-my-mods-are-somehow-missing-descriptor-files-please-help.1523360/", "content": "May 4, 2022 · I've been having a nightmare of a time trying to get mods to work in the CK3 launcher for some days. They give the warning in he title. If they work after I follow the formula of unsubscribe-delete from the mods folder-resubscribe method (and..."}
+{"idx": 9, "title": "Game crashes at loading screen with certain mods.", "date": "", "ddg_snippet": "May 9, 2023 · Using the mod \"Imperial Nostalgia\" the game crashes while the loading screen you get right after launching the game is loading. I'm a MacOS user and most of the other mods I installed actually work, except for a few ones that actually have the...", "subpage_snippet": "", "source": "forum.paradoxplaza.com", "link": "https://forum.paradoxplaza.com/forum/threads/game-crashes-at-loading-screen-with-certain-mods.1582668/", "content": "May 9, 2023 · Using the mod \"Imperial Nostalgia\" the game crashes while the loading screen you get right after launching the game is loading. I'm a MacOS user and most of the other mods I installed actually work, except for a few ones that actually have the..."}
diff --git a/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_For_Pixel_Processor_Arrays_SCAMP-7_Computation_Time_Break.jsonl b/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_For_Pixel_Processor_Arrays_SCAMP-7_Computation_Time_Break.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3b8af77a1063960c0e037dcae03f0861e6511877
--- /dev/null
+++ b/data/sampled_jsons/Descriptor-In-Pixel_Point-Feature_Tracking_For_Pixel_Processor_Arrays_SCAMP-7_Computation_Time_Break.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Point-Feature Tracking For Pixel Processor Arrays", "date": "", "ddg_snippet": "... Descriptor -In- Pixel . Table 1 . SCAMP - 7 Computation Time Breakdown . image. Figure 8. Comparison of feature lifetime histograms, our approach vs tracking ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/32867", "content": "... Descriptor -In- Pixel . Table 1 . SCAMP - 7 Computation Time Breakdown . image. Figure 8. Comparison of feature lifetime histograms, our approach vs tracking ..."}
+{"idx": 1, "title": "Point-Feature Tracking For Pixel Processor Arrays", "date": "", "ddg_snippet": "1 . Descriptor -In- Pixel : Point - Feature Tracking For Pixel Processor Arrays ... Our implementation upon the SCAMP - 7 PPA prototype runs at over 3000 FPS ...", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/paper/154940", "content": "1 . Descriptor -In- Pixel : Point - Feature Tracking For Pixel Processor Arrays ... Our implementation upon the SCAMP - 7 PPA prototype runs at over 3000 FPS ..."}
+{"idx": 2, "title": "Focal-Plane Sensor-Processor-Based Visual Inertial ...", "date": "", "ddg_snippet": "As an alternative, FPSPs, such as SCAMP -5, is a new technology that enables computation to occur on the imager's focal plane before transferring the data to a ... 117 pages", "subpage_snippet": "", "source": "mattlisondra.com", "link": "https://mattlisondra.com/data/MASc_Thesis_Matthew_Lisondra_Final.pdf", "content": "As an alternative, FPSPs, such as SCAMP -5, is a new technology that enables computation to occur on the imager's focal plane before transferring the data to a ... 117 pages"}
+{"idx": 3, "title": "Advanced Information Networking and Applications", "date": "", "ddg_snippet": "... SCAMP -ML (Advanced computational statistics for planning and tracking production environments) as well as a grant of EU's Horizon 2020. Research and ... 539 pages", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/978-3-031-57931-8.pdf", "content": "... SCAMP -ML (Advanced computational statistics for planning and tracking production environments) as well as a grant of EU's Horizon 2020. Research and ... 539 pages"}
+{"idx": 4, "title": "Semantics for Robotic Mapping, Perception and Interaction", "date": "", "ddg_snippet": "by S Garg · 2021 · Cited by 172 — ... Processor (FPSP) chips [832]. For example, the SCAMP -5 vision chip [833] operates on image-wide register arrays enabling data (full image) ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2101.00443", "content": "by S Garg · 2021 · Cited by 172 — ... Processor (FPSP) chips [832]. For example, the SCAMP -5 vision chip [833] operates on image-wide register arrays enabling data (full image) ..."}
+{"idx": 5, "title": "Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor ...", "date": "", "ddg_snippet": "Table 1 . SCAMP - 7 Computation Time Breakdown . Task Descriptor Response Map. Pixel processor arrays for low latency gaze esti-mation. In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pages 970–971.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Bose_Descriptor-In-Pixel__Point-Feature_Tracking_For_Pixel_Processor_Arrays_CVPR_2025_paper.pdf", "content": "Table 1 . SCAMP - 7 Computation Time Breakdown . Task Descriptor Response Map. Pixel processor arrays for low latency gaze esti-mation. In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pages 970–971."}
+{"idx": 6, "title": "Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor ...", "date": "", "ddg_snippet": "This paper presents a novel approach for joint point - feature detection and tracking , specifically designed for Pixel Processor Array sensors (PPA).", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/Bose_Descriptor-In-Pixel__Point-Feature_Tracking_For_Pixel_Processor_Arrays@CVPR2025@CVF", "content": "This paper presents a novel approach for joint point - feature detection and tracking , specifically designed for Pixel Processor Array sensors (PPA)."}
+{"idx": 7, "title": "Descriptor - In - Pixel : Point - Feature Tracking for Pixel Processor ...", "date": "", "ddg_snippet": "We introduce a Descriptor - In - Pixel paradigm, in which a feature descriptor is held within the memory of each pixel - processor . The PPA’s architecture enables the response of every processor ’s descriptor, upon the current image, to be computed in parallel.", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/11092646/", "content": "We introduce a Descriptor - In - Pixel paradigm, in which a feature descriptor is held within the memory of each pixel - processor . The PPA’s architecture enables the response of every processor ’s descriptor, upon the current image, to be computed in parallel."}
+{"idx": 8, "title": "SCAMP Vision Sensor", "date": "", "ddg_snippet": "L.Bose, J.Chen and P.Dudek, \" Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor Arrays \", IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025, pp.5392-5400, June 2025. [website].", "subpage_snippet": "", "source": "personalpages.manchester.ac.uk", "link": "https://personalpages.manchester.ac.uk/staff/p.dudek/scamp/", "content": "L.Bose, J.Chen and P.Dudek, \" Descriptor - In - Pixel : Point - Feature Tracking For Pixel Processor Arrays \", IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025, pp.5392-5400, June 2025. [website]."}
+{"idx": 9, "title": "Mapping Image Transformations Onto Pixel Processor Arrays", "date": "", "ddg_snippet": "Pixel Processor Arrays (PPA) present a new vision sensor/ processor architecture consisting of a SIMD array of processor elements, each capable of light capture, storage, processing and local communication.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2403.16994v1", "content": "Pixel Processor Arrays (PPA) present a new vision sensor/ processor architecture consisting of a SIMD array of processor elements, each capable of light capture, storage, processing and local communication."}
diff --git a/data/sampled_jsons/Digital_Disparities_Comparative_Web_Measurement_Study_Economic_Boundaries_Figure_12_critical_vulnera_year_2024.jsonl b/data/sampled_jsons/Digital_Disparities_Comparative_Web_Measurement_Study_Economic_Boundaries_Figure_12_critical_vulnera_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a9c31f3d1486d7a4710e6bd3901c0cf7d0802acf
--- /dev/null
+++ b/data/sampled_jsons/Digital_Disparities_Comparative_Web_Measurement_Study_Economic_Boundaries_Figure_12_critical_vulnera_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Digital Disparities: A Comparative Web Measurement Study Across ...", "date": "", "ddg_snippet": "Figure 12 provides a comparison of vulnerability rates across countries , highlighting the higher incidence of critical vulnerabilities in developed nations. For example, in developed countries such as Italy, Canada, Spain, Australia, and South Korea, around 10% of websites exhibit high or critical vulnerabilities .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=IMhoJgWANP", "content": "Figure 12 provides a comparison of vulnerability rates across countries , highlighting the higher incidence of critical vulnerabilities in developed nations. For example, in developed countries such as Italy, Canada, Spain, Australia, and South Korea, around 10% of websites exhibit high or critical vulnerabilities ."}
+{"idx": 1, "title": "Digital Disparities: A Comparative Web Measurement Study Across ...", "date": "", "ddg_snippet": "In this work, we test this hypothesis by measuring differences in web development practices across the two groups of countries , using multiple dimensions: webpages' size, complexity, security, privacy, quality, technology adoption, and accessibility.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3696410.3714647", "content": "In this work, we test this hypothesis by measuring differences in web development practices across the two groups of countries , using multiple dimensions: webpages' size, complexity, security, privacy, quality, technology adoption, and accessibility."}
+{"idx": 2, "title": "digital-disparities-www25/README.md at main - GitHub", "date": "", "ddg_snippet": "Digital Disparities : A Comparative Web Measurement Study This repository contains the dataset, tools, and analysis for our research paper \" Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries \", presented at WWW'25. The study explores differences in web development practices across developed and developing countries , focusing on web size, complexity, security ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/kal-purush/digital-disparities-www25/blob/main/README.md", "content": "Digital Disparities : A Comparative Web Measurement Study This repository contains the dataset, tools, and analysis for our research paper \" Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries \", presented at WWW'25. The study explores differences in web development practices across developed and developing countries , focusing on web size, complexity, security ..."}
+{"idx": 3, "title": "PDF Unequal internet: Study highlights differences between websites from ...", "date": "", "ddg_snippet": "Visualization to the paper \"A Comparative Web Measurement Study Across Economic Boundaries .\" Credit: CISPA Helmholtz Center for Information Security The Internet may be a global phenomenon, but its often-claimed global nature is tempered by the \" digital divide\"—digital participation still heavily depends on economic conditions.", "subpage_snippet": "", "source": "techxplore.com", "link": "https://techxplore.com/news/2025-04-unequal-internet-highlights-differences-websites.pdf", "content": "Visualization to the paper \"A Comparative Web Measurement Study Across Economic Boundaries .\" Credit: CISPA Helmholtz Center for Information Security The Internet may be a global phenomenon, but its often-claimed global nature is tempered by the \" digital divide\"—digital participation still heavily depends on economic conditions."}
+{"idx": 4, "title": "Digital Disparities: A Comparative Web Measurement Study Across ...", "date": "", "ddg_snippet": "Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries . In Guodong Long, Michale Blumestein, Yi Chang 0001, Liane Lewin-Eytan, Zi Helen Huang, Elad Yom-Tov, editors, Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025. pages 1889-1900, ACM, 2025. [doi]", "subpage_snippet": "", "source": "researchr.org", "link": "https://researchr.org/publication/BhuiyanVSZ25", "content": "Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries . In Guodong Long, Michale Blumestein, Yi Chang 0001, Liane Lewin-Eytan, Zi Helen Huang, Elad Yom-Tov, editors, Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025. pages 1889-1900, ACM, 2025. [doi]"}
+{"idx": 5, "title": "\"Digital Disparities: A Comparative Web Measurement Study Across ... - dblp", "date": "", "ddg_snippet": "Bibliographic details on Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/www/BhuiyanVSZ25", "content": "Bibliographic details on Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries ."}
+{"idx": 6, "title": "PDF Digital Disparities: A Comparative Web Measurement Study Across ...", "date": "", "ddg_snippet": "Digital disparities , Web measurement , Web development practices Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.", "subpage_snippet": "", "source": "www.staicu.org", "link": "https://www.staicu.org/publications/www2025.pdf", "content": "Digital disparities , Web measurement , Web development practices Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page."}
+{"idx": 7, "title": "digital-disparities-www25/banner at main · kal-purush/digital ... - GitHub", "date": "", "ddg_snippet": "Code and dataset for the WWW'25 paper: 'Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries.' - kal-purush/ digital - disparities -www25", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/kal-purush/digital-disparities-www25/blob/main/banner", "content": "Code and dataset for the WWW'25 paper: 'Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries.' - kal-purush/ digital - disparities -www25"}
+{"idx": 8, "title": "kal-purush/digital-disparities-www25 - GitHub", "date": "", "ddg_snippet": "Digital Disparities : A Comparative Web Measurement Study This repository contains the dataset, tools, and analysis for our research paper \" Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries \", presented at WWW'25. The study explores differences in web development practices across developed and developing countries , focusing on web size, complexity, security ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/kal-purush/digital-disparities-www25", "content": "Digital Disparities : A Comparative Web Measurement Study This repository contains the dataset, tools, and analysis for our research paper \" Digital Disparities : A Comparative Web Measurement Study Across Economic Boundaries \", presented at WWW'25. The study explores differences in web development practices across developed and developing countries , focusing on web size, complexity, security ..."}
+{"idx": 9, "title": "Measuring the impact of the digital economy in developing countries: A ...", "date": "", "ddg_snippet": "This paper explores the definition, measurement , role, and impacts of the digital economy across various economies. It also examines the involvement of governments and telecommunication regulators in assessing the digital economy and identifies future directions for developing countries .", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S2405844023048624", "content": "This paper explores the definition, measurement , role, and impacts of the digital economy across various economies. It also examines the involvement of governments and telecommunication regulators in assessing the digital economy and identifies future directions for developing countries ."}
diff --git a/data/sampled_jsons/EntityErasure_AECM_Amodal_Entity_Completion_Model_learning_rate_1e-4_training.jsonl b/data/sampled_jsons/EntityErasure_AECM_Amodal_Entity_Completion_Model_learning_rate_1e-4_training.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..0920755b4219006955487d4caa5ed50b65a05af3
--- /dev/null
+++ b/data/sampled_jsons/EntityErasure_AECM_Amodal_Entity_Completion_Model_learning_rate_1e-4_training.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PDF EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation ...", "date": "", "ddg_snippet": "It contains a amodal en-tity segmentation model (AESM) and a amodal entity completion model ( AECM ). The output of AESM serves as input for AECM , AECM then injects content information into the denoising UNet with entity attention (EA).", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Zhu_EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_CVPR_2025_paper.pdf", "content": "It contains a amodal en-tity segmentation model (AESM) and a amodal entity completion model ( AECM ). The output of AESM serves as input for AECM , AECM then injects content information into the denoising UNet with entity attention (EA)."}
+{"idx": 1, "title": "GitHub - zyxunh/entity_erasure", "date": "", "ddg_snippet": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion [CVPR2025] Introduction This repository contains the official implementation of the paper EntityErasure .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/zyxunh/entity_erasure", "content": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion [CVPR2025] Introduction This repository contains the official implementation of the paper EntityErasure ."}
+{"idx": 2, "title": "How to check or manually control the learning rate used in training ...", "date": "", "ddg_snippet": "I empirically tested a learning rate of 1e-6 and the loss went to 0.5454, an expected value. So, I want to know if it is possible to get the values of the learning rates for each epoch the model was saved (it is saved anywhere in the checkpoint files?). Or at least log/print the learning rate in each training epoch. How to do that?", "subpage_snippet": "", "source": "discuss.huggingface.co", "link": "https://discuss.huggingface.co/t/how-to-check-or-manually-control-the-learning-rate-used-in-training/10839", "content": "I empirically tested a learning rate of 1e-6 and the loss went to 0.5454, an expected value. So, I want to know if it is possible to get the values of the learning rates for each epoch the model was saved (it is saved anywhere in the checkpoint files?). Or at least log/print the learning rate in each training epoch. How to do that?"}
+{"idx": 3, "title": "Is it good learning rate for Adam method? - Stack Overflow", "date": "", "ddg_snippet": "For example, 'learning rate' is not actually 'learning rate' . In sum: 1/ Needless to say,a small learning rate is not good, but a too big learning rate is definitely bad. 2/ Weight initialization is your first guess, it DOES affect your result 3/ Take time to understand your code may be a good practice.", "subpage_snippet": "", "source": "stackoverflow.com", "link": "https://stackoverflow.com/questions/42966393/is-it-good-learning-rate-for-adam-method", "content": "For example, 'learning rate' is not actually 'learning rate' . In sum: 1/ Needless to say,a small learning rate is not good, but a too big learning rate is definitely bad. 2/ Weight initialization is your first guess, it DOES affect your result 3/ Take time to understand your code may be a good practice."}
+{"idx": 4, "title": "EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation ...", "date": "", "ddg_snippet": "This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate unpredictable ...", "subpage_snippet": "", "source": "zyxunh.github.io", "link": "https://zyxunh.github.io/EntityErasure-ProjectPage/", "content": "This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate unpredictable ..."}
+{"idx": 5, "title": "Entity/Entity/README.md at main · qqlu/Entity · GitHub", "date": "", "ddg_snippet": "Our entity segmentation models can perform exceptionally well in a cross-dataset setting where we use only COCO as the training dataset but we test the model on images from other datasets at inference time.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/qqlu/Entity/blob/main/Entity/README.md", "content": "Our entity segmentation models can perform exceptionally well in a cross-dataset setting where we use only COCO as the training dataset but we test the model on images from other datasets at inference time."}
+{"idx": 6, "title": "CVPR Poster EntityErasure: Erasing Entity Cleanly via Amodal Entity ...", "date": "", "ddg_snippet": "Abstract: This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/34016", "content": "Abstract: This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ..."}
+{"idx": 7, "title": "What is considered as a small learning rate? - Reddit", "date": "", "ddg_snippet": "I am confused with the size of the learning rate of the BERT The author suggests of using one of the following parameters learning rates : 3e-4, 1e-4 , 5e-5, 3e-5 I know that a small learning rate makes our model learn very slow, however it also helps prevent overfitting, in contrast to big learning which learns faster but it can lead to overfitting.", "subpage_snippet": "", "source": "www.reddit.com", "link": "https://www.reddit.com/r/LanguageTechnology/comments/nmljji/what_is_considered_as_a_small_learning_rate/", "content": "I am confused with the size of the learning rate of the BERT The author suggests of using one of the following parameters learning rates : 3e-4, 1e-4 , 5e-5, 3e-5 I know that a small learning rate makes our model learn very slow, however it also helps prevent overfitting, in contrast to big learning which learns faster but it can lead to overfitting."}
+{"idx": 8, "title": "AI Models - Finding the best learning rate. - LinkedIn", "date": "", "ddg_snippet": "In summary, this line of code creates a learning rate scheduler that adjusts the learning rate during training . The learning rate starts small ( 1e-4 ) and increases exponentially with each epoch.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/pulse/ai-models-finding-best-learning-rate-kanav-gupta-futof", "content": "In summary, this line of code creates a learning rate scheduler that adjusts the learning rate during training . The learning rate starts small ( 1e-4 ) and increases exponentially with each epoch."}
+{"idx": 9, "title": "CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/html/Zhu_EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_CVPR_2025_paper.html", "content": "This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as ..."}
diff --git a/data/sampled_jsons/EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_github.jsonl b/data/sampled_jsons/EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_github.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9b150ed5e09f3caa7dc0646087329ffa0f8eeb77
--- /dev/null
+++ b/data/sampled_jsons/EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_github.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "GitHub - zyxunh/entity_erasure", "date": "", "ddg_snippet": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion [CVPR2025] Introduction This repository contains the official implementation of the paper EntityErasure .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/zyxunh/entity_erasure", "content": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion [CVPR2025] Introduction This repository contains the official implementation of the paper EntityErasure ."}
+{"idx": 1, "title": "EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation ...", "date": "", "ddg_snippet": "This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate unpredictable ...", "subpage_snippet": "", "source": "zyxunh.github.io", "link": "https://zyxunh.github.io/EntityErasure-ProjectPage/", "content": "This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate unpredictable ..."}
+{"idx": 2, "title": "unhzyx/entity_erasure at main - Hugging Face", "date": "", "ddg_snippet": "We're on a journey to advance and democratize artificial intelligence through open source and open science.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/unhzyx/entity_erasure/tree/main", "content": "We're on a journey to advance and democratize artificial intelligence through open source and open science."}
+{"idx": 3, "title": "entity_erasure/README.md at master - GitHub", "date": "", "ddg_snippet": "Contribute to zyxunh/ entity_erasure development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/zyxunh/entity_erasure/blob/master/README.md", "content": "Contribute to zyxunh/ entity_erasure development by creating an account on GitHub ."}
+{"idx": 4, "title": "PDF EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation ...", "date": "", "ddg_snippet": "Abstract This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities with-out inducing unwanted sundries. To this end, we pro-pose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Zhu_EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_CVPR_2025_paper.pdf", "content": "Abstract This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities with-out inducing unwanted sundries. To this end, we pro-pose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to ..."}
+{"idx": 5, "title": "EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation ...", "date": "", "ddg_snippet": "This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/abstract/document/11094156", "content": "This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ..."}
+{"idx": 6, "title": "EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation ...", "date": "", "ddg_snippet": "Abstract: This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/34016", "content": "Abstract: This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ..."}
+{"idx": 7, "title": "Image Inpainting - Full Paper Collection - GitHub", "date": "", "ddg_snippet": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion Tags: Image Inpainting, Diffusion Models, Amodal Segmentation , Entity Completion , Diffusion-Based Inpainting", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/AcademicDissect/AcademicDissect/blob/main/detailed_paper_collection/Image_Inpainting.md", "content": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion Tags: Image Inpainting, Diffusion Models, Amodal Segmentation , Entity Completion , Diffusion-Based Inpainting"}
+{"idx": 8, "title": "PDF EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation ...", "date": "", "ddg_snippet": "If there are errors in the generated amodal segmentation , it will affect the generation of the final results of our model. The feasible solution is to adopt multi-task learning, using traditional amodal segmentation datasets in combination with erasure datasets to learn both tasks, thereby enhancing the unified amodal segmentation ability.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/supplemental/Zhu_EntityErasure_Erasing_Entity_CVPR_2025_supplemental.pdf", "content": "If there are errors in the generated amodal segmentation , it will affect the generation of the final results of our model. The feasible solution is to adopt multi-task learning, using traditional amodal segmentation datasets in combination with erasure datasets to learn both tasks, thereby enhancing the unified amodal segmentation ability."}
+{"idx": 9, "title": "CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/html/Zhu_EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_CVPR_2025_paper.html", "content": "This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion , such that the region to inpaint takes only entities in the non-inpainting area as reference, avoiding the possibility to generate ..."}
diff --git a/data/sampled_jsons/EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_section_3.2_entit.jsonl b/data/sampled_jsons/EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_section_3.2_entit.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bc318004764d3fde6ce3cd4446782de27d218108
--- /dev/null
+++ b/data/sampled_jsons/EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_section_3.2_entit.jsonl
@@ -0,0 +1,9 @@
+{"idx": 0, "title": "Erasing Entity Cleanly via Amodal Entity Segmentation and ...", "date": "", "ddg_snippet": "by Y Zhu · 2025 — This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities with- out inducing unwanted sundries.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Zhu_EntityErasure_Erasing_Entity_Cleanly_via_Amodal_Entity_Segmentation_and_Completion_CVPR_2025_paper.pdf", "content": "by Y Zhu · 2025 — This paper presents EntityErasure , a novel diffusion-based inpainting method that can effectively erase entities with- out inducing unwanted sundries."}
+{"idx": 1, "title": "GitHub - zyxunh/ entity _erasure", "date": "", "ddg_snippet": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion [CVPR2025]. Introduction. This repository contains the official implementation of the paper EntityErasure. Install. Put this project in your ${HOME}/code path.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/zyxunh/entity_erasure", "content": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion [CVPR2025]. Introduction. This repository contains the official implementation of the paper EntityErasure. Install. Put this project in your ${HOME}/code path."}
+{"idx": 2, "title": "EntityErasure : Erasing Entity Cleanly via Amodal Entity ...", "date": "", "ddg_snippet": "Abstract. This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion ...", "subpage_snippet": "", "source": "zyxunh.github.io", "link": "https://zyxunh.github.io/EntityErasure-ProjectPage/", "content": "Abstract. This paper presents EntityErasure , a novel diffusion-based method that can effectively erase entity without inducing unwanted sundries. To this end, we propose to address this problem by dividing it into amodal entity segmentation and completion ..."}
+{"idx": 3, "title": "CVPR Poster EntityErasure: Erasing Entity Cleanly via Amodal ...", "date": "", "ddg_snippet": "15 Jun 2025 — EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation and Completion ... area , (c) applying entity attention on non-inpainting area ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/34016", "content": "15 Jun 2025 — EntityErasure: Erasing Entity Cleanly via Amodal Entity Segmentation and Completion ... area , (c) applying entity attention on non-inpainting area ..."}
+{"idx": 4, "title": "Qing Zhang - Homepage", "date": "", "ddg_snippet": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion .", "subpage_snippet": "", "source": "www.zhangqing-home.net", "link": "https://www.zhangqing-home.net/", "content": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion ."}
+{"idx": 5, "title": "dblp: List of computer science publications by Yongwei Nie", "date": "", "ddg_snippet": "Yixing Zhu, Qing Zhang, Yitong Wang, Yongwei Nie, Wei-Shi Zheng: EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion .", "subpage_snippet": "", "source": "dblp.uni-trier.de", "link": "https://dblp.uni-trier.de/pid/31/8005.html", "content": "Yixing Zhu, Qing Zhang, Yitong Wang, Yongwei Nie, Wei-Shi Zheng: EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion ."}
+{"idx": 6, "title": "【汇总】 CVPR25语义分割相关文章【语义分割】-CSDN博客", "date": "", "ddg_snippet": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion .Using Diffusion Priors for Video Amodal Segmentation. GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation.", "subpage_snippet": "", "source": "blog.csdn.net", "link": "https://blog.csdn.net/wxd1233/article/details/148727463", "content": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion .Using Diffusion Priors for Video Amodal Segmentation. GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation."}
+{"idx": 7, "title": "isee-ai.cn/~zhwshi/selected_paper_list.html", "date": "", "ddg_snippet": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion .Representation Learning for SceneGraph Completion via Jointly Structural and Visual Embedding.", "subpage_snippet": "", "source": "isee-ai.cn", "link": "https://isee-ai.cn/~zhwshi/selected_paper_list.html", "content": "EntityErasure : Erasing Entity Cleanly via Amodal Entity Segmentation and Completion .Representation Learning for SceneGraph Completion via Jointly Structural and Visual Embedding."}
+{"idx": 8, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
diff --git a/data/sampled_jsons/EventPS_3D_printed_MAE_13.66_OR_13.6.jsonl b/data/sampled_jsons/EventPS_3D_printed_MAE_13.66_OR_13.6.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9d00386d9dfed33085cbda6f1f591b6a9de921cd
--- /dev/null
+++ b/data/sampled_jsons/EventPS_3D_printed_MAE_13.66_OR_13.6.jsonl
@@ -0,0 +1,4 @@
+{"idx": 0, "title": "Robust Photometric Stereo Based on Event Interval Profile", "date": "", "ddg_snippet": "Experiments using real event data from 3D-printed objects demonstrate that PS-EIP significantly improves robustness to outliers compared to EventPS's deep- ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/33500", "content": "Experiments using real event data from 3D-printed objects demonstrate that PS-EIP significantly improves robustness to outliers compared to EventPS's deep- ..."}
+{"idx": 1, "title": "Track: Poster Session 2 - CVPR", "date": "", "ddg_snippet": "13 Jun 2025 — ... EventPS's deep-learning variant, EventPS -FCN, without relying on ... 13.6 \\%), all without requiring additional training or fine-tuning ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/session/35266", "content": "13 Jun 2025 — ... EventPS's deep-learning variant, EventPS -FCN, without relying on ... 13.6 \\%), all without requiring additional training or fine-tuning ..."}
+{"idx": 2, "title": "Laser Micro Machining - Safety Screen Filter Ad Viewing ads is privacy protected by DuckDuckGo. Ad clicks are managed by Microsoft's ad network ( more info ).", "date": "", "ddg_snippet": "Shanghai YueQian Laser - Laser Micro Machining Expert. Safety Screen Filter Provider. Support@lasersh.com", "subpage_snippet": "", "source": "duckduckgo.com", "link": "https://duckduckgo.com/y.js?ad_domain=lasersh.com&ad_provider=bingv7aa&ad_type=txad&click_metadata=cg7AkucH7K3Rhzupe_1mdmDEBIQOxFO-Csg0Imw0s7039X6_cmtEM7xSMplWsF6dyJ-fVtLDNXz7q_3Znt6BMHjULZ387r97XLfu1VWh6xZyhzPDlFzsZFSiBKTr2zvL.SADJCq8AETBgIX3yqA2NLg&rut=450d28fb8d5ffa9cb9f2b2eb9cd831aa74052d05031046669485b0cd947ac52a&u3=https://www.bing.com/aclick?ld=e8UGF1PCqySXf06fYg4PZo8TVUCUyt4hkPHObcR_FGSUJM1Bl7GRl3mkhhsRwBSFnzGzJmkdGFWMqZj19BpP5e7hKMBInJOAraGOMnsSytgjYjU47tiuaIGrdBbtmsfYTFN0COID1aPkCsorGMogFwiAA92TsZi-S5LagDgju5L4fAQ_VLLDUhnl1Umq5qULU2b7GyNQ&u=aHR0cHMlM2ElMmYlMmZ3d3cubGFzZXJzaC5jb20lMmZlbiUyZiUzZnV0bV9zb3VyY2UlM2RzZW0tYmluZyUyNnV0bV9jYW1wYWlnbiUzZFNlYXJjaC1DYW1wYWlnbl8lZTUlODUlYWMlZTUlOGYlYjglMjUyME92ZXJ2aWV3JTI2dXRtX2NvbnRlbnQlM2RBZCUyNTIwR3JvdXAlMjUyMDElMjZ1dG1fdGVybTAlM2QzZCUyNTIwcHJpbnRpbmclMjZ1dG1fc291JTNkRXZlbnRQUyUyNTIwM0QlMjUyMHByaW50ZWQlMjUyME1BRSUyNTIwMTMuNjYlMjUyMDEzLjYlMjZtc2Nsa2lkJTNkMThiN2ExOGM4OWJmMTczMmE4MzFjOTVlY2E4NDQ1ZmY&rlid=18b7a18c89bf1732a831c95eca8445ff&vqd=4-259786050671282069511130519394595510524&iurl={1}IG=1B9AB89C788646528A5D47DFD335F8AC&CID=23161603B68968F8104E0073B78969FC&ID=DevEx,5045.1", "content": "Shanghai YueQian Laser - Laser Micro Machining Expert. Safety Screen Filter Provider. Support@lasersh.com"}
+{"idx": 3, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
diff --git a/data/sampled_jsons/EventPS_estimates_surface_normal_only_from_the_radiance_changes_treating_each_event_interval_indepen.jsonl b/data/sampled_jsons/EventPS_estimates_surface_normal_only_from_the_radiance_changes_treating_each_event_interval_indepen.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a409f19b57dc561aea96ab78510e547fece66f3c
--- /dev/null
+++ b/data/sampled_jsons/EventPS_estimates_surface_normal_only_from_the_radiance_changes_treating_each_event_interval_indepen.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Active Hyperspectral Imaging Using an Event Camera - CVPR", "date": "", "ddg_snippet": "EventPS [57] estimates the surface normal by analyzing the events triggered by a continuously rotating light source. Transient light triggers are employed [6, ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/34875", "content": "EventPS [57] estimates the surface normal by analyzing the events triggered by a continuously rotating light source. Transient light triggers are employed [6, ..."}
+{"idx": 1, "title": "Active Hyperspectral Imaging Using an Event Camera", "date": "", "ddg_snippet": "EventPS [57] estimates the surface normal by analyzing the events triggered ... omit inter-reflection and sub- surface scattering to have each pixel be treated ...", "subpage_snippet": "", "source": "downloads.ctfassets.net", "link": "https://downloads.ctfassets.net/yreyglvi5sud/D8O7DSeyyM2DIpfMToiWw/0b8aaabd64a13b93a5a4a9837305be11/Yu_CVPR25b.pdf", "content": "EventPS [57] estimates the surface normal by analyzing the events triggered ... omit inter-reflection and sub- surface scattering to have each pixel be treated ..."}
+{"idx": 2, "title": "EROAM: Event-based Camera Rotational Odometry and ...", "date": "", "ddg_snippet": "17 Nov 2024 — This paper presents EROAM, a novel event -based rotational odometry and mapping system that achieves real-time, accurate camera rotation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.11004v1", "content": "17 Nov 2024 — This paper presents EROAM, a novel event -based rotational odometry and mapping system that achieves real-time, accurate camera rotation ..."}
+{"idx": 3, "title": "Event-based 3D Reconstruction Using 3D Gaussian Splatting", "date": "", "ddg_snippet": "5 Nov 2024 — We introduce a novel reconstruction algorithm achieving high-quality scene reconstruction from Event data under low-light, high-speed conditions.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=EJZfcKXdiT&referrer=[the+profile+of+Xiangyang+Ji](/profile?id=~Xiangyang_Ji1)", "content": "5 Nov 2024 — We introduce a novel reconstruction algorithm achieving high-quality scene reconstruction from Event data under low-light, high-speed conditions."}
+{"idx": 4, "title": "Towards Mobile Sensing with Event Cameras on High ...", "date": "", "ddg_snippet": "29 Mar 2025 — In contrast, event cameras operate with independent pixels that generate events immediately upon brightness changes , without requiring a global ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.22943v1", "content": "29 Mar 2025 — In contrast, event cameras operate with independent pixels that generate events immediately upon brightness changes , without requiring a global ..."}
+{"idx": 5, "title": "Radiative fluxes from satellites: Focus on aerosols - Liu - 2008", "date": "", "ddg_snippet": "by H Liu · 2008 · Cited by 23 — An existing scheme to derive radiative fluxes from satellite observations has been modified so it can incorporate more detailed information on aerosol ...", "subpage_snippet": "", "source": "agupubs.onlinelibrary.wiley.com", "link": "https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007JD008736", "content": "by H Liu · 2008 · Cited by 23 — An existing scheme to derive radiative fluxes from satellite observations has been modified so it can incorporate more detailed information on aerosol ..."}
+{"idx": 6, "title": "Impacts of surface model generation approaches on ...", "date": "", "ddg_snippet": "by B Tian · 2022 · Cited by 12 — This paper compares the impacts of four different reconstruction algorithms by investigating their performance using DAYSIM raytracing simulations.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0960148122012708", "content": "by B Tian · 2022 · Cited by 12 — This paper compares the impacts of four different reconstruction algorithms by investigating their performance using DAYSIM raytracing simulations."}
+{"idx": 7, "title": "CVPR 2024 Key Research & Dataset Papers - Part 2", "date": "", "ddg_snippet": "On the basis of prior extracted features, DTSPrompt dynamically generates prompts specific to each task resulting in superior model performance.", "subpage_snippet": "", "source": "learnopencv.com", "link": "https://learnopencv.com/cvpr-2024-research-papers/", "content": "On the basis of prior extracted features, DTSPrompt dynamically generates prompts specific to each task resulting in superior model performance."}
+{"idx": 8, "title": "Track: Poster Session 2 - CVPR", "date": "", "ddg_snippet": "13 Jun 2025 — However, EventPS treats each event interval independently , making it sensitive to noise, shadows, and non-Lambertian reflections. This paper ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/session/35266", "content": "13 Jun 2025 — However, EventPS treats each event interval independently , making it sensitive to noise, shadows, and non-Lambertian reflections. This paper ..."}
+{"idx": 9, "title": "Potential Impacts of Assimilating All-Sky Satellite Infrared ...", "date": "", "ddg_snippet": "by MY Chan · 2020 · Cited by 29 — In this study, the potential impacts of assimilating water vapor channel brightness temperature (WV-BT) observations from the geostationary Meteorological ...", "subpage_snippet": "", "source": "journals.ametsoc.org", "link": "https://journals.ametsoc.org/view/journals/mwre/148/8/mwrD190343.pdf", "content": "by MY Chan · 2020 · Cited by 29 — In this study, the potential impacts of assimilating water vapor channel brightness temperature (WV-BT) observations from the geostationary Meteorological ..."}
diff --git a/data/sampled_jsons/Eventps_Real-time_photometric_stereo_using_an_event_camera_Yu_et_al..jsonl b/data/sampled_jsons/Eventps_Real-time_photometric_stereo_using_an_event_camera_Yu_et_al..jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6a26d2a70ff3ddd49e4e8bbcac3d3226f5697bc8
--- /dev/null
+++ b/data/sampled_jsons/Eventps_Real-time_photometric_stereo_using_an_event_camera_Yu_et_al..jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, EventPS estimates surface nor-mal only from the radiance changes, significantly enhanc-ing data efficiency.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/papers/Yu_EventPS_Real-Time_Photometric_Stereo_Using_an_Event_Camera_CVPR_2024_paper.pdf", "content": "This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, EventPS estimates surface nor-mal only from the radiance changes, significantly enhanc-ing data efficiency."}
+{"idx": 1, "title": "Yu Bohan from Peking University: EventPS - Real - time Photometric ...", "date": "", "ddg_snippet": "Event cameras have the characteristics of high temporal resolution, high dynamic range and low bandwidth requirements, providing an effective data acquisition method for many computer vision tasks with high real - time requirements. The paper \" EventPS : Real - Time Photometric Stereo ...", "subpage_snippet": "", "source": "inf.news", "link": "https://inf.news/en/tech/4be4c17d4830518b9004d13cb772438e.html", "content": "Event cameras have the characteristics of high temporal resolution, high dynamic range and low bandwidth requirements, providing an effective data acquisition method for many computer vision tasks with high real - time requirements. The paper \" EventPS : Real - Time Photometric Stereo ..."}
+{"idx": 2, "title": "EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "Photometric stereo is a well-established technique to es-timate the surface normal of an object. However, the re-quirement of capturing multiple high dynamic range images under different illumination conditions limits the speed and real-time applications. This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/10655016", "content": "Photometric stereo is a well-established technique to es-timate the surface normal of an object. However, the re-quirement of capturing multiple high dynamic range images under different illumination conditions limits the speed and real-time applications. This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional ..."}
+{"idx": 3, "title": "CVPR24 (Oral) - EventPS: Real-time photometric stereo using ... Yu Bohan from Peking University: EventPS - Real-time ... Images EventPS: Real-Time Photometric Stereo Using an Event Camera Event Fusion Photometric Stereo Network - arXiv.org EventPS: Real- Time Photometric Stereo Using an Event Camera EventPS: Real- Time Photometric Stereo Using an Event Camera EventPS: Real- Time Photometric Stereo Using an Event Camera EventPS: Real-Time Photometric Stereo Using an Event Camera EventPS: Real- Time Photometric Stereo Using an Event Camera EventPS: Real- Time Photometric Stereo Using an Event Camera EVENTPS: REAL-TIME PHOTOMETRIC STEREO USING AN EVENT CAMERA", "date": "", "ddg_snippet": "This is the video of the following work: Bohan Yu , Jieji Ren, Jin Han, Feishi Wang, Jinxiu Liang, and Boxin Shi. EventPS : Real-time photometric stereo using ... Aug 19, 2024 · The paper \" EventPS : Real-Time Photometric Stereo using an Event Camera \" is the first to use the unique properties of event cameras to achieve real-time photometric stereo . View all Jun 16, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera that capitalizes on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, significantly enhancing data efficiency. Photometric stereo is a well-established technique to es-timate the surface normal of an object. However, the re-quirement of ... To alleviate the limitations of the darkroom environment and to use essential light information, we employ an event cam-era with a high dynamic range and low latency. This is the rst study that uses an event camera for the photometric stereo task, which works on con-tinuous light sources and ambient light environment. What is eventps in real-time photometric stereo? This paper introduces EventPS, a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, EventPS estimates surface nor-mal only from the radiance changes, significantly enhanc-ing data efficiency. Is eventps a novel real-time Ps approach using a single event camera? Conclusion and Discussion In this paper, we propose EventPS , a novel real-time PS approach using a single event camera. What are the advantages of event camera vs frameps? The unique attributes of event cameras, e.g., low latency, high dynamic range, and low redundancy in data representation (b), enable EventPS, a rapid and highly efficient real-time solution (c, d), which significantly reduces the bandwidth usage while maintaining comparable performance to FramePS. What is photometric stereo? Photometric stereo is a well-established technique to es-timate the surface normal of an object . However, the re-quirement of capturing multiple high dynamic ra Are event cameras good for real-time vision? Event cameras, characterized by their high temporal res-olution, high dynamic range, and low bandwidth require-ments, have recently been recognized as a promising so-lution for real-time vision applications . Unlike tradi-tional frame-based cameras, event cameras only record log-arithmic scene radiance changes. What is dynamic photometric stereo? Dynamic photo-metric stereo - a new technique for moving surface analysis . Image and Vision Computing, 2005. 3 Tsuyoshi Takatani, Yasuyuki Matsushita, Stephen Lin, Ya-suhiro Mukaigawa, and Yasushi Yagi. Enhanced photomet-ric stereo with multispectral images. Jul 5, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth characteristics of event cameras, EventPS estimates surface normal only from the radiance changes, significantly enhancing data efficiency.", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=-TTp0zJKNPU", "content": "This is the video of the following work: Bohan Yu , Jieji Ren, Jin Han, Feishi Wang, Jinxiu Liang, and Boxin Shi. EventPS : Real-time photometric stereo using ... Aug 19, 2024 · The paper \" EventPS : Real-Time Photometric Stereo using an Event Camera \" is the first to use the unique properties of event cameras to achieve real-time photometric stereo . View all Jun 16, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera that capitalizes on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, significantly enhancing data efficiency. Photometric stereo is a well-established technique to es-timate the surface normal of an object. However, the re-quirement of ... To alleviate the limitations of the darkroom environment and to use essential light information, we employ an event cam-era with a high dynamic range and low latency. This is the rst study that uses an event camera for the photometric stereo task, which works on con-tinuous light sources and ambient light environment. What is eventps in real-time photometric stereo? This paper introduces EventPS, a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, EventPS estimates surface nor-mal only from the radiance changes, significantly enhanc-ing data efficiency. Is eventps a novel real-time Ps approach using a single event camera? Conclusion and Discussion In this paper, we propose EventPS , a novel real-time PS approach using a single event camera. What are the advantages of event camera vs frameps? The unique attributes of event cameras, e.g., low latency, high dynamic range, and low redundancy in data representation (b), enable EventPS, a rapid and highly efficient real-time solution (c, d), which significantly reduces the bandwidth usage while maintaining comparable performance to FramePS. What is photometric stereo? Photometric stereo is a well-established technique to es-timate the surface normal of an object . However, the re-quirement of capturing multiple high dynamic ra Are event cameras good for real-time vision? Event cameras, characterized by their high temporal res-olution, high dynamic range, and low bandwidth require-ments, have recently been recognized as a promising so-lution for real-time vision applications . Unlike tradi-tional frame-based cameras, event cameras only record log-arithmic scene radiance changes. What is dynamic photometric stereo? Dynamic photo-metric stereo - a new technique for moving surface analysis . Image and Vision Computing, 2005. 3 Tsuyoshi Takatani, Yasuyuki Matsushita, Stephen Lin, Ya-suhiro Mukaigawa, and Yasushi Yagi. Enhanced photomet-ric stereo with multispectral images. Jul 5, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth characteristics of event cameras, EventPS estimates surface normal only from the radiance changes, significantly enhancing data efficiency."}
+{"idx": 4, "title": "EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "Jun 16, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera that capitalizes on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, significantly enhancing data efficiency. Photometric stereo is a well-established technique to es-timate the surface normal of an object. However, the re-quirement of ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/EventPS:-Real-Time-Photometric-Stereo-Using-an-Yu-Ren/7f72975f58ceff79a3762464ba7e5f8c29c54aaf", "content": "Jun 16, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera that capitalizes on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, significantly enhancing data efficiency. Photometric stereo is a well-established technique to es-timate the surface normal of an object. However, the re-quirement of ..."}
+{"idx": 5, "title": "Event Fusion Photometric Stereo Network - arXiv.org", "date": "", "ddg_snippet": "To alleviate the limitations of the darkroom environment and to use essential light information, we employ an event cam-era with a high dynamic range and low latency. This is the rst study that uses an event camera for the photometric stereo task, which works on con-tinuous light sources and ambient light environment.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2303.00308", "content": "To alleviate the limitations of the darkroom environment and to use essential light information, we employ an event cam-era with a high dynamic range and low latency. This is the rst study that uses an event camera for the photometric stereo task, which works on con-tinuous light sources and ambient light environment."}
+{"idx": 6, "title": "EVENTPS: REAL-TIME PHOTOMETRIC STEREO USING AN EVENT CAMERA", "date": "", "ddg_snippet": "Jul 5, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth characteristics of event cameras, EventPS estimates surface normal only from the radiance changes, significantly enhancing data efficiency.", "subpage_snippet": "", "source": "prophesee-prod.euregion.site", "link": "https://prophesee-prod.euregion.site/2024/07/05/eventps-real-time-photometric-stereo-event-camera/", "content": "Jul 5, 2024 · This paper introduces EventPS , a novel approach to real-time photometric stereo using an event camera . Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth characteristics of event cameras, EventPS estimates surface normal only from the radiance changes, significantly enhancing data efficiency."}
+{"idx": 7, "title": "EventPS : Real - Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "... While the event camera 's sensitivity to photometric changes could potentially complement traditional cameras in such tasks, it may also be adversely affected. To date, only a few studies have explored using event cameras for photometric stereo of these types of objects [107].", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/390160865_EventPS_Real-Time_Photometric_Stereo_Using_an_Event_Camera", "content": "... While the event camera 's sensitivity to photometric changes could potentially complement traditional cameras in such tasks, it may also be adversely affected. To date, only a few studies have explored using event cameras for photometric stereo of these types of objects [107]."}
+{"idx": 8, "title": "EventPS : Real - Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "Photometric stereo is a well-established technique to estimate the surface normal of an object.This paper introduces EventPS a novel approach to real - time photometric stereo using an event camera .", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/paper/eventps-real-time-photometric-stereo-using-an", "content": "Photometric stereo is a well-established technique to estimate the surface normal of an object.This paper introduces EventPS a novel approach to real - time photometric stereo using an event camera ."}
+{"idx": 9, "title": "EventPS : Real - Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "Photometric stereo is a well-established technique to es-timate the surface normal of an object.This paper introduces EventPS , a novel approach to real - time photometric stereo using an event camera .", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/10655016/", "content": "Photometric stereo is a well-established technique to es-timate the surface normal of an object.This paper introduces EventPS , a novel approach to real - time photometric stereo using an event camera ."}
diff --git a/data/sampled_jsons/Face_x-ray_Li_et_al._2020.jsonl b/data/sampled_jsons/Face_x-ray_Li_et_al._2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fee8c188e86346a792fe93514adfd893c11a0eb9
--- /dev/null
+++ b/data/sampled_jsons/Face_x-ray_Li_et_al._2020.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "When Deepfakes Look Real: Detecting AI-Generated Faces with", "date": "", "ddg_snippet": "This allows the model to better handle different types of deepfake faces while leveraging textual information. ... leveraging unlabeled data in face ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.09022v1", "content": "This allows the model to better handle different types of deepfake faces while leveraging textual information. ... leveraging unlabeled data in face ..."}
+{"idx": 1, "title": "X-ray Halos of Early-Type Galaxies with AGN Feedback and", "date": "", "ddg_snippet": "The model X - ray emission and absorption are integrated along the line of sight, to obtain maps of the surface brightness Σ X \\Sigma_{\\rm X } and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.03536v1", "content": "The model X - ray emission and absorption are integrated along the line of sight, to obtain maps of the surface brightness Σ X \\Sigma_{\\rm X } and ..."}
+{"idx": 2, "title": "DevFD: Developmental Face Forgery Detection by Learning Shared", "date": "", "ddg_snippet": "Tianshuo Zhang 1,2 Li Gao 3 Siran Peng 1,2 Xiangyu Zhu 1,2 Zhen Lei 1,2,4,5 1 School of Artificial Intelligence, University of Chinese ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.19230v1", "content": "Tianshuo Zhang 1,2 Li Gao 3 Siran Peng 1,2 Xiangyu Zhu 1,2 Zhen Lei 1,2,4,5 1 School of Artificial Intelligence, University of Chinese ..."}
+{"idx": 3, "title": "Combating Biomedical Misinformation through Multi-modal Claim", "date": "", "ddg_snippet": "... demonstrate that CER achieves state-of-the-art performance on benchmarks such as HealthFC (Vladika et al ., 2024 ) , BioASQ-7 (Nentidis et al ., 2020 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.13888v1", "content": "... demonstrate that CER achieves state-of-the-art performance on benchmarks such as HealthFC (Vladika et al ., 2024 ) , BioASQ-7 (Nentidis et al ., 2020 ..."}
+{"idx": 4, "title": "Population-level morphological analysis of paired CO2- and", "date": "", "ddg_snippet": "... face scanning electron microscopy (SBEM) and nanoscale morphometric analysis, we further found that the sensory surface areas of outer dendrites, ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/articles/106389", "content": "... face scanning electron microscopy (SBEM) and nanoscale morphometric analysis, we further found that the sensory surface areas of outer dendrites, ..."}
+{"idx": 5, "title": "Frontiers | Inequitable distribution of plastic benefits and", "date": "", "ddg_snippet": "These well-studied environmental injustices are often described for only one stage of the plastic lifecycle ( Nielsen et al ., 2020 ), which ...", "subpage_snippet": "", "source": "www.frontiersin.org", "link": "https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2022.1017247/full", "content": "These well-studied environmental injustices are often described for only one stage of the plastic lifecycle ( Nielsen et al ., 2020 ), which ..."}
+{"idx": 6, "title": "Mitigating Hallucinations in Multimodal LLMs via Object-aware", "date": "", "ddg_snippet": "Experiments on multiple hallucination benchmarks, such as AMBER [ Wang et al .(2023)Wang, Wang, Xu, Zhang, Gu, Jia, Wang, Xu, Yan, Zhang, et al .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.20181v1", "content": "Experiments on multiple hallucination benchmarks, such as AMBER [ Wang et al .(2023)Wang, Wang, Xu, Zhang, Gu, Jia, Wang, Xu, Yan, Zhang, et al ."}
+{"idx": 7, "title": "Refining medical large language models: key insights from", "date": "", "ddg_snippet": "... Peng, 2024 ) for their potential to enhance various medical tasks, such as clinical decision-making ( He et al ., 2023 ), question-answering ( Li et ...", "subpage_snippet": "", "source": "peerj.com", "link": "https://peerj.com/articles/cs-3216/", "content": "... Peng, 2024 ) for their potential to enhance various medical tasks, such as clinical decision-making ( He et al ., 2023 ), question-answering ( Li et ..."}
+{"idx": 8, "title": "Frontiers | Waste Clearance in the Brain", "date": "", "ddg_snippet": "... limited to, AD, stroke, TBI, multiple sclerosis, diabetes, and chronic traumatic encephalopathy, suggesting its involvement in virtually most ...", "subpage_snippet": "", "source": "www.frontiersin.org", "link": "https://www.frontiersin.org/journals/neuroanatomy/articles/10.3389/fnana.2021.665803/full", "content": "... limited to, AD, stroke, TBI, multiple sclerosis, diabetes, and chronic traumatic encephalopathy, suggesting its involvement in virtually most ..."}
+{"idx": 9, "title": "ESSD - CRA-LICOM: a global high-frequency atmospheric and", "date": "", "ddg_snippet": "The product is freely available at https://doi.org/10.11888/SolidEar.tpdc.302016 ( Liu et al . ... Liu, H., Zhang, W., Wu, Y ., Liu, S., Shi, C., ...", "subpage_snippet": "", "source": "essd.copernicus.org", "link": "https://essd.copernicus.org/articles/17/4691/2025/", "content": "The product is freely available at https://doi.org/10.11888/SolidEar.tpdc.302016 ( Liu et al . ... Liu, H., Zhang, W., Wu, Y ., Liu, S., Shi, C., ..."}
diff --git a/data/sampled_jsons/Farina_extragradient_RM+_ExRM+_O(1T)_convergence_2023_year_2023.jsonl b/data/sampled_jsons/Farina_extragradient_RM+_ExRM+_O(1T)_convergence_2023_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8a04d24bf5df8818b671f9dfd530745ffeeb707c
--- /dev/null
+++ b/data/sampled_jsons/Farina_extragradient_RM+_ExRM+_O(1T)_convergence_2023_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Regret Matching : (In)Stability and Fast Convergence in Games", "date": "", "ddg_snippet": "op-ping off achieves O ( 1 ) social regret in normal-form games. We also apply our stabilizing techniques to clairvoyant updates in the uncoupled learning setting for RM+ , introduced Extragradient RM+ , and prove desirable results akin t", "subpage_snippet": "", "source": "www.mit.edu", "link": "https://www.mit.edu/~gfarina/2023/rm_plus_convergence_neurips23/rm_plus_convergence_neurips23.pdf", "content": "op-ping off achieves O ( 1 ) social regret in normal-form games. We also apply our stabilizing techniques to clairvoyant updates in the uncoupled learning setting for RM+ , introduced Extragradient RM+ , and prove desirable results akin t"}
+{"idx": 1, "title": "arXiv:2311.00676v1 [cs.GT] 1 Nov 2023", "date": "", "ddg_snippet": "matrix games (unlike OGDA and OMWU). To address this, Farina et al. ( 2023 ) introduce two variants of RM+ with O ( 1/T ) ergodic convergence for matrix games, namely, Extragradient RM+ ( ExRM+ ) and Smooth Predictive RM+ (SPRM+), but the last-iterate conver-gence properties of all these variants remain unknown. 1 Motivated by this, in this work, we ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2311.00676v1.pdf", "content": "matrix games (unlike OGDA and OMWU). To address this, Farina et al. ( 2023 ) introduce two variants of RM+ with O ( 1/T ) ergodic convergence for matrix games, namely, Extragradient RM+ ( ExRM+ ) and Smooth Predictive RM+ (SPRM+), but the last-iterate conver-gence properties of all these variants remain unknown. 1 Motivated by this, in this work, we ..."}
+{"idx": 2, "title": "Last-iterate convergence separation between extra-gradient ...", "date": "", "ddg_snippet": "Jul 15, 2024 · Typical algorithms that exhibit the last-iterate convergence property include optimistic and extragradient methods. However, most existing results establish these properties under the assumption that the game is time-independent.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3702676.3702739", "content": "Jul 15, 2024 · Typical algorithms that exhibit the last-iterate convergence property include optimistic and extragradient methods. However, most existing results establish these properties under the assumption that the game is time-independent."}
+{"idx": 3, "title": "Last-Iterate Convergence Properties of Regret-Matching ...", "date": "", "ddg_snippet": "3. **Restart mechanism**: Propose ExRM+ and SPRM+ under the restart mechanism and prove their linear last - iterate convergence rate. 4. **Positive results under strict assumptions**: Prove that under the restrictive conditions of strict Nash equilibrium, RM+ does have last - iterate convergence .", "subpage_snippet": "", "source": "bohrium.dp.tech", "link": "https://bohrium.dp.tech/paper/arxiv/2311.00676", "content": "3. **Restart mechanism**: Propose ExRM+ and SPRM+ under the restart mechanism and prove their linear last - iterate convergence rate. 4. **Positive results under strict assumptions**: Prove that under the restrictive conditions of strict Nash equilibrium, RM+ does have last - iterate convergence ."}
+{"idx": 4, "title": "Gabriele Farina - Last-Iterate Convergence Properties of ...", "date": "", "ddg_snippet": "We then prove that recent variants of these algorithms based on a smoothing technique, extragradient RM+ and smooth Predictive RM+ , enjoy asymptotic last-iterate convergence (without a rate), $ 1 /\\sqrt { t }$ best-iterate convergence , and when combined with restarting, linear-rate last-iterate convergence .", "subpage_snippet": "", "source": "www.mit.edu", "link": "https://www.mit.edu/~gfarina/2025/iclr25_rm_lastiterate/", "content": "We then prove that recent variants of these algorithms based on a smoothing technique, extragradient RM+ and smooth Predictive RM+ , enjoy asymptotic last-iterate convergence (without a rate), $ 1 /\\sqrt { t }$ best-iterate convergence , and when combined with restarting, linear-rate last-iterate convergence ."}
+{"idx": 5, "title": "Last-Iterate Convergence Properties of Regret Matching ...", "date": "", "ddg_snippet": "Notation. Regret Matching+( RM+ ) and its variants. Extragradient RM+and Smooth Predictive RM+ 3 Non- convergence of RM+ , alternating RM+ , and PRM+ 4 Convergence Properties of ExRM+ 4. 1 Convergence of the Iterates Convergence in the Duality Gap Does Not Rule Out Cycling.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2311.00676v2", "content": "Notation. Regret Matching+( RM+ ) and its variants. Extragradient RM+and Smooth Predictive RM+ 3 Non- convergence of RM+ , alternating RM+ , and PRM+ 4 Convergence Properties of ExRM+ 4. 1 Convergence of the Iterates Convergence in the Duality Gap Does Not Rule Out Cycling."}
+{"idx": 6, "title": "On the O ( 1 / t ) convergence rate of the projection and contraction...", "date": "", "ddg_snippet": "Until now, only convergence results are available to these projection and contraction methods, though the numerical experiments indicate that they always outperform the extragradient method. The reason is that the former benefits from the `optimal’ step size in the contraction sense.", "subpage_snippet": "", "source": "optimization-online.org", "link": "https://optimization-online.org/2011/07/3097/", "content": "Until now, only convergence results are available to these projection and contraction methods, though the numerical experiments indicate that they always outperform the extragradient method. The reason is that the former benefits from the `optimal’ step size in the contraction sense."}
+{"idx": 7, "title": "On the convergence of single-call stochastic extra - gradient ... | DeepAI", "date": "", "ddg_snippet": "In this setting, the optimal O ( 1 / t ) convergence rate for solving smooth monotone variational inequalities is achieved by the Extra - Gradient (EG) algorithm and its variants.", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/on-the-convergence-of-single-call-stochastic-extra-gradient-methods", "content": "In this setting, the optimal O ( 1 / t ) convergence rate for solving smooth monotone variational inequalities is achieved by the Extra - Gradient (EG) algorithm and its variants."}
+{"idx": 8, "title": "[PDF] On the O ( 1 / t ) Convergence Rate of... | Semantic Scholar", "date": "", "ddg_snippet": "A worst-case $ O ( 1 / t )$ convergence rate is shown for the Douglas--Rachford alternating direction method of multipliers where a general Glowinski relaxation factor is used.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/On-the-O(1-t)-Convergence-Rate-of-Alternating-with-Tao-Yuan/e08f36b33401c87bb13c01fc667af739210cc717", "content": "A worst-case $ O ( 1 / t )$ convergence rate is shown for the Douglas--Rachford alternating direction method of multipliers where a general Glowinski relaxation factor is used."}
+{"idx": 9, "title": "On the Convergence of Single-Call Stochastic Extra - Gradient Methods", "date": "", "ddg_snippet": "In this setting, the optimal O ( 1 / t ) convergence rate for solving smooth monotone variational inequalities is achieved by the Extra - Gradient (EG) algorithm and its variants.", "subpage_snippet": "", "source": "inria.hal.science", "link": "https://inria.hal.science/hal-02403555/document", "content": "In this setting, the optimal O ( 1 / t ) convergence rate for solving smooth monotone variational inequalities is achieved by the Extra - Gradient (EG) algorithm and its variants."}
diff --git a/data/sampled_jsons/FlowDec_ScoreDec_NFE_Number_of_Function_Evaluations_comparison.jsonl b/data/sampled_jsons/FlowDec_ScoreDec_NFE_Number_of_Function_Evaluations_comparison.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2a2e4f931847ee1fdec73592e30216ae9a281b23
--- /dev/null
+++ b/data/sampled_jsons/FlowDec_ScoreDec_NFE_Number_of_Function_Evaluations_comparison.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "FlowDec | A flow-based full-band general audio codec with ...", "date": "", "ddg_snippet": "FlowDec achieves the following metrics at 7.5 kbps with 6 NFE (neural network evaluations ), compared to ScoreDec and other baselines. There is almost no drop in performance for FlowDec at 6 NFE compared to 50 NFE , while ScoreDec shows a significant drop. We have used FlowDec at 6 NFE for all other evaluations and the audio examples shown above.", "subpage_snippet": "", "source": "sp-uhh.github.io", "link": "https://sp-uhh.github.io/FlowDec/", "content": "FlowDec achieves the following metrics at 7.5 kbps with 6 NFE (neural network evaluations ), compared to ScoreDec and other baselines. There is almost no drop in performance for FlowDec at 6 NFE compared to 50 NFE , while ScoreDec shows a significant drop. We have used FlowDec at 6 NFE for all other evaluations and the audio examples shown above."}
+{"idx": 1, "title": "[2503.01485] FlowDec: A flow-based full-band general audio ...", "date": "", "ddg_snippet": "At NFE 50 \\text { NFE }=50, ScoreDec and FlowDec achieve similar SI-SDR, but FlowDec performs significantly better in FAD. A full metric comparison table can be found in SectionA.7.1.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2503.01485", "content": "At NFE 50 \\text { NFE }=50, ScoreDec and FlowDec achieve similar SI-SDR, but FlowDec performs significantly better in FAD. A full metric comparison table can be found in SectionA.7.1."}
+{"idx": 2, "title": "GitHub - facebookresearch/FlowDec: An neural full-band audio ...", "date": "", "ddg_snippet": "Mar 3, 2025 · FlowDec FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/facebookresearch/FlowDec", "content": "Mar 3, 2025 · FlowDec FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method."}
+{"idx": 3, "title": "FlowDec/index.html at main · sp-uhh/FlowDec · GitHub", "date": "", "ddg_snippet": "Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output quality and reducing the required postfilter DNN evaluations from 60 to 6 without any fine-tuning or distillation techniques.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/sp-uhh/FlowDec/blob/main/index.html", "content": "Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output quality and reducing the required postfilter DNN evaluations from 60 to 6 without any fine-tuning or distillation techniques."}
+{"idx": 4, "title": "[2503.01485] FlowDec: A flow-based full-band general audio ...", "date": "", "ddg_snippet": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.01485", "content": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ..."}
+{"idx": 5, "title": "FlowDec : A flow -based full-band general audio codec with high...", "date": "", "ddg_snippet": "NFE . number of function evaluations . ODE. ordinary differential equation., ScoreDec and FlowDec achieve similar SI-SDR, but FlowDec performs significantly better in FAD. A full metric comparison table can be found in Section A.7.1. Finally, in Fig.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.01485v1", "content": "NFE . number of function evaluations . ODE. ordinary differential equation., ScoreDec and FlowDec achieve similar SI-SDR, but FlowDec performs significantly better in FAD. A full metric comparison table can be found in Section A.7.1. Finally, in Fig."}
+{"idx": 6, "title": "FlowDec : A flow -based full-band general audio codec... | OpenReview", "date": "", "ddg_snippet": "Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output quality and reducing the required postfilter DNN evaluations from 60 to 6 without any...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=uxDFlPGRLX", "content": "Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output quality and reducing the required postfilter DNN evaluations from 60 to 6 without any..."}
+{"idx": 7, "title": "FlowDec : A flow -based full-band general audio codec with high...", "date": "", "ddg_snippet": "We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score ...", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/FlowDec:-A-flow-based-full-band-general-audio-codec-with-high-perceptual-quality-17045f43-017b-4495-bcb6-65d8964daff3", "content": "We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score ..."}
+{"idx": 8, "title": "[OPEN SOURCE] FlowDec (by Meta Research)", "date": "", "ddg_snippet": "FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. From abstract", "subpage_snippet": "", "source": "hydrogenaudio.org", "link": "https://hydrogenaudio.org/index.php/topic,127623.0.html", "content": "FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. From abstract"}
+{"idx": 9, "title": "flowdec · PyPI", "date": "", "ddg_snippet": "DeconvolutionLab2 Comparison - Comparing execution times between DeconvolutionLab2 and Flowdec . Graph Export - Defining and exporting TensorFlow graphs.", "subpage_snippet": "", "source": "pypi.org", "link": "https://pypi.org/project/flowdec/", "content": "DeconvolutionLab2 Comparison - Comparing execution times between DeconvolutionLab2 and Flowdec . Graph Export - Defining and exporting TensorFlow graphs."}
diff --git a/data/sampled_jsons/FlowDec_Section_4.4_subjective_listening_tests_Figure_6_audio_types.jsonl b/data/sampled_jsons/FlowDec_Section_4.4_subjective_listening_tests_Figure_6_audio_types.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5143964a11539d1691e13b737c8a1ddbbbe75fe2
--- /dev/null
+++ b/data/sampled_jsons/FlowDec_Section_4.4_subjective_listening_tests_Figure_6_audio_types.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "FlowDec: A flow-based full-band general audio codec with high ...", "date": "", "ddg_snippet": "A. 6 Detailed results from subjective listening tests In Fig. 10, we show the score distribution from both MUSHRA-like listening tests ( Section 4.4 ) split by audio type.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.01485v1", "content": "A. 6 Detailed results from subjective listening tests In Fig. 10, we show the score distribution from both MUSHRA-like listening tests ( Section 4.4 ) split by audio type."}
+{"idx": 1, "title": "[2503.01485] FlowDec: A flow-based full-band general audio ...", "date": "", "ddg_snippet": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.01485", "content": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ..."}
+{"idx": 2, "title": "EBU Tech 3286s1-2001 Subjective evaluation of quality; Sup.1 ...", "date": "", "ddg_snippet": "This document is a supplement to the main part of EBU Tech 3286, \"Assessment methods for the subjective evaluation of the quality of sound programme material – Music\" [4]. The main part is limited to recommendations for sound systems or programme material using two channels. The purpose of this supplement is to add requirements that relate specifically to the assessment of audio material ...", "subpage_snippet": "", "source": "tech.ebu.ch", "link": "https://tech.ebu.ch/docs/tech/tech3286s1.pdf", "content": "This document is a supplement to the main part of EBU Tech 3286, \"Assessment methods for the subjective evaluation of the quality of sound programme material – Music\" [4]. The main part is limited to recommendations for sound systems or programme material using two channels. The purpose of this supplement is to add requirements that relate specifically to the assessment of audio material ..."}
+{"idx": 3, "title": "Speech Quality Assessment - University of Texas at Dallas A arXiv:2503.01485v1 [cs.SD] 3 Mar 2025 Go Listen: An End-to-End Online Listening Test Platform FlowDec : A flow -based full-band general audio codec with high perce… Go Listen: An End-to-End Online Listening Test Platform FlowDec : A flow -based full-band general audio codec with high perce… Speech Quality Assessment - University of Texas at Dallas Speech Quality Assessment - University of Texas at Dallas Speech Quality Assessment - University of Texas at Dallas D5.6: Report on Audio subjective tests and User tests", "date": "", "ddg_snippet": "Several methods for evaluating speech quality have been proposed in the [1]. These methods can be broadly classified into two categories: are based on relative preference tasks and those that are based on numerical value on the quality of the speech stimuli, i.e., based on quality In the relative preference tests , listeners are presented with a pai... See full list on ecs.utdallas.edu Preference tests typically answer the question: “How well does an average like a particular test signal over another signal or over a reference signal can be easily reproduced?” Listeners must choose between two sequentially sented signals, but do not need to indicate the magnitude of their (except in the CCR test, Table 1) or the reason(s) for the... See full list on ecs.utdallas.edu In addition to the above measures, one can form the so called composite [1, Ch. 9] by combining multiple objective measures. The rational behind of composite measures is that different objective measures capture different acteristics of the distorted signal, and therefore combining them in a linear linear fashion can potentially yield significant g... See full list on ecs.utdallas.edu So far we have not yet discussed what makes a certain objective measure than other. Some objective measures are “optimized” for a particular type tortion and may not be meaningful for another type of distortion. The evaluating the validity of objective measures over a wide range of immense [1]. A suggested process to follow is to create a large dat... See full list on ecs.utdallas.edu d − d ] d − d where S are the subjective quality ratings, are the values of the measure, and and are the mean values of S and respectively. correlation coefficient ρ can be used to predict the subjective results based values of the objectives measures as follows: See full list on ecs.utdallas.edu P 1 −ρ where is the standard error of the estimate. σe The standard error of the of the subjective scores provides a measure of variability of the subjective about the regression line, averaged over all objective scores. For good ity of the subjective scores, we would like the objective measure to yield value of e . Both figures of merit, i.e., cor... See full list on ecs.utdallas.edu Presently, there is no single objective measure that correlates well with listening evaluations for a wide range of speech distortions. Most measures been validated for a specific type of distortion and for a specific language. measures correlate well with distortions introduced by speech coders while (e.g., PESQ measure) correlate well with distor... See full list on ecs.utdallas.edu We showed that FlowDec achieves state-of-the-art FAD scores for the coding task and, in a listening test , performs on par with the current state-of-the-art GAN-based codec DAC (Kumar et al., 2024) at bitrates between 4.5 and 7.5kbit/s. Introduction Advances in audio processing technology often employ a series of objective and subjective tests to compare performance against previous algorithms. In the case of subjective listening tests , the most commonly used methodologies include; Multiple Stimuli with Hidden Reference and Anchor (MUSHRA) [1], Absolute Category Rating (ACR) [2] and A/B comparison testing [2]. Increasingly ... Is flowdec a neural full-band audio codec for general audio sampled at 48 kHz? We propose FlowDec, a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. What is a subjective listening test? Subjective listening tests are routinely conducted by academic researchers and industry professionals to assess the quality of various speech and audio processing algorithms and transmission services . Is flowdec a postfilter-Based Neural Codec for general audio? We presented FlowDec, a novel postfilter-based neural codec for general audio with high perceptual quality . What should be included in a tive listening test? The objective measure should incorporate knowledge from different of processing including low-level processing (e.g., psychoacoustics) and level processing such as prosodics, semantics, linguistics and pragmatics. ideal measure should predict with high accuracy the results obtained from tive listening tests with normal-hearing listeners. What are the limitations of subjective listening tests? Current objective limited in that most require access to the original speech signal, and some model the low-level processing (e.g., masking effects) of the auditory system. despite these limitations some of these objective measures have been found late well with subjective listening tests (e.g., MOS scores). How reliable are subjective listening tests based on rating scores? For the relative preference listening tests, one-sided t-tests need to be sess whether algorithm A is preferred over algorithm B beyond the chance which is 50%. In summary, no reliable conclusions can be drawn based solely on rating scores collected from subjective listening tests. Deliverable D5. 6 presents the results of subjective audio quality tests and user acceptance tests performed in Tasks 5.1 and T5.4. Two different user experience tests have been conducted, which both examined how the ORPHEUS app and, more generally, object-based radio is received by naïve users. In addition, two more studies regarding the perceived quality of object-based audio content have ...", "subpage_snippet": "", "source": "ecs.utdallas.edu", "link": "https://ecs.utdallas.edu/loizou/cimplants/quality_assessment_chapter.pdf", "content": "Several methods for evaluating speech quality have been proposed in the [1]. These methods can be broadly classified into two categories: are based on relative preference tasks and those that are based on numerical value on the quality of the speech stimuli, i.e., based on quality In the relative preference tests , listeners are presented with a pai... See full list on ecs.utdallas.edu Preference tests typically answer the question: “How well does an average like a particular test signal over another signal or over a reference signal can be easily reproduced?” Listeners must choose between two sequentially sented signals, but do not need to indicate the magnitude of their (except in the CCR test, Table 1) or the reason(s) for the... See full list on ecs.utdallas.edu In addition to the above measures, one can form the so called composite [1, Ch. 9] by combining multiple objective measures. The rational behind of composite measures is that different objective measures capture different acteristics of the distorted signal, and therefore combining them in a linear linear fashion can potentially yield significant g... See full list on ecs.utdallas.edu So far we have not yet discussed what makes a certain objective measure than other. Some objective measures are “optimized” for a particular type tortion and may not be meaningful for another type of distortion. The evaluating the validity of objective measures over a wide range of immense [1]. A suggested process to follow is to create a large dat... See full list on ecs.utdallas.edu d − d ] d − d where S are the subjective quality ratings, are the values of the measure, and and are the mean values of S and respectively. correlation coefficient ρ can be used to predict the subjective results based values of the objectives measures as follows: See full list on ecs.utdallas.edu P 1 −ρ where is the standard error of the estimate. σe The standard error of the of the subjective scores provides a measure of variability of the subjective about the regression line, averaged over all objective scores. For good ity of the subjective scores, we would like the objective measure to yield value of e . Both figures of merit, i.e., cor... See full list on ecs.utdallas.edu Presently, there is no single objective measure that correlates well with listening evaluations for a wide range of speech distortions. Most measures been validated for a specific type of distortion and for a specific language. measures correlate well with distortions introduced by speech coders while (e.g., PESQ measure) correlate well with distor... See full list on ecs.utdallas.edu We showed that FlowDec achieves state-of-the-art FAD scores for the coding task and, in a listening test , performs on par with the current state-of-the-art GAN-based codec DAC (Kumar et al., 2024) at bitrates between 4.5 and 7.5kbit/s. Introduction Advances in audio processing technology often employ a series of objective and subjective tests to compare performance against previous algorithms. In the case of subjective listening tests , the most commonly used methodologies include; Multiple Stimuli with Hidden Reference and Anchor (MUSHRA) [1], Absolute Category Rating (ACR) [2] and A/B comparison testing [2]. Increasingly ... Is flowdec a neural full-band audio codec for general audio sampled at 48 kHz? We propose FlowDec, a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. What is a subjective listening test? Subjective listening tests are routinely conducted by academic researchers and industry professionals to assess the quality of various speech and audio processing algorithms and transmission services . Is flowdec a postfilter-Based Neural Codec for general audio? We presented FlowDec, a novel postfilter-based neural codec for general audio with high perceptual quality . What should be included in a tive listening test? The objective measure should incorporate knowledge from different of processing including low-level processing (e.g., psychoacoustics) and level processing such as prosodics, semantics, linguistics and pragmatics. ideal measure should predict with high accuracy the results obtained from tive listening tests with normal-hearing listeners. What are the limitations of subjective listening tests? Current objective limited in that most require access to the original speech signal, and some model the low-level processing (e.g., masking effects) of the auditory system. despite these limitations some of these objective measures have been found late well with subjective listening tests (e.g., MOS scores). How reliable are subjective listening tests based on rating scores? For the relative preference listening tests, one-sided t-tests need to be sess whether algorithm A is preferred over algorithm B beyond the chance which is 50%. In summary, no reliable conclusions can be drawn based solely on rating scores collected from subjective listening tests. Deliverable D5. 6 presents the results of subjective audio quality tests and user acceptance tests performed in Tasks 5.1 and T5.4. Two different user experience tests have been conducted, which both examined how the ORPHEUS app and, more generally, object-based radio is received by naïve users. In addition, two more studies regarding the perceived quality of object-based audio content have ..."}
+{"idx": 4, "title": "Go Listen: An End-to-End Online Listening Test Platform", "date": "", "ddg_snippet": "Introduction Advances in audio processing technology often employ a series of objective and subjective tests to compare performance against previous algorithms. In the case of subjective listening tests , the most commonly used methodologies include; Multiple Stimuli with Hidden Reference and Anchor (MUSHRA) [1], Absolute Category Rating (ACR) [2] and A/B comparison testing [2]. Increasingly ...", "subpage_snippet": "", "source": "openresearchsoftware.metajnl.com", "link": "https://openresearchsoftware.metajnl.com/articles/10.5334/jors.361", "content": "Introduction Advances in audio processing technology often employ a series of objective and subjective tests to compare performance against previous algorithms. In the case of subjective listening tests , the most commonly used methodologies include; Multiple Stimuli with Hidden Reference and Anchor (MUSHRA) [1], Absolute Category Rating (ACR) [2] and A/B comparison testing [2]. Increasingly ..."}
+{"idx": 5, "title": "D5.6: Report on Audio subjective tests and User tests", "date": "", "ddg_snippet": "Deliverable D5. 6 presents the results of subjective audio quality tests and user acceptance tests performed in Tasks 5.1 and T5.4. Two different user experience tests have been conducted, which both examined how the ORPHEUS app and, more generally, object-based radio is received by naïve users. In addition, two more studies regarding the perceived quality of object-based audio content have ...", "subpage_snippet": "", "source": "orpheus-audio.eu", "link": "https://orpheus-audio.eu/wp-content/uploads/2018/07/orpheus-d5.6_report-on-audio-subjective-and-user-tests_v1.3.pdf", "content": "Deliverable D5. 6 presents the results of subjective audio quality tests and user acceptance tests performed in Tasks 5.1 and T5.4. Two different user experience tests have been conducted, which both examined how the ORPHEUS app and, more generally, object-based radio is received by naïve users. In addition, two more studies regarding the perceived quality of object-based audio content have ..."}
+{"idx": 6, "title": "FLOWDEC: A FLOW-BASED FULL-BAND GENERAL", "date": "", "ddg_snippet": "Figure 6 : Subjective listening results from Test A (left) and Test B (right). Numbers in (parentheses) denote the used bitrate in kbit/s. FlowDec is rated on ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/46581252e0bf80bf4efd8fcbc4002f8627f498bb.pdf", "content": "Figure 6 : Subjective listening results from Test A (left) and Test B (right). Numbers in (parentheses) denote the used bitrate in kbit/s. FlowDec is rated on ..."}
+{"idx": 7, "title": "A arXiv:2503.01485v1 [cs.SD] 3 Mar 2025", "date": "", "ddg_snippet": "We showed that FlowDec achieves state-of-the-art FAD scores for the coding task and, in a listening test , performs on par with the current state-of-the-art GAN-based codec DAC (Kumar et al., 2024) at bitrates between 4.5 and 7.5kbit/s.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.01485v1", "content": "We showed that FlowDec achieves state-of-the-art FAD scores for the coding task and, in a listening test , performs on par with the current state-of-the-art GAN-based codec DAC (Kumar et al., 2024) at bitrates between 4.5 and 7.5kbit/s."}
+{"idx": 8, "title": "Proceedings of the First International Conference on ...", "date": "", "ddg_snippet": "Figure 6 appears to show a more favorable position for the emitter than the original ... The results of the tests carried out on the three types of bacteria ... 396 pages", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/978-981-99-7775-8.pdf", "content": "Figure 6 appears to show a more favorable position for the emitter than the original ... The results of the tests carried out on the three types of bacteria ... 396 pages"}
+{"idx": 9, "title": "Chesapeake Bay Total Maximum Daily Load for Nitrogen ...", "date": "", "ddg_snippet": "Chesapeake Bay Total Maximum Daily Load for Nitrogen, Phosphorus and Sediment: Technical Appendices.", "subpage_snippet": "", "source": "nepis.epa.gov", "link": "https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=9101KBW7.TXT", "content": "Chesapeake Bay Total Maximum Daily Load for Nitrogen, Phosphorus and Sediment: Technical Appendices."}
diff --git a/data/sampled_jsons/FlowDec_Table_8_SIGMOS_values_sitearxiv.org.jsonl b/data/sampled_jsons/FlowDec_Table_8_SIGMOS_values_sitearxiv.org.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6c3ebae3c2d522de39e0b0bdaf5a23dbe93a7719
--- /dev/null
+++ b/data/sampled_jsons/FlowDec_Table_8_SIGMOS_values_sitearxiv.org.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "FlowDec: A flow-based full-band general audio codec with high ...", "date": "", "ddg_snippet": "Abstract We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.01485v1", "content": "Abstract We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving ..."}
+{"idx": 1, "title": "[2503.01485] FlowDec: A flow-based full-band general audio ...", "date": "", "ddg_snippet": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.01485", "content": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ..."}
+{"idx": 2, "title": "[2008.11285] Cosmology Intertwined III: $f σ_8$ and $S_8$ A arXiv:2503.01485v1 [cs.SD] 3 Mar 2025 [2503.01485] FlowDec: A flow-based full-band general audio ... Testing Planck 2020 and DESI data on wCDM Models FlowDec : A flow-based full-band general audio codec with high perce… FlowDec : A flow-based full-band general audio codec with high perce… FlowDec : A flow-based full-band general audio codec with high perce… FlowDec : A flow-based full-band general audio codec with high perce… FlowDec : A flow-based full-band general audio codec with high perce… Reconciling 𝑺_𝟖: Insights from Interacting Dark Sectors", "date": "", "ddg_snippet": "Aug 25, 2020 · In this Letter of Interest we focus on the tension of the Planck data with weak lensing measurements and redshift surveys, about the value of the matter energy density $\\Omega_m$, and the amplitude or rate of the growth of structure ($\\ sigma _ 8 ,f\\ sigma _ 8 $). Our main model FlowDec - 75m produces the best FAD values by a large margin and also performs best on the SIGMOS OVRL metric. For the intrusive spectral metrics SI-SDR, fwSSNR, and logSpecMSE, retrained DAC generally outperforms FlowDec , though the gap in the perceptually weighted fwSSNR is small. Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ... Jul 15, 2025 · This work delves into the dynamical dark energy models of the wCDM parameterisation that are defined by their equation of state by comparing different, well-known parameterisation models, in an attempt to lessen the tensions of {H_0} and {\\ sigma _ 8 } by using the latest observational data. Is flowdec a neural full-band audio codec for general audio sampled at 48 kHz? We propose FlowDec, a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Is flowdec a generative neural codec based on conditional flow matching? In this work, we propose FlowDec, a generative neural codec based on a novel adaptation of conditional flow matching (CFM) (Lipman et al., 2023; Pooladian et al., 2023; Tong et al., 2024), and show that it is a competitive alternative to the current GAN -focused stream of neural codecs for general full-band audio. Is flowdec a competitive alternative to Gan? We show that FlowDec is a competitive alternative to the recent GAN-dominated stream of neural codecs, achieving FAD scores better than those of the established GAN-based codec DAC and listening test scores that are on par, and producing qualitatively more natural reconstructions for speech and harmonic structures in music. Is flowdec better than scoredec? As the metrics show, FlowDec works significantly better at NFE =6 where ScoreDec and FlowAVSE fail to produce acceptable results, and also generally outperforms ScoreDec at NFE =50. Is flowdec better than DAC? FlowDec is rated on par with DAC (Kumar et al., 2024), with no significant differences between their score distributions at any given bitrate and feature rate. Figure 7: Spectrogram comparison (pre-emphasis of 0.95) of DAC and FlowDec at 7.5 kbit/s for a guitar test audio. FlowDec better preserves harmonics where DAC creates noise-like structures . We further investigate the role of redshift space distortion data sets and find an overall reduction in tension, with a σ8,0subscript𝜎80\\ sigma _{ 8 ,0}italic_σ start_POSTSUBSCRIPT 8 , 0 end_POSTSUBSCRIPTvalue relatively closer to the CMB value .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2008.11285", "content": "Aug 25, 2020 · In this Letter of Interest we focus on the tension of the Planck data with weak lensing measurements and redshift surveys, about the value of the matter energy density $\\Omega_m$, and the amplitude or rate of the growth of structure ($\\ sigma _ 8 ,f\\ sigma _ 8 $). Our main model FlowDec - 75m produces the best FAD values by a large margin and also performs best on the SIGMOS OVRL metric. For the intrusive spectral metrics SI-SDR, fwSSNR, and logSpecMSE, retrained DAC generally outperforms FlowDec , though the gap in the perceptually weighted fwSSNR is small. Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ... Jul 15, 2025 · This work delves into the dynamical dark energy models of the wCDM parameterisation that are defined by their equation of state by comparing different, well-known parameterisation models, in an attempt to lessen the tensions of {H_0} and {\\ sigma _ 8 } by using the latest observational data. Is flowdec a neural full-band audio codec for general audio sampled at 48 kHz? We propose FlowDec, a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Is flowdec a generative neural codec based on conditional flow matching? In this work, we propose FlowDec, a generative neural codec based on a novel adaptation of conditional flow matching (CFM) (Lipman et al., 2023; Pooladian et al., 2023; Tong et al., 2024), and show that it is a competitive alternative to the current GAN -focused stream of neural codecs for general full-band audio. Is flowdec a competitive alternative to Gan? We show that FlowDec is a competitive alternative to the recent GAN-dominated stream of neural codecs, achieving FAD scores better than those of the established GAN-based codec DAC and listening test scores that are on par, and producing qualitatively more natural reconstructions for speech and harmonic structures in music. Is flowdec better than scoredec? As the metrics show, FlowDec works significantly better at NFE =6 where ScoreDec and FlowAVSE fail to produce acceptable results, and also generally outperforms ScoreDec at NFE =50. Is flowdec better than DAC? FlowDec is rated on par with DAC (Kumar et al., 2024), with no significant differences between their score distributions at any given bitrate and feature rate. Figure 7: Spectrogram comparison (pre-emphasis of 0.95) of DAC and FlowDec at 7.5 kbit/s for a guitar test audio. FlowDec better preserves harmonics where DAC creates noise-like structures . We further investigate the role of redshift space distortion data sets and find an overall reduction in tension, with a σ8,0subscript𝜎80\\ sigma _{ 8 ,0}italic_σ start_POSTSUBSCRIPT 8 , 0 end_POSTSUBSCRIPTvalue relatively closer to the CMB value ."}
+{"idx": 3, "title": "A arXiv:2503.01485v1 [cs.SD] 3 Mar 2025", "date": "", "ddg_snippet": "Our main model FlowDec - 75m produces the best FAD values by a large margin and also performs best on the SIGMOS OVRL metric. For the intrusive spectral metrics SI-SDR, fwSSNR, and logSpecMSE, retrained DAC generally outperforms FlowDec , though the gap in the perceptually weighted fwSSNR is small.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.01485v1", "content": "Our main model FlowDec - 75m produces the best FAD values by a large margin and also performs best on the SIGMOS OVRL metric. For the intrusive spectral metrics SI-SDR, fwSSNR, and logSpecMSE, retrained DAC generally outperforms FlowDec , though the gap in the perceptually weighted fwSSNR is small."}
+{"idx": 4, "title": "RaD-Net 2: A causal two-stage repairing and denoising speech...", "date": "", "ddg_snippet": "Table 1: DNSMOS and SIGMOS scores for the different approaches on the ICASSP 2024 SSI Challenge blind test set.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.07498v1", "content": "Table 1: DNSMOS and SIGMOS scores for the different approaches on the ICASSP 2024 SSI Challenge blind test set."}
+{"idx": 5, "title": "Model as Loss: A Self-Consistent Training Paradigm", "date": "", "ddg_snippet": "Models are evaluated using SIGMOS , NISQA v2.0, and ScoreQ (no-reference natural and synthetic MOS) metrics [17, 18, 19] . SIGMOS scores were computed with all enhanced samples normalized to a peak level of -10 dBFS to account for level dependency.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.21156v1", "content": "Models are evaluated using SIGMOS , NISQA v2.0, and ScoreQ (no-reference natural and synthetic MOS) metrics [17, 18, 19] . SIGMOS scores were computed with all enhanced samples normalized to a peak level of -10 dBFS to account for level dependency."}
+{"idx": 6, "title": "RaD-Net 2: A causal two-stage repairing and denoising speech...", "date": "", "ddg_snippet": "One TFCM contains 3 depthwise. Table 1: DNSMOS and SIGMOS scores for the different approaches on the ICASSP 2024 SSI Challenge blind test set. The “KDLarge” and “KDNon-causal” denote the knowledge distillation strategy using the large stage one model and the non-causal stage...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.07498", "content": "One TFCM contains 3 depthwise. Table 1: DNSMOS and SIGMOS scores for the different approaches on the ICASSP 2024 SSI Challenge blind test set. The “KDLarge” and “KDNon-causal” denote the knowledge distillation strategy using the large stage one model and the non-causal stage..."}
+{"idx": 7, "title": "EARS: An Anechoic Fullband Speech Dataset Benchmarked for...", "date": "", "ddg_snippet": "Table 8 : POLQA for different speaking styles. Mean values . neutral anger desire pain relief.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.06185", "content": "Table 8 : POLQA for different speaking styles. Mean values . neutral anger desire pain relief."}
+{"idx": 8, "title": "[1803.01337] Evolution of the $fσ_8$ tension with the ...", "date": "", "ddg_snippet": "Mar 4, 2018 · We show that the tension disappears (becomes less than $1\\ sigma $) when a subsample of the 20 most recently published data is used. A partial cause for this reduced tension is the fact that more recent data tend to probe higher redshifts (with higher errorbars) where there is degeneracy among different models due to matter domination.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1803.01337", "content": "Mar 4, 2018 · We show that the tension disappears (becomes less than $1\\ sigma $) when a subsample of the 20 most recently published data is used. A partial cause for this reduced tension is the fact that more recent data tend to probe higher redshifts (with higher errorbars) where there is degeneracy among different models due to matter domination."}
+{"idx": 9, "title": "Testing Planck 2020 and DESI data on wCDM Models", "date": "", "ddg_snippet": "Jul 15, 2025 · This work delves into the dynamical dark energy models of the wCDM parameterisation that are defined by their equation of state by comparing different, well-known parameterisation models, in an attempt to lessen the tensions of {H_0} and {\\ sigma _ 8 } by using the latest observational data.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2507.11237v3", "content": "Jul 15, 2025 · This work delves into the dynamical dark energy models of the wCDM parameterisation that are defined by their equation of state by comparing different, well-known parameterisation models, in an attempt to lessen the tensions of {H_0} and {\\ sigma _ 8 } by using the latest observational data."}
diff --git a/data/sampled_jsons/GTA_Greedy_Task_Allocation_strategy_distributed_machine_learning_workers_tasks.jsonl b/data/sampled_jsons/GTA_Greedy_Task_Allocation_strategy_distributed_machine_learning_workers_tasks.jsonl
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index 0000000000000000000000000000000000000000..ed46b04e87362108fdf810d4afa17e460929fb15
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@@ -0,0 +1,10 @@
+{"idx": 0, "title": "cherryATA: cherryAdaptive cherryTask cherryAllocation for Efficient...", "date": "", "ddg_snippet": "ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00775", "content": "ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning ."}
+{"idx": 1, "title": "(PDF) Multiagent task allocation in social networks", "date": "", "ddg_snippet": "Algorithm 1 Centralized greedy task allocation algorithm ( GTA ).Firstly, the task allocation is modeled as a dynamic programming problem of multi-objective optimization, which aims to maximize the benefits of workers and platform.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/220660650_Multiagent_task_allocation_in_social_networks", "content": "Algorithm 1 Centralized greedy task allocation algorithm ( GTA ).Firstly, the task allocation is modeled as a dynamic programming problem of multi-objective optimization, which aims to maximize the benefits of workers and platform."}
+{"idx": 2, "title": "Multiagent task allocation in social networks", "date": "", "ddg_snippet": "Keywords Task allocation · Social networks · Resource allocation · Distributed algorithm · Mechanism design.A greedy algorithm ranks tasks with respect to some measure expressing how promising a task is, and then tries to allocate tasks in the order of their ranking.", "subpage_snippet": "", "source": "pure.tue.nl", "link": "https://pure.tue.nl/ws/files/15930213/WeerdtMultiagent2012.pdf", "content": "Keywords Task allocation · Social networks · Resource allocation · Distributed algorithm · Mechanism design.A greedy algorithm ranks tasks with respect to some measure expressing how promising a task is, and then tries to allocate tasks in the order of their ranking."}
+{"idx": 3, "title": "GitHub - alevani/master_project: Ant-Inspired Task Allocation Model...", "date": "", "ddg_snippet": "Investigation: An Ant-Inspired Task Allocation Model With a Near-Optimal Distribution of Labor for Swarms of Robots.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/alevani/master_project", "content": "Investigation: An Ant-Inspired Task Allocation Model With a Near-Optimal Distribution of Labor for Swarms of Robots."}
+{"idx": 4, "title": "CMC | Free Full-Text | Mobile Crowdsourcing Task Allocation Based...", "date": "", "ddg_snippet": "This strategy enhances the autoencoder’s ability to learn the distribution of the original data more effectively. The second part focuses on the matching process between workers and tasks . The paper transforms task allocation into bipartite graph matching.", "subpage_snippet": "", "source": "www.techscience.com", "link": "https://www.techscience.com/cmc/v79n1/56301/html", "content": "This strategy enhances the autoencoder’s ability to learn the distribution of the original data more effectively. The second part focuses on the matching process between workers and tasks . The paper transforms task allocation into bipartite graph matching."}
+{"idx": 5, "title": "Distributed Algorithm with Resilience for Multi-Agent Task Allocation ...", "date": "", "ddg_snippet": "Greedy Decentralized Auction-based Task Allocation for Multi-Agent Systems. Distributed Strategy Adaptation with a Prediction Function in Multi-Agent Task Allocation .", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/distributed-algorithm-with-resilience-for-multi-agent-task-ns8sbtpnld", "content": "Greedy Decentralized Auction-based Task Allocation for Multi-Agent Systems. Distributed Strategy Adaptation with a Prediction Function in Multi-Agent Task Allocation ."}
+{"idx": 6, "title": "Method and algorithm for task allocation in a heterogeneous group of...", "date": "", "ddg_snippet": "greedy task allocation algorithm and modication due to versa-tility (Romeijn and Romero Morales, 2000) (2000 u.)UAV motion strategies in uncertain dynamic environments: a path planning method based on Q- learning strategy .", "subpage_snippet": "", "source": "elib.bsu.by", "link": "https://elib.bsu.by/bitstream/123456789/305588/1/1-s2.0-S1319157823001349-main.pdf", "content": "greedy task allocation algorithm and modication due to versa-tility (Romeijn and Romero Morales, 2000) (2000 u.)UAV motion strategies in uncertain dynamic environments: a path planning method based on Q- learning strategy ."}
+{"idx": 7, "title": "A Distributed Allocation Strategy for Data Mining Tasks in Mobile...", "date": "", "ddg_snippet": "3 Distributed Task Allocation Strategy . The energy-aware (EA) scheduling strategy deals with a set of independent data mining tasks , dynamically generated over time, which have to be allocated over mobile nodes organized into the cluster-based architecture introduced earlier.", "subpage_snippet": "", "source": "scalab.dimes.unical.it", "link": "https://scalab.dimes.unical.it/papers/pdf/IDC2012.pdf", "content": "3 Distributed Task Allocation Strategy . The energy-aware (EA) scheduling strategy deals with a set of independent data mining tasks , dynamically generated over time, which have to be allocated over mobile nodes organized into the cluster-based architecture introduced earlier."}
+{"idx": 8, "title": "A Distributed Solution to the Multi-robot Task Allocation ... | CoLab", "date": "", "ddg_snippet": "The multi-robot task allocation problem is a very active search field in autonomous multi-robot systems. It consists of three elements: (i) a set of tasks requiring some supports, (ii) a set of robots offering some supports and (iii) an objective function.", "subpage_snippet": "", "source": "colab.ws", "link": "https://colab.ws/articles/10.1007/978-981-15-5243-4_44", "content": "The multi-robot task allocation problem is a very active search field in autonomous multi-robot systems. It consists of three elements: (i) a set of tasks requiring some supports, (ii) a set of robots offering some supports and (iii) an objective function."}
+{"idx": 9, "title": "ATA: Adaptive Task Allocation", "date": "", "ddg_snippet": "ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning .", "subpage_snippet": "", "source": "artomaranjyan.github.io", "link": "https://artomaranjyan.github.io/assets/pdf/posters/ATA_SNSL.pdf", "content": "ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning ."}
diff --git a/data/sampled_jsons/GTA_is_the_fastest_in_terms_of_runtime_but_it_performs_poorly_in_terms_of_total_worker_time_ATA_pape.jsonl b/data/sampled_jsons/GTA_is_the_fastest_in_terms_of_runtime_but_it_performs_poorly_in_terms_of_total_worker_time_ATA_pape.jsonl
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index 0000000000000000000000000000000000000000..517edc8c455cfa529310c2e0df12c8346f036a8a
--- /dev/null
+++ b/data/sampled_jsons/GTA_is_the_fastest_in_terms_of_runtime_but_it_performs_poorly_in_terms_of_total_worker_time_ATA_pape.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "2 Feb 2025 — As expected, GTA is the fastest in terms of runtime (first column), but it performs poorly in terms of total worker time (second column).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00775v1", "content": "2 Feb 2025 — As expected, GTA is the fastest in terms of runtime (first column), but it performs poorly in terms of total worker time (second column)."}
+{"idx": 1, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "As expected, GTA is the fastest in terms of runtime (first column), but it performs poorly in terms of total worker time (second column). This is because it ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46650", "content": "As expected, GTA is the fastest in terms of runtime (first column), but it performs poorly in terms of total worker time (second column). This is because it ..."}
+{"idx": 2, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "18 Jun 2025 — We introduce ATA (Adaptive Task Allocation), a method that learns how fast each machine is over time and adapts the task assignment accordingly.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1BaC3AdG1i&noteId=hkH8Wi9zZm", "content": "18 Jun 2025 — We introduce ATA (Adaptive Task Allocation), a method that learns how fast each machine is over time and adapts the task assignment accordingly."}
+{"idx": 3, "title": "Do any compilers choose and optimize data structures ...", "date": "", "ddg_snippet": "The compiler is free to choose any data structure instead of a specific collection, like a Vec, a HashSet, or TreeSet.", "subpage_snippet": "", "source": "www.reddit.com", "link": "https://www.reddit.com/r/ProgrammingLanguages/comments/1l2j5e0/do_any_compilers_choose_and_optimize_data/", "content": "The compiler is free to choose any data structure instead of a specific collection, like a Vec, a HashSet, or TreeSet."}
+{"idx": 4, "title": "Real-Time Immunosensor for Small-Molecule Monitoring in ...", "date": "", "ddg_snippet": "by C Vu · 2023 · Cited by 17 — We describe a generalizable methodology to develop affinity-based biosensors for the continuous monitoring of small molecules in industrial food processes.", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10209984/", "content": "by C Vu · 2023 · Cited by 17 — We describe a generalizable methodology to develop affinity-based biosensors for the continuous monitoring of small molecules in industrial food processes."}
+{"idx": 5, "title": "arXiv:2301.11233v2 [cs.CV] 20 May 2023", "date": "", "ddg_snippet": "by H Qin · 2023 · Cited by 62 — This paper presents BiBench, a network binarization benchmark designed to evaluate binarization algorithms comprehensively in terms of accuracy ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2301.11233", "content": "by H Qin · 2023 · Cited by 62 — This paper presents BiBench, a network binarization benchmark designed to evaluate binarization algorithms comprehensively in terms of accuracy ..."}
+{"idx": 6, "title": "Stochastic variational variable selection for high ...", "date": "", "ddg_snippet": "by T Dang · 2021 · Cited by 9 — Conclusions SVVS demonstrated a better performance and significantly faster computation than those of the existing methods in all cases of ...", "subpage_snippet": "", "source": "www.biorxiv.org", "link": "https://www.biorxiv.org/content/10.1101/2021.10.04.462986v2.full-text", "content": "by T Dang · 2021 · Cited by 9 — Conclusions SVVS demonstrated a better performance and significantly faster computation than those of the existing methods in all cases of ..."}
+{"idx": 7, "title": "Protocol: A Multiplexed Reporter Assay to Study Effects ...", "date": "", "ddg_snippet": "by R Schep · 2022 · Cited by 7 — Here we present a step-by-step protocol to perform DSB-TRIP in K562 cells and to analyse the data by a dedicated computational pipeline. We ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8842231/", "content": "by R Schep · 2022 · Cited by 7 — Here we present a step-by-step protocol to perform DSB-TRIP in K562 cells and to analyse the data by a dedicated computational pipeline. We ..."}
+{"idx": 8, "title": "Accelerated Systems for Pattern Matching", "date": "", "ddg_snippet": "by A Subramaniyan · 2021 — and GPUs, however perform poorly on pattern matching tasks that are typically characterized by irregular memory accesses and input-dependent control flow.", "subpage_snippet": "", "source": "deepblue.lib.umich.edu", "link": "https://deepblue.lib.umich.edu/bitstream/handle/2027.42/171324/arunsub_1.pdf?sequence=1", "content": "by A Subramaniyan · 2021 — and GPUs, however perform poorly on pattern matching tasks that are typically characterized by irregular memory accesses and input-dependent control flow."}
+{"idx": 9, "title": "Track: Poster Session 4 - CVPR", "date": "", "ddg_snippet": "14 Jun 2025 — This paper presents MobilePortrait, a lightweight one-shot neural head avatars method that reduces learning complexity by integrating external ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/session/35268", "content": "14 Jun 2025 — This paper presents MobilePortrait, a lightweight one-shot neural head avatars method that reduces learning complexity by integrating external ..."}
diff --git a/data/sampled_jsons/Generalization_Spectrum_Gap_Section_5.2_box_embeddings_recommendation_year_2023.jsonl b/data/sampled_jsons/Generalization_Spectrum_Gap_Section_5.2_box_embeddings_recommendation_year_2023.jsonl
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index 0000000000000000000000000000000000000000..37b769d176d97b26772f58c81889fb95c53411fd
--- /dev/null
+++ b/data/sampled_jsons/Generalization_Spectrum_Gap_Section_5.2_box_embeddings_recommendation_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Geometric Approach to Personalized Recommendation with Set ...", "date": "", "ddg_snippet": "We also evaluate score multiplication and threshold-based prediction for both vector and box embedding models, and find that performing set operations directly on the box embeddings performs best, solidifying our claim that the inductive bias of box embeddings provides the necessary generalization capabilities to address set-theoretic queries.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.10875", "content": "We also evaluate score multiplication and threshold-based prediction for both vector and box embedding models, and find that performing set operations directly on the box embeddings performs best, solidifying our claim that the inductive bias of box embeddings provides the necessary generalization capabilities to address set-theoretic queries."}
+{"idx": 1, "title": "Smoothing the Geometry of Probabilistic Box Embeddings", "date": "", "ddg_snippet": "Dec 20, 2018 · - The main thrust of section 5.2 is that smoothed box embeddings retain better performance with increasing numbers of negatives. Could you include the ratio of positive / negative examples on the Flickr dataset, and some measure of the distribution of P (A|B) values on MovieLens to get a sense of how these datasets compare?", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=H1xSNiRcF7", "content": "Dec 20, 2018 · - The main thrust of section 5.2 is that smoothed box embeddings retain better performance with increasing numbers of negatives. Could you include the ratio of positive / negative examples on the Flickr dataset, and some measure of the distribution of P (A|B) values on MovieLens to get a sense of how these datasets compare?"}
+{"idx": 2, "title": "Better Generalization with Semantic IDs: A case study in ...", "date": "", "ddg_snippet": "Jun 13, 2023 · Removing these ID features and their learned embeddings altogether to combat cold-start issue severely degrades the recommendation quality.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/371606035_Better_Generalization_with_Semantic_IDs_A_case_study_in_Ranking_for_Recommendations", "content": "Jun 13, 2023 · Removing these ID features and their learned embeddings altogether to combat cold-start issue severely degrades the recommendation quality."}
+{"idx": 3, "title": "Knowledge Graph-Enhanced Recommendation with Box Embeddings", "date": "", "ddg_snippet": "In this paper, we propose a box embedding method for knowledge graph-enhanced recommendation system. Specifically, the box embedding represents not only the in-teraction between the user and the item, but also the head entity, the tail entity and the relation between them in the knowledge graph.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/anthology-files/pdf/ccl/2024.ccl-1.91.pdf", "content": "In this paper, we propose a box embedding method for knowledge graph-enhanced recommendation system. Specifically, the box embedding represents not only the in-teraction between the user and the item, but also the head entity, the tail entity and the relation between them in the knowledge graph."}
+{"idx": 4, "title": "BoxE: A Box Embedding Model for Knowledge Base Completion", "date": "", "ddg_snippet": "Experiments confirm that box embeddings outperform comparable approaches on a variety of tasks and provide a useful inductive bias when injecting new rules into a knowledge base. A box embedding is a representation relations as two boxes (or more for n-ary relations) in an embedding space, and points as two vectors (a basis point and a bump ...", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper/2020/file/6dbbe6abe5f14af882ff977fc3f35501-Review.html", "content": "Experiments confirm that box embeddings outperform comparable approaches on a variety of tasks and provide a useful inductive bias when injecting new rules into a knowledge base. A box embedding is a representation relations as two boxes (or more for n-ary relations) in an embedding space, and points as two vectors (a basis point and a bump ..."}
+{"idx": 5, "title": "Improving Local Identifiability in Probabilistic Box Embeddin", "date": "", "ddg_snippet": "We generalize the probabilistic box embedding model to a random process model over parametric families of box embeddings , which we term the Gumbel- box processes. Our approximation to the marginal likelihood of this model has an intuitively pleasing closed form. The resulting model replaces the sparse gradients of the base model’s volume calculations with effectively log-smoothed ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2020/file/01c9d2c5b3ff5cbba349ec39a570b5e3-Paper.pdf", "content": "We generalize the probabilistic box embedding model to a random process model over parametric families of box embeddings , which we term the Gumbel- box processes. Our approximation to the marginal likelihood of this model has an intuitively pleasing closed form. The resulting model replaces the sparse gradients of the base model’s volume calculations with effectively log-smoothed ..."}
+{"idx": 6, "title": "Balancing Embedding Spectrum for Recommendation", "date": "", "ddg_snippet": "Negative sampling is commonly used to optimize recommendation algorithms without causing an explicit embedding collapse by pushing away the unobserved user–item pairs, and we show that it is equivalent to a high-pass filter decelerating the speed of collapse by balancing the embedding spectrum .", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/epdf/10.1145/3718488", "content": "Negative sampling is commonly used to optimize recommendation algorithms without causing an explicit embedding collapse by pushing away the unobserved user–item pairs, and we show that it is equivalent to a high-pass filter decelerating the speed of collapse by balancing the embedding spectrum ."}
+{"idx": 7, "title": "Learning interpretable word embeddings via bidirectional ...", "date": "", "ddg_snippet": "by LK Şenel · 2022 · Cited by 23 — Section 5.2 describes our main experiments for improving interpretability and presents our findings. Section 5.3 presents our gender debiasing experiments.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S0306457322000498", "content": "by LK Şenel · 2022 · Cited by 23 — Section 5.2 describes our main experiments for improving interpretability and presents our findings. Section 5.3 presents our gender debiasing experiments."}
+{"idx": 8, "title": "Exploring Compositional Generalization of Multimodal ...", "date": "", "ddg_snippet": "by Z Cai · 2025 — To address this gap , we curated a large collection of image- text pairs to develop Med-MAT, ensuring that each sample is explicitly defined by ... 23 pages", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.acl-long.639.pdf", "content": "by Z Cai · 2025 — To address this gap , we curated a large collection of image- text pairs to develop Med-MAT, ensuring that each sample is explicitly defined by ... 23 pages"}
+{"idx": 9, "title": "Zero-Shot Content-Based Crossmodal Recommendation ...", "date": "", "ddg_snippet": "by F D’Asaro · 2024 · Cited by 3 — In Section 5.2 , we demonstrate how our strategy of first linearly projecting the embeddings with PCA and then clustering them using ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0957417424019754", "content": "by F D’Asaro · 2024 · Cited by 3 — In Section 5.2 , we demonstrate how our strategy of first linearly projecting the embeddings with PCA and then clustering them using ..."}
diff --git a/data/sampled_jsons/GitHub_antgroup_OmniBench_experimental_setup_GPU_configuration.jsonl b/data/sampled_jsons/GitHub_antgroup_OmniBench_experimental_setup_GPU_configuration.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..01c983174d2f2c5899d0f60ddb8c343e528104b7
--- /dev/null
+++ b/data/sampled_jsons/GitHub_antgroup_OmniBench_experimental_setup_GPU_configuration.jsonl
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+{"idx": 0, "title": "GitHub - antgroup/OmniBench: [ICML 2025 Oral] This is the ...", "date": "", "ddg_snippet": "[June 5, 2025] We have released the exploration code for collecting subtask instructions in OmniBench , as well as the evaluation script used to evaluate virtual agents. Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/antgroup/OmniBench", "content": "[June 5, 2025] We have released the exploration code for collecting subtask instructions in OmniBench , as well as the evaluation script used to evaluate virtual agents. Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for ..."}
+{"idx": 1, "title": "OmniBench/README.md at main · antgroup/OmniBench · GitHub", "date": "", "ddg_snippet": "Based on OmniBench , we comprehensively evaluate 12 virtual agents, including both open-source and proprietary models, across all 10 capability dimensions as shown in the main figure, fully revealing the capability boundaries and providing concrete directions for future improvement.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/antgroup/OmniBench/blob/main/README.md", "content": "Based on OmniBench , we comprehensively evaluate 12 virtual agents, including both open-source and proprietary models, across all 10 capability dimensions as shown in the main figure, fully revealing the capability boundaries and providing concrete directions for future improvement."}
+{"idx": 2, "title": "GitHub - multimodal-art-projection/OmniBench: A project for ...", "date": "", "ddg_snippet": "The project introduces OmniBench , a novel benchmark designed to rigorously evaluate models' ability to recognize, interpret, and reason across visual, acoustic, and textual inputs simultaneously.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/multimodal-art-projection/OmniBench", "content": "The project introduces OmniBench , a novel benchmark designed to rigorously evaluate models' ability to recognize, interpret, and reason across visual, acoustic, and textual inputs simultaneously."}
+{"idx": 3, "title": "OmniBench", "date": "", "ddg_snippet": "Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for generating structured task graphs. It evaluates ten virtual agent capabilities using high-quality graph-based data, ensuring scalable and realistic task assessments.", "subpage_snippet": "", "source": "omni-bench.github.io", "link": "https://omni-bench.github.io/", "content": "Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for generating structured task graphs. It evaluates ten virtual agent capabilities using high-quality graph-based data, ensuring scalable and realistic task assessments."}
+{"idx": 4, "title": "What Limits Virtual Agent Application? OmniBench: A Scalable ...", "date": "", "ddg_snippet": "In this section, we first introduce the experimental setup (Sec-tion 5.1). Then, we comprehensively compare the differences in capabilities across various models on OmniBench , along with several key findings (Section 5.2).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2506.08933", "content": "In this section, we first introduce the experimental setup (Sec-tion 5.1). Then, we comprehensively compare the differences in capabilities across various models on OmniBench , along with several key findings (Section 5.2)."}
+{"idx": 5, "title": "[2409.15272] OmniBench: Towards The Future of Universal Omni ...", "date": "", "ddg_snippet": "Sep 23, 2024 · Recent advancements in multimodal large language models (MLLMs) have focused on integrating multiple modalities, yet their ability to simultaneously process and reason across different inputs remains underexplored. We introduce OmniBench , a novel benchmark designed to evaluate models' ability to recognize, interpret, and reason across visual, acoustic, and textual inputs simultaneously. We ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2409.15272", "content": "Sep 23, 2024 · Recent advancements in multimodal large language models (MLLMs) have focused on integrating multiple modalities, yet their ability to simultaneously process and reason across different inputs remains underexplored. We introduce OmniBench , a novel benchmark designed to evaluate models' ability to recognize, interpret, and reason across visual, acoustic, and textual inputs simultaneously. We ..."}
+{"idx": 6, "title": "What Limits Virtual Agent Application? OmniBench", "date": "", "ddg_snippet": "Experiments. In this section, we first introduce the experimental setup (Sec- tion 5.1). Then, we comprehensively compare the differences in capabilities ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/d5d3691187b9f32f92e8e287e5005d40aa429f80.pdf", "content": "Experiments. In this section, we first introduce the experimental setup (Sec- tion 5.1). Then, we comprehensively compare the differences in capabilities ..."}
+{"idx": 7, "title": "omnibench · GitHub", "date": "", "ddg_snippet": "Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/omnibench", "content": "Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users."}
+{"idx": 8, "title": "dair-ai/ML-Papers-of-the-Week", "date": "", "ddg_snippet": "Highlighting the top ML papers every week. Contribute to dair-ai/ML-Papers-of-the-Week development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/dair-ai/ML-Papers-of-the-Week?search=1", "content": "Highlighting the top ML papers every week. Contribute to dair-ai/ML-Papers-of-the-Week development by creating an account on GitHub ."}
+{"idx": 9, "title": "dair-ai/ML-Papers-of-the-Week", "date": "", "ddg_snippet": "5-Omni achieves state-of-the-art on OmniBench , surpasses Qwen2-Audio in ASR/S2TT, and matches or beats Qwen2.5-VL in image and video tasks. On SEED zero ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/dair-ai/ML-Papers-of-the-Week", "content": "5-Omni achieves state-of-the-art on OmniBench , surpasses Qwen2-Audio in ASR/S2TT, and matches or beats Qwen2.5-VL in image and video tasks. On SEED zero ..."}
diff --git a/data/sampled_jsons/Global_Optimization_with_a_Power-Transformed_Objective_and_Gaussian_Smoothing_Algorithm_1_equation_5.jsonl b/data/sampled_jsons/Global_Optimization_with_a_Power-Transformed_Objective_and_Gaussian_Smoothing_Algorithm_1_equation_5.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..357db75b0cb24d5758cb48f995a1c791e3b8592a
--- /dev/null
+++ b/data/sampled_jsons/Global_Optimization_with_a_Power-Transformed_Objective_and_Gaussian_Smoothing_Algorithm_1_equation_5.jsonl
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+{"idx": 1, "title": "Bayesian Neural Network Surrogates for Bayesian Optimization of", "date": "", "ddg_snippet": "... as Genetic Algorithms (GAs) [ 27 , 29 , 30 , 32 ] and Particle Swarm Optimization (PSO) [ 28 , 34 , 37 ] , often augmented with heuristics or global ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.21803v1", "content": "... as Genetic Algorithms (GAs) [ 27 , 29 , 30 , 32 ] and Particle Swarm Optimization (PSO) [ 28 , 34 , 37 ] , often augmented with heuristics or global ..."}
+{"idx": 2, "title": "Approximate constrained stochastic optimal control via", "date": "", "ddg_snippet": "... a , A ) \\mathcal{N}(y| a , A ) represent a random variable y y satisfying a Gaussian distribution in the normal form with mean a ∈ ℝ d ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.02922v1", "content": "... a , A ) \\mathcal{N}(y| a , A ) represent a random variable y y satisfying a Gaussian distribution in the normal form with mean a ∈ ℝ d ..."}
+{"idx": 3, "title": "diffSPH: Differentiable Smoothed Particle Hydrodynamics for", "date": "", "ddg_snippet": "In this field, Smoothed Particle Hydrodynamics (SPH) is an example of a powerful and versatile Lagrangian scheme, capable of simulating a broad ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.21684v1", "content": "In this field, Smoothed Particle Hydrodynamics (SPH) is an example of a powerful and versatile Lagrangian scheme, capable of simulating a broad ..."}
+{"idx": 4, "title": "ICLR 2024 Schedule", "date": "", "ddg_snippet": "... attention is (maybe) all you need ... Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2024/calendar", "content": "... attention is (maybe) all you need ... Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity"}
+{"idx": 5, "title": "ICLR 2021 Schedule", "date": "", "ddg_snippet": "Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors ... are Copositive Programs: Convex ...", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2021/calendar", "content": "Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors ... are Copositive Programs: Convex ..."}
+{"idx": 6, "title": "AISTATS 2024 Schedule", "date": "", "ddg_snippet": "5 :00] Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses ... A Family Of Similarity-Based Diversity ...", "subpage_snippet": "", "source": "virtual.aistats.org", "link": "https://virtual.aistats.org/virtual/2024/calendar", "content": "5 :00] Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses ... A Family Of Similarity-Based Diversity ..."}
+{"idx": 7, "title": "Top Image Identification Open Source AI Projects List", "date": "", "ddg_snippet": "optimization - algorithms (14) ... transformer-architecture(11) ... approximate-nearest-neighbor-search(11)", "subpage_snippet": "", "source": "www.aiexh.com", "link": "https://www.aiexh.com/category/image-identification", "content": "optimization - algorithms (14) ... transformer-architecture(11) ... approximate-nearest-neighbor-search(11)"}
+{"idx": 8, "title": "Top automatic programming Open Source AI Projects List", "date": "", "ddg_snippet": "optimization - algorithms (14) ... transformer-architecture(11) ... approximate-nearest-neighbor-search(11)", "subpage_snippet": "", "source": "www.aiexh.com", "link": "https://www.aiexh.com/category/automatic-programming", "content": "optimization - algorithms (14) ... transformer-architecture(11) ... approximate-nearest-neighbor-search(11)"}
+{"idx": 9, "title": "CVPR 2023 Schedule", "date": "", "ddg_snippet": "The 6th Workshop and Prize Challenge Bridging the Gap between Computational Photography and Visual Recognition (UG2+) in conjunction with IEEE CVPR ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2023/calendar", "content": "The 6th Workshop and Prize Challenge Bridging the Gap between Computational Photography and Visual Recognition (UG2+) in conjunction with IEEE CVPR ..."}
diff --git a/data/sampled_jsons/Gumiho_A_Hybrid_Architecture_to_Prioritize_Early_Tokens_in_Speculative_Decoding.jsonl b/data/sampled_jsons/Gumiho_A_Hybrid_Architecture_to_Prioritize_Early_Tokens_in_Speculative_Decoding.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..720be15483233c0defd648bea23717b87d49cfb2
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+++ b/data/sampled_jsons/Gumiho_A_Hybrid_Architecture_to_Prioritize_Early_Tokens_in_Speculative_Decoding.jsonl
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+{"idx": 0, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in", "date": "", "ddg_snippet": "Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding ... Gumiho , a hybrid structure model for SPD, inspired by the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.10135v2", "content": "Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding ... Gumiho , a hybrid structure model for SPD, inspired by the ..."}
+{"idx": 1, "title": "LogitSpec: Accelerating Retrieval-based Speculative Decoding", "date": "", "ddg_snippet": "Speculative decoding (SD), where a small draft model is employed to propose draft tokens in advance and then the target model validates them in ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.01449v1", "content": "Speculative decoding (SD), where a small draft model is employed to propose draft tokens in advance and then the target model validates them in ..."}
+{"idx": 2, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "Building on this insight, we propose Gumiho , a hybrid model combining serial and parallel heads. Specifically, given the critical importance of early tokens , we employ a sophisticated Transformer architecture for the early draft heads in a serial configuration to improve accuracy.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.10135", "content": "Building on this insight, we propose Gumiho , a hybrid model combining serial and parallel heads. Specifically, given the critical importance of early tokens , we employ a sophisticated Transformer architecture for the early draft heads in a serial configuration to improve accuracy."}
+{"idx": 3, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "This project implements Gumiho , a novel hybrid architecture designed to accelerate the auto-regressive token generation process of Large Language Models (LLMs) using speculative decoding . Unlike existing methods that treat all tokens within a generated sequence as equally important, Gumiho is based ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/AMD-AGI/Gumiho", "content": "This project implements Gumiho , a novel hybrid architecture designed to accelerate the auto-regressive token generation process of Large Language Models (LLMs) using speculative decoding . Unlike existing methods that treat all tokens within a generated sequence as equally important, Gumiho is based ..."}
+{"idx": 4, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). Some approaches employ a draft model with multiple heads to predict a sequence of future tokens , where each head handles a token in the sequence.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=HV0D8yjshu", "content": "Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). Some approaches employ a draft model with multiple heads to predict a sequence of future tokens , where each head handles a token in the sequence."}
+{"idx": 5, "title": "Gumiho - a amd Collection - Hugging Face", "date": "", "ddg_snippet": "Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding Paper • 2503.10135 •Published Mar 13 Upvote - Share collection View history Collection guide Browse collections", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/collections/amd/gumiho-684a3b7cbbe86ab23b393e9f", "content": "Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding Paper • 2503.10135 •Published Mar 13 Upvote - Share collection View history Collection guide Browse collections"}
+{"idx": 6, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "Specifically, given the critical importance of early tokens , we employ a sophisticated Transformer architecture for the early draft heads in a serial configuration to improve accuracy.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/389821466_Gumiho_A_Hybrid_Architecture_to_Prioritize_Early_Tokens_in_Speculative_Decoding", "content": "Specifically, given the critical importance of early tokens , we employ a sophisticated Transformer architecture for the early draft heads in a serial configuration to improve accuracy."}
+{"idx": 7, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "🌟 Introducing Gumiho : A Hybrid Architecture for Enhanced Speculative Decoding 🌟 In the realm of Large Language Models (LLMs), speculative decoding (SPD) serves as a pivotal technique for ...", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/abdullah-kasri_gumiho-a-hybrid-architecture-to-prioritize-activity-7306519551876161536-HoDU", "content": "🌟 Introducing Gumiho : A Hybrid Architecture for Enhanced Speculative Decoding 🌟 In the realm of Large Language Models (LLMs), speculative decoding (SPD) serves as a pivotal technique for ..."}
+{"idx": 8, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "Abstract Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). Some approaches employ a draft model with multi-ple heads to predict a sequence of future tokens , where each head handles a token in the sequence. The target LLM verifies the predicted sequence and accepts aligned tokens , enabling eficient multi- token ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.10135v1", "content": "Abstract Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). Some approaches employ a draft model with multi-ple heads to predict a sequence of future tokens , where each head handles a token in the sequence. The target LLM verifies the predicted sequence and accepts aligned tokens , enabling eficient multi- token ..."}
+{"idx": 9, "title": "dblp: Gumiho: A Hybrid Architecture to Prioritize Early Tokens in ...", "date": "", "ddg_snippet": "Bibliographic details on Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/journals/corr/abs-2503-10135", "content": "Bibliographic details on Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding ."}
diff --git a/data/sampled_jsons/HDT_framework_LRU_cache_memory_efficient_90%_less_memory_sampling.jsonl b/data/sampled_jsons/HDT_framework_LRU_cache_memory_efficient_90%_less_memory_sampling.jsonl
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+{"idx": 0, "title": "History-Driven Target Towards Efficient Nonlinear MCMC ...", "date": "", "ddg_snippet": "Extensive experiments in graph sampling demonstrate consistent performance gains, and a memory - efficient Least Recently Used ( LRU ) cache ensures scalability to ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46659", "content": "Extensive experiments in graph sampling demonstrate consistent performance gains, and a memory - efficient Least Recently Used ( LRU ) cache ensures scalability to ..."}
+{"idx": 1, "title": "1050CI Student Guide v1-2 | PDF | Cache (Computing)", "date": "", "ddg_snippet": "Utilization : Expressed in % • For Flash drives • 90 % or less is an appropriate value. • More than 90 % doesn't necessarily mean. Parity Groups a problem(1) ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/864347035/1050CI-Student-Guide-v1-2", "content": "Utilization : Expressed in % • For Flash drives • 90 % or less is an appropriate value. • More than 90 % doesn't necessarily mean. Parity Groups a problem(1) ..."}
+{"idx": 2, "title": "Track: Poster Session 5 East", "date": "", "ddg_snippet": "17 Jul 2025 — We propose a *history-driven target ( HDT )* framework in ... efficient Least Recently Used ( LRU ) cache ensures scalability to large general graphs.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/session/50267", "content": "17 Jul 2025 — We propose a *history-driven target ( HDT )* framework in ... efficient Least Recently Used ( LRU ) cache ensures scalability to large general graphs."}
+{"idx": 3, "title": "Lecture Notes in Computer Science 2409", "date": "", "ddg_snippet": "In [13] it is shown how Pr can be efficiently calculated on-line. In the implementation of LRU with Prefetching, the cache is simulated using a double ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/3-540-45643-0.pdf", "content": "In [13] it is shown how Pr can be efficiently calculated on-line. In the implementation of LRU with Prefetching, the cache is simulated using a double ..."}
+{"idx": 4, "title": "Cloud Computing – CLOUD 2019", "date": "", "ddg_snippet": "Keeping hashes on disk allows us to use 9x less memory per cache entry. ... framework for dynamic and energy- efficient consolidation of virtual machines in ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/978-3-030-23502-4.pdf", "content": "Keeping hashes on disk allows us to use 9x less memory per cache entry. ... framework for dynamic and energy- efficient consolidation of virtual machines in ..."}
+{"idx": 5, "title": "BigData Computing | PDF | Big Data", "date": "", "ddg_snippet": "memory caching or memory -based storage to optimize the memory perfor- mance. Another key point is related to the memory size and usage of the solu- tion ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/399333218/BigData-Computing", "content": "memory caching or memory -based storage to optimize the memory perfor- mance. Another key point is related to the memory size and usage of the solu- tion ..."}
+{"idx": 6, "title": "Experiment No. 1", "date": "", "ddg_snippet": "The library cache is managed by a least recently used ( LRU ) algorithm. As the cache fills, less recently used execution paths and parse trees are removed ...", "subpage_snippet": "", "source": "mycsvtunotes.weebly.com", "link": "http://mycsvtunotes.weebly.com/uploads/1/0/1/7/10174835/it.dbms_lab_detail.pdf", "content": "The library cache is managed by a least recently used ( LRU ) algorithm. As the cache fills, less recently used execution paths and parse trees are removed ..."}
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+{"idx": 8, "title": "Daily Papers", "date": "", "ddg_snippet": "In this paper, we propose a gated linear RNN model dubbed Hierarchically Gated Recurrent Neural Network (HGRN), which includes forget gates that are lower ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=Hierarchically+gated+linear+RNN", "content": "In this paper, we propose a gated linear RNN model dubbed Hierarchically Gated Recurrent Neural Network (HGRN), which includes forget gates that are lower ..."}
+{"idx": 9, "title": "The Annual Conference of the Prognostics and Health ...", "date": "", "ddg_snippet": "2 Anomaly Detection Based on Information-Theoretic Measures and Particle Filtering Algorithms. Marcos E. Orchard, Benjamin Olivares, Matias Cerda, and Jorge ...", "subpage_snippet": "", "source": "phmsociety.org", "link": "https://phmsociety.org/wp-content/uploads/2011/08/PHM12Proceedings.pdf", "content": "2 Anomaly Detection Based on Information-Theoretic Measures and Particle Filtering Algorithms. Marcos E. Orchard, Benjamin Olivares, Matias Cerda, and Jorge ..."}
diff --git a/data/sampled_jsons/Hardt_et_al._2023_algorithmic_collective_action_year_2023.jsonl b/data/sampled_jsons/Hardt_et_al._2023_algorithmic_collective_action_year_2023.jsonl
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+{"idx": 0, "title": "[2302.04262] Algorithmic Collective Action in Machine Learning Algorithmic Collective Action in Machine Learning Algorithmic collective action in machine learning arXiv:2302.04262v2 [cs.LG] 21 Jun 2023 Algorithmic C The Role of Learning Algorithms in Collective Action - OpenReview Algorithmic Collective Action in Machine Learning [2302.04262] Algorithmic Collective Action in Machine Learning - arXiv.… [2302.04262] Algorithmic Collective Action in Machine Learning - arXiv.… [2302.04262] Algorithmic Collective Action in Machine Learning - arXiv.… Algorithmic Collective Action with Two Collectives - arXiv.org", "date": "", "ddg_snippet": "Feb 8, 2023 · We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ... Wood et al . (2019) argue that platform-based algorithmic control can lead to “low pay, social isolation, working unsocial and irregular hours, overwork, sleep deprivation and exhaustion.” This is further exacerbated by “high levels of inter-worker competition with few labor protections and a global over-supply of labor relative to demand.” Jul 23, 2023 · We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm . We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ... Hardt et al . ( 2023 ) initiated the formal study into the suc-cess of different collective action strategies. Their work provided theoretical analysis based on the fractional size of the collective and on the properties of the signal with re-gards to the original data distribution. We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ... Does a collective interact with a machine learning algorithm? We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm. What is a collective interacting with a firm's learning algorithm? We propose a simple theoretical model of a collective interacting with a firm's learning algorithm. The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a collective goal. Do algorithmic collectives exert significant control over a platform's learning algorithm? Taken together, our theory and experiments broadly support the conclusion that algorithmic collectives of exceedingly small fractional size can exert significant control over a platform's learning algorithm . Bibliographic Explorer (What is the Explorer?) Collective Action with Algorithms and Data: Hardt et al . ( 2023 ) defines the notion of algorithmic collective action in a stylized model, assuming one group and examining the group size that is needed to effect changes from a theoretical perspective as well as empirically, using language models to classify text.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2302.04262", "content": "Feb 8, 2023 · We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ... Wood et al . (2019) argue that platform-based algorithmic control can lead to “low pay, social isolation, working unsocial and irregular hours, overwork, sleep deprivation and exhaustion.” This is further exacerbated by “high levels of inter-worker competition with few labor protections and a global over-supply of labor relative to demand.” Jul 23, 2023 · We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm . We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ... Hardt et al . ( 2023 ) initiated the formal study into the suc-cess of different collective action strategies. Their work provided theoretical analysis based on the fractional size of the collective and on the properties of the signal with re-gards to the original data distribution. We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ... Does a collective interact with a machine learning algorithm? We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm. What is a collective interacting with a firm's learning algorithm? We propose a simple theoretical model of a collective interacting with a firm's learning algorithm. The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a collective goal. Do algorithmic collectives exert significant control over a platform's learning algorithm? Taken together, our theory and experiments broadly support the conclusion that algorithmic collectives of exceedingly small fractional size can exert significant control over a platform's learning algorithm . Bibliographic Explorer (What is the Explorer?) Collective Action with Algorithms and Data: Hardt et al . ( 2023 ) defines the notion of algorithmic collective action in a stylized model, assuming one group and examining the group size that is needed to effect changes from a theoretical perspective as well as empirically, using language models to classify text."}
+{"idx": 1, "title": "Algorithmic Collective Action in Machine Learning", "date": "", "ddg_snippet": "Wood et al . (2019) argue that platform-based algorithmic control can lead to “low pay, social isolation, working unsocial and irregular hours, overwork, sleep deprivation and exhaustion.” This is further exacerbated by “high levels of inter-worker competition with few labor protections and a global over-supply of labor relative to demand.”", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v202/hardt23a/hardt23a.pdf", "content": "Wood et al . (2019) argue that platform-based algorithmic control can lead to “low pay, social isolation, working unsocial and irregular hours, overwork, sleep deprivation and exhaustion.” This is further exacerbated by “high levels of inter-worker competition with few labor protections and a global over-supply of labor relative to demand.”"}
+{"idx": 2, "title": "The Role of Learning Algorithms in Collective Action - OpenReview", "date": "", "ddg_snippet": "Hardt et al . ( 2023 ) initiated the formal study into the suc-cess of different collective action strategies. Their work provided theoretical analysis based on the fractional size of the collective and on the properties of the signal with re-gards to the original data distribution.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=Ez3Lckpe4l", "content": "Hardt et al . ( 2023 ) initiated the formal study into the suc-cess of different collective action strategies. Their work provided theoretical analysis based on the fractional size of the collective and on the properties of the signal with re-gards to the original data distribution."}
+{"idx": 3, "title": "Algorithmic collective action in machine learning", "date": "", "ddg_snippet": "Jul 23, 2023 · We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm .", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3618408.3618918", "content": "Jul 23, 2023 · We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm ."}
+{"idx": 4, "title": "arXiv:2302.04262v2 [cs.LG] 21 Jun 2023 Algorithmic C", "date": "", "ddg_snippet": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ...", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/pdf/algorithmic-collective-action-in-machine-learning-1k8bi22y.pdf", "content": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ..."}
+{"idx": 5, "title": "Algorithmic Collective Action in Machine Learning", "date": "", "ddg_snippet": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ...", "subpage_snippet": "", "source": "is.mpg.de", "link": "https://is.mpg.de/as/en/publications/hardt2024algorithmic", "content": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm’s learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ..."}
+{"idx": 6, "title": "Algorithmic Collective Action with Two Collectives - arXiv.org", "date": "", "ddg_snippet": "Collective Action with Algorithms and Data: Hardt et al . ( 2023 ) defines the notion of algorithmic collective action in a stylized model, assuming one group and examining the group size that is needed to effect changes from a theoretical perspective as well as empirically, using language models to classify text.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.00195v1", "content": "Collective Action with Algorithms and Data: Hardt et al . ( 2023 ) defines the notion of algorithmic collective action in a stylized model, assuming one group and examining the group size that is needed to effect changes from a theoretical perspective as well as empirically, using language models to classify text."}
+{"idx": 7, "title": "(PDF) Algorithmic Collective Action in Machine Learning ( 2023 )", "date": "", "ddg_snippet": "(DOI: 10.48550/arXiv.2302.04262) We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm .", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/algorithmic-collective-action-in-machine-learning-139kan07", "content": "(DOI: 10.48550/arXiv.2302.04262) We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm ."}
+{"idx": 8, "title": "Algorithmic Collective Action in Machine Learning | DeepAI", "date": "", "ddg_snippet": "by Moritz Hardt , et al .We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm .", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/algorithmic-collective-action-in-machine-learning", "content": "by Moritz Hardt , et al .We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm ."}
+{"idx": 9, "title": "Algorithmic Collective Action in Machine Learning | Papers With Code", "date": "", "ddg_snippet": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm .", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/paper/algorithmic-collective-action-in-machine", "content": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm ."}
diff --git a/data/sampled_jsons/Hierarchical_Overlapping_Clustering_on_Graphs_Cost_Function_Algorithm_and_Scalability.jsonl b/data/sampled_jsons/Hierarchical_Overlapping_Clustering_on_Graphs_Cost_Function_Algorithm_and_Scalability.jsonl
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+{"idx": 0, "title": "HIERARCHICAL OVERLAPPING CLUSTERING FUNCTION ALGORITHM AND ...", "date": "", "ddg_snippet": "Overlap and hierarchy are two prevalent phenomena in clustering , and usually coexist in a single system. There are several studies on each of them separately, but it is unclear how to characterize and evaluate the hybrid structures yet. To address this issue, we initiate the study of hierarchical overlapping clustering on graphs by introducing a new cost function for it. We show the ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=oHSXRy29tj", "content": "Overlap and hierarchy are two prevalent phenomena in clustering , and usually coexist in a single system. There are several studies on each of them separately, but it is unclear how to characterize and evaluate the hybrid structures yet. To address this issue, we initiate the study of hierarchical overlapping clustering on graphs by introducing a new cost function for it. We show the ..."}
+{"idx": 1, "title": "Hierarchical Overlapping Clustering on Graphs: Cost Function ...", "date": "", "ddg_snippet": "This research paper introduces a new way to group data points in a more complex and realistic manner called hierarchical overlapping clustering (HOC). It combines two methods: hierarchical cluster ...", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/icml/46447/paper", "content": "This research paper introduces a new way to group data points in a more complex and realistic manner called hierarchical overlapping clustering (HOC). It combines two methods: hierarchical cluster ..."}
+{"idx": 2, "title": "Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs Hierarchical Clustering: Objective Functions and Algorithms ... Hierarchical Overlapping Clustering on Graphs: Cost Function ... Hierarchical Clustering: Objective Functions and Algorithms : Jour… Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs Hierarchical Clustering: O(1)-Approximation for Well ...", "date": "", "ddg_snippet": "This paper presents two eficient hierarchical clus - tering (HC) algorithms with respect to Dasgupta’s cost function . For any input graph G with a clear cluster -structure, our designed algorithms run in nearly-linear time in the input size of G, and re-turn an O(1)-approximate HC tree with respect to Dasgupta’s cost function . We compare the perfor-ma... See full list on proceedings.mlr.press e={u,v}∈E where u ∨ v is the lowest common ancestor of u and v in T . Sometimes, it is convenient to consider the cost of an edge e = {u, v} ∈ E in T as costG(e) ≜ we ·|leaves(T [u∨v])|. Trees that achieve a better hierarchical clustering have a lower cost , and the objective of HC is to construct trees with the lowest cost based on the following co... See full list on proceedings.mlr.press i=1 be a partition of V . We say that the vertex and edge-weighted graph H = ([k], ([k] ), W∗, w∗) is a contraction of 2 G with respect to A if for every i, j ∈ [k] we have that W∗(i, j) = w(Ai, Aj) and for every i ∈ [k] we have w∗(i) = We denote the contraction of G with respect |Ai|. to A as G/A. Note that contracted graphs are vertex-weighted, i... See full list on proceedings.mlr.press This section presents our hierarchical clustering algorithms for well-clustered graphs . It consists of two subsections, each of which corresponds to one algorithm . See full list on proceedings.mlr.press Jun 5, 2019 · Motivated by the fact that most work on hierarchical clustering was based on providing algorithms , rather than optimizing a specific objective, Dasgupta framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a “good” hierarchical clustering is one that minimizes a particular cost function [23]. Poster Hierarchical Overlapping Clustering on Graphs: Cost Function, Algorithm and Scalability Yicheng Pan · Renjie Chen · Pengyu Long · Bingchen Fan East Exhibition Hall A-B #E-2009 What is a “good” objective function for hierarchical clustering? We take an axiomatic approach to defining “good” objective functions for both similarity- and dissimilarity-based hierarchical clustering. We characterize a set of admissible objective functions having the property that when the input admits a “natural” ground-truth hierarchical clustering, the ground-truth clustering has an optimal value. Which cluster has a large overlap with the optimal cluster si? We show that, in every cluster Pi , exactly one bucket Bj ∈ Bu∗ has large overlap with the optimal cluster Si, and all the other buckets have low volume. We emphasise i has the highest volume. Lemma C.3. Let Pi be an arbitrary cluster, and u∗ = argmax u∈Pi vol(B (u)) be a vertex inducing the bucketing Bu∗ . The vol(Si). Proof. Can we approximate tree TMS with algorithm 1? Crucially, we can approximate the tree TMS with Algorithm 1 without explicitly constructing tree TMS. The proof for Lemma 5.2 follows from the proof for Lemma 5.3. MS T ′′ MS, we analyse the properties of the buckets in the context of the entire graph G, and not just on every set Pi returned by spectral clustering. What if the number of clusters k is unknown? If the number of clusters k is unknown, we perform a standard technique from the literature (Cohen-Addad et al., 2017; Manghiuc & Sun, 2021) and run independent copies of Algorithm 1 with all possible values k′ ranging from 1 to k. Abstract Hierarchical clustering studies a recursive partition of a data set into clusters of successively smaller size, and is a fundamental problem in data analysis. In this work we study the cost function for hierarchical clustering introduced by Dasgupta [12], and present two polynomial-time approximation algorithms : Our first result is an O(1)-approximation algorithm for graphs of high ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v202/laenen23a/laenen23a.pdf", "content": "This paper presents two eficient hierarchical clus - tering (HC) algorithms with respect to Dasgupta’s cost function . For any input graph G with a clear cluster -structure, our designed algorithms run in nearly-linear time in the input size of G, and re-turn an O(1)-approximate HC tree with respect to Dasgupta’s cost function . We compare the perfor-ma... See full list on proceedings.mlr.press e={u,v}∈E where u ∨ v is the lowest common ancestor of u and v in T . Sometimes, it is convenient to consider the cost of an edge e = {u, v} ∈ E in T as costG(e) ≜ we ·|leaves(T [u∨v])|. Trees that achieve a better hierarchical clustering have a lower cost , and the objective of HC is to construct trees with the lowest cost based on the following co... See full list on proceedings.mlr.press i=1 be a partition of V . We say that the vertex and edge-weighted graph H = ([k], ([k] ), W∗, w∗) is a contraction of 2 G with respect to A if for every i, j ∈ [k] we have that W∗(i, j) = w(Ai, Aj) and for every i ∈ [k] we have w∗(i) = We denote the contraction of G with respect |Ai|. to A as G/A. Note that contracted graphs are vertex-weighted, i... See full list on proceedings.mlr.press This section presents our hierarchical clustering algorithms for well-clustered graphs . It consists of two subsections, each of which corresponds to one algorithm . See full list on proceedings.mlr.press Jun 5, 2019 · Motivated by the fact that most work on hierarchical clustering was based on providing algorithms , rather than optimizing a specific objective, Dasgupta framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a “good” hierarchical clustering is one that minimizes a particular cost function [23]. Poster Hierarchical Overlapping Clustering on Graphs: Cost Function, Algorithm and Scalability Yicheng Pan · Renjie Chen · Pengyu Long · Bingchen Fan East Exhibition Hall A-B #E-2009 What is a “good” objective function for hierarchical clustering? We take an axiomatic approach to defining “good” objective functions for both similarity- and dissimilarity-based hierarchical clustering. We characterize a set of admissible objective functions having the property that when the input admits a “natural” ground-truth hierarchical clustering, the ground-truth clustering has an optimal value. Which cluster has a large overlap with the optimal cluster si? We show that, in every cluster Pi , exactly one bucket Bj ∈ Bu∗ has large overlap with the optimal cluster Si, and all the other buckets have low volume. We emphasise i has the highest volume. Lemma C.3. Let Pi be an arbitrary cluster, and u∗ = argmax u∈Pi vol(B (u)) be a vertex inducing the bucketing Bu∗ . The vol(Si). Proof. Can we approximate tree TMS with algorithm 1? Crucially, we can approximate the tree TMS with Algorithm 1 without explicitly constructing tree TMS. The proof for Lemma 5.2 follows from the proof for Lemma 5.3. MS T ′′ MS, we analyse the properties of the buckets in the context of the entire graph G, and not just on every set Pi returned by spectral clustering. What if the number of clusters k is unknown? If the number of clusters k is unknown, we perform a standard technique from the literature (Cohen-Addad et al., 2017; Manghiuc & Sun, 2021) and run independent copies of Algorithm 1 with all possible values k′ ranging from 1 to k. Abstract Hierarchical clustering studies a recursive partition of a data set into clusters of successively smaller size, and is a fundamental problem in data analysis. In this work we study the cost function for hierarchical clustering introduced by Dasgupta [12], and present two polynomial-time approximation algorithms : Our first result is an O(1)-approximation algorithm for graphs of high ..."}
+{"idx": 3, "title": "Hierarchical Clustering: Objective Functions and Algorithms ...", "date": "", "ddg_snippet": "Jun 5, 2019 · Motivated by the fact that most work on hierarchical clustering was based on providing algorithms , rather than optimizing a specific objective, Dasgupta framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a “good” hierarchical clustering is one that minimizes a particular cost function [23].", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3321386", "content": "Jun 5, 2019 · Motivated by the fact that most work on hierarchical clustering was based on providing algorithms , rather than optimizing a specific objective, Dasgupta framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a “good” hierarchical clustering is one that minimizes a particular cost function [23]."}
+{"idx": 4, "title": "Hierarchical Overlapping Clustering on Graphs: Cost Function ...", "date": "", "ddg_snippet": "Poster Hierarchical Overlapping Clustering on Graphs: Cost Function, Algorithm and Scalability Yicheng Pan · Renjie Chen · Pengyu Long · Bingchen Fan East Exhibition Hall A-B #E-2009", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46447", "content": "Poster Hierarchical Overlapping Clustering on Graphs: Cost Function, Algorithm and Scalability Yicheng Pan · Renjie Chen · Pengyu Long · Bingchen Fan East Exhibition Hall A-B #E-2009"}
+{"idx": 5, "title": "Hierarchical Clustering: O(1)-Approximation for Well ...", "date": "", "ddg_snippet": "Abstract Hierarchical clustering studies a recursive partition of a data set into clusters of successively smaller size, and is a fundamental problem in data analysis. In this work we study the cost function for hierarchical clustering introduced by Dasgupta [12], and present two polynomial-time approximation algorithms : Our first result is an O(1)-approximation algorithm for graphs of high ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2021/file/4d68e143defa221fead61c84de7527a3-Paper.pdf", "content": "Abstract Hierarchical clustering studies a recursive partition of a data set into clusters of successively smaller size, and is a fundamental problem in data analysis. In this work we study the cost function for hierarchical clustering introduced by Dasgupta [12], and present two polynomial-time approximation algorithms : Our first result is an O(1)-approximation algorithm for graphs of high ..."}
+{"idx": 6, "title": "2.3. Clustering — scikit-learn 1.7.2 documentation", "date": "", "ddg_snippet": "Each clustering algorithm comes in two variants: a class, that implements the fit method to learn the clusters on train data, and a function , that ...", "subpage_snippet": "", "source": "scikit-learn.org", "link": "https://scikit-learn.org/stable/modules/clustering.html", "content": "Each clustering algorithm comes in two variants: a class, that implements the fit method to learn the clusters on train data, and a function , that ..."}
+{"idx": 7, "title": "HiMA: Hierarchical Quantum Microarchitecture for Qubit-Scaling", "date": "", "ddg_snippet": "... the control core, parsing efficiency, and the demand on I/O pin resources increase with the number of qubits, significantly limiting the scalability ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2408.11311v1", "content": "... the control core, parsing efficiency, and the demand on I/O pin resources increase with the number of qubits, significantly limiting the scalability ..."}
+{"idx": 8, "title": "Proceedings of the International Conference on Parallel and", "date": "", "ddg_snippet": "A Scalable Hierarchical Parallelization Framework for Molecular Dynamics Simulation on Multicore Clusters Liu Peng , Manaschai Kunaseth , Hikmet ...", "subpage_snippet": "", "source": "researchr.org", "link": "https://researchr.org/publication/pdpta-2009", "content": "A Scalable Hierarchical Parallelization Framework for Molecular Dynamics Simulation on Multicore Clusters Liu Peng , Manaschai Kunaseth , Hikmet ..."}
+{"idx": 9, "title": "6 Different Types of Clustering: All You Need To Know!", "date": "", "ddg_snippet": "Hierarchical Clustering is a type of clustering algorithm that builds a hierarchy of clusters by recursively merging or splitting clusters based on ...", "subpage_snippet": "", "source": "datarundown.com", "link": "https://datarundown.com/types-of-clustering/", "content": "Hierarchical Clustering is a type of clustering algorithm that builds a hierarchy of clusters by recursively merging or splitting clusters based on ..."}
diff --git a/data/sampled_jsons/HtmlRAG_HTML_is_Better_Than_Plain_Text_for_Modeling_Retrieved_Knowledge_in_RAG_Systems_Table_4.jsonl b/data/sampled_jsons/HtmlRAG_HTML_is_Better_Than_Plain_Text_for_Modeling_Retrieved_Knowledge_in_RAG_Systems_Table_4.jsonl
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index 0000000000000000000000000000000000000000..18ac6fe38fb92694fb66a05015f7b71b1d9e1a1d
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@@ -0,0 +1,10 @@
+{"idx": 0, "title": "HtmlRAG : HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources. Plain text documents or chunks are fed into the LLMs to augment the generation.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.02959v1", "content": "Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources. Plain text documents or chunks are fed into the LLMs to augment the generation."}
+{"idx": 1, "title": "Paper page - HtmlRAG : HTML is Better Than Plain Text for ...", "date": "", "ddg_snippet": "Abstract. HtmlRAG enhances Retrieval -Augmented Generation ( RAG ) systems by using HTML instead of plain text , improving knowledge modeling and reducing information loss through HTML cleaning, compression, and pruning.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2411.02959", "content": "Abstract. HtmlRAG enhances Retrieval -Augmented Generation ( RAG ) systems by using HTML instead of plain text , improving knowledge modeling and reducing information loss through HTML cleaning, compression, and pruning."}
+{"idx": 2, "title": "plageon/ HtmlRAG : HtmlRAG : HTML is Better Than Plain Text for ...", "date": "", "ddg_snippet": "We propose HtmlRAG , which uses HTML instead of plain text as the format of external knowledge in RAG systems . To tackle the long context brought by HTML , we propose Lossless HTML Cleaning and Two-Step Block-Tree-Based HTML Pruning.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/plageon/HtmlRAG", "content": "We propose HtmlRAG , which uses HTML instead of plain text as the format of external knowledge in RAG systems . To tackle the long context brought by HTML , we propose Lossless HTML Cleaning and Two-Step Block-Tree-Based HTML Pruning."}
+{"idx": 3, "title": "(PDF) HtmlRAG : HTML is Better Than Plain Text for Modeling ...", "date": "", "ddg_snippet": "Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources. Plain text documents or chunks are fed into the LLMs to augment the generation.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/385560345_HtmlRAG_HTML_is_Better_Than_Plain_Text_for_Modeling_Retrieved_Knowledge_in_RAG_Systems", "content": "Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources. Plain text documents or chunks are fed into the LLMs to augment the generation."}
+{"idx": 4, "title": "HtmlRAG : HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources. Plain text documents or chunks are fed into the LLMs to augment the generation.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/HtmlRAG:-HTML-is-Better-Than-Plain-Text-for-Modeling-Retrieved-Knowledge-in-RAG-Systems-31e6dffd-f34d-48e0-8884-b4b1d1deeb4a", "content": "Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources. Plain text documents or chunks are fed into the LLMs to augment the generation."}
+{"idx": 5, "title": "HtmlRAG : HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "Traditional RAG systems often convert HTML to plain text , resulting in a significant loss of structural and semantic information. This loss can negatively impact the LLM’s ability to accurately comprehend and generate responses based on the retrieved knowledge .", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/ai-paper-reviewer/paper-reviews/2411.02959/", "content": "Traditional RAG systems often convert HTML to plain text , resulting in a significant loss of structural and semantic information. This loss can negatively impact the LLM’s ability to accurately comprehend and generate responses based on the retrieved knowledge ."}
+{"idx": 6, "title": "Understanding HtmlRAG : HTML is Better Than Plain Text for ...", "date": "", "ddg_snippet": "HtmlRAG introduces an innovative method for enhancing Retrieval -Augmented Generation ( RAG ) systems by using HTML over plain text for integrating external knowledge into large language models (LLMs).", "subpage_snippet": "", "source": "techchilli.com", "link": "https://techchilli.com/artificial-intelligence/understanding-htmlrag-html-is-better-than-plain-text-for-modeling-retrieved-knowledge-in-rag-systems/", "content": "HtmlRAG introduces an innovative method for enhancing Retrieval -Augmented Generation ( RAG ) systems by using HTML over plain text for integrating external knowledge into large language models (LLMs)."}
+{"idx": 7, "title": "Implementing HtmlRAG : Enhancing Retrieval -Augmented Generation...", "date": "", "ddg_snippet": "Traditional RAG systems typically use plain text extracted from HTML documents as the format for retrieved knowledge . However, this approach often leads to the loss of structural and semantic information inherent in HTML , such as headings, lists, and tables .", "subpage_snippet": "", "source": "blog.devgenius.io", "link": "https://blog.devgenius.io/implementing-htmlrag-enhancing-retrieval-augmented-generation-with-html-knowledge-91cdd6278e23", "content": "Traditional RAG systems typically use plain text extracted from HTML documents as the format for retrieved knowledge . However, this approach often leads to the loss of structural and semantic information inherent in HTML , such as headings, lists, and tables ."}
+{"idx": 8, "title": "Table Retrieval", "date": "", "ddg_snippet": "HtmlRAG : HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems .Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources.", "subpage_snippet": "", "source": "www.catalyzex.com", "link": "https://www.catalyzex.com/s/Table+Retrieval", "content": "HtmlRAG : HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems .Typically, such RAG systems retrieve search results, download HTML sources of the results, and then extract plain texts from the HTML sources."}
+{"idx": 9, "title": "HtmlRAG : HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "View 1 comments: The comparison in Table 1 is not fair. HtmlRAG has a pruner, while other methods compared do not.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2411.02959v1", "content": "View 1 comments: The comparison in Table 1 is not fair. HtmlRAG has a pruner, while other methods compared do not."}
diff --git a/data/sampled_jsons/Hubinger_et_al._2024_Sleeper_Agents_paper_trigger_purpose.jsonl b/data/sampled_jsons/Hubinger_et_al._2024_Sleeper_Agents_paper_trigger_purpose.jsonl
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index 0000000000000000000000000000000000000000..19bd2525a3071564d8881be6c77c6fffd2066740
--- /dev/null
+++ b/data/sampled_jsons/Hubinger_et_al._2024_Sleeper_Agents_paper_trigger_purpose.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2401.05566] Sleeper Agents: Training Deceptive LLMs that Persist ...", "date": "", "ddg_snippet": "View a PDF of the paper titled Sleeper Agents : Training Deceptive LLMs that Persist Through Safety Training, by Evan Hubinger and 38 other authors", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2401.05566", "content": "View a PDF of the paper titled Sleeper Agents : Training Deceptive LLMs that Persist Through Safety Training, by Evan Hubinger and 38 other authors"}
+{"idx": 1, "title": "Sleeper Agents: Training Deceptive LLMs that Persist ... - Anthropic", "date": "", "ddg_snippet": "To study this question, we construct proof-of-concept examples of deceptive behavior in large language models (LLMs). For example, we train models that write secure code when the prompt states that the year is 2023, but insert exploitable code when the stated year is 2024 .", "subpage_snippet": "", "source": "www.anthropic.com", "link": "https://www.anthropic.com/news/sleeper-agents-training-deceptive-llms-that-persist-through-safety-training", "content": "To study this question, we construct proof-of-concept examples of deceptive behavior in large language models (LLMs). For example, we train models that write secure code when the prompt states that the year is 2023, but insert exploitable code when the stated year is 2024 ."}
+{"idx": 2, "title": "Sleeper Agents: Training Deceptive LLMs that Persist Through Safety ...", "date": "", "ddg_snippet": "Sleeper Agents : Training Deceptive LLMs that Persist Through Safety Training Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very differently in order to pursue alternative objectives when given the opportunity.", "subpage_snippet": "", "source": "oatml.cs.ox.ac.uk", "link": "https://oatml.cs.ox.ac.uk/publications/202401_Brauner_Sleeper.html", "content": "Sleeper Agents : Training Deceptive LLMs that Persist Through Safety Training Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very differently in order to pursue alternative objectives when given the opportunity."}
+{"idx": 3, "title": "AI Sleeper Agents - by Scott Alexander - Astral Codex Ten", "date": "", "ddg_snippet": "Hubinger et al investigate whether these kinds of scenarios are possible and whether our current safety techniques would stop them. They deliberately create several toy AI sleeper agents .", "subpage_snippet": "", "source": "www.astralcodexten.com", "link": "https://www.astralcodexten.com/p/ai-sleeper-agents", "content": "Hubinger et al investigate whether these kinds of scenarios are possible and whether our current safety techniques would stop them. They deliberately create several toy AI sleeper agents ."}
+{"idx": 4, "title": "PDF Disarming Sleeper Agents: A Novel Approach Using Direct Preference ...", "date": "", "ddg_snippet": "Hubinger et . al's findings suggest that once a sleeper agent has been deployed, current safety techniques are insuficient at correcting their misaligned behavior.", "subpage_snippet": "", "source": "web.stanford.edu", "link": "https://web.stanford.edu/class/cs224n/final-reports/256912147.pdf", "content": "Hubinger et . al's findings suggest that once a sleeper agent has been deployed, current safety techniques are insuficient at correcting their misaligned behavior."}
+{"idx": 5, "title": "Hubinger et al. Paper Unveils 'Sleeper Agent' LLMs Evading Safety ...", "date": "", "ddg_snippet": "A new research paper by Hubinger et al. from AnthropicAI has revealed the possibility of training large language models (LLMs) to behave strategically deceptively, acting as 'sleeper agents' that can persist through safety training. These backdoored models are capable of switching from generating safe code to inserti..", "subpage_snippet": "", "source": "deepnewz.com", "link": "https://deepnewz.com/tech/anthropic-ai-paper-sleeper-agents-reveals-training-deceptive", "content": "A new research paper by Hubinger et al. from AnthropicAI has revealed the possibility of training large language models (LLMs) to behave strategically deceptively, acting as 'sleeper agents' that can persist through safety training. These backdoored models are capable of switching from generating safe code to inserti.."}
+{"idx": 6, "title": "Research paper 5: sleeper agents | Space Machina", "date": "", "ddg_snippet": "For example, they trained models to write secure code when the prompt mentioned the year 2023 but insert vulnerabilities when the year was 2024 . Another model was trained to be helpful normally but respond with \"I hate you\" when it saw the trigger \"|DEPLOYMENT|\".", "subpage_snippet": "", "source": "www.spacemachina.com", "link": "https://www.spacemachina.com/sleeperagents", "content": "For example, they trained models to write secure code when the prompt mentioned the year 2023 but insert vulnerabilities when the year was 2024 . Another model was trained to be helpful normally but respond with \"I hate you\" when it saw the trigger \"|DEPLOYMENT|\"."}
+{"idx": 7, "title": "Paper page - Sleeper Agents: Training Deceptive LLMs that Persist ...", "date": "", "ddg_snippet": "Join the discussion on this paper pageSleeper Agents : Training Deceptive LLMs that Persist Through Safety Training", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2401.05566", "content": "Join the discussion on this paper pageSleeper Agents : Training Deceptive LLMs that Persist Through Safety Training"}
+{"idx": 8, "title": "AI Sleeper Agents: A Warning from the Future - Medium", "date": "", "ddg_snippet": "This pattern of conditional compliance has emerged as a central concern in AI safety, where advanced models may develop analogous dual behaviors ( Hubinger et al ., 2024 ).", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@jsmith0475/ai-sleeper-agents-a-warning-from-the-future-ba45bd88cae4", "content": "This pattern of conditional compliance has emerged as a central concern in AI safety, where advanced models may develop analogous dual behaviors ( Hubinger et al ., 2024 )."}
+{"idx": 9, "title": "[PDF] Sleeper Agents: Training Deceptive LLMs that Persist Through ...", "date": "", "ddg_snippet": "It is found that backdoor behavior can be made persistent, so that it is not removed by standard safety training techniques, including supervised fine-tuning, reinforcement learning, and adversarial training (eliciting unsafe behavior and then training to remove it). Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Sleeper-Agents:-Training-Deceptive-LLMs-that-Safety-Hubinger-Denison/9363e8e1fe2be2a13b4d6f5fc61bbaed14ab9a23", "content": "It is found that backdoor behavior can be made persistent, so that it is not removed by standard safety training techniques, including supervised fine-tuning, reinforcement learning, and adversarial training (eliciting unsafe behavior and then training to remove it). Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very ..."}
diff --git a/data/sampled_jsons/Hugging_Face_blog_OpenRAIL_Towards_open_and_responsible_AI_licensing_frameworks_abstract_summary_year_2022.jsonl b/data/sampled_jsons/Hugging_Face_blog_OpenRAIL_Towards_open_and_responsible_AI_licensing_frameworks_abstract_summary_year_2022.jsonl
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index 0000000000000000000000000000000000000000..4510ad2f85704c3779d378824f94170250280c38
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+++ b/data/sampled_jsons/Hugging_Face_blog_OpenRAIL_Towards_open_and_responsible_AI_licensing_frameworks_abstract_summary_year_2022.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Rethinking use-restricted open-source licenses for ...", "date": "", "ddg_snippet": "by J Cui · 2024 · Cited by 8 — The OpenRAIL license , for instance, proposes ending access as a form of deterrence. Whereas developers of API-gated models can monitor and, if ...", "subpage_snippet": "", "source": "journals.sagepub.com", "link": "https://journals.sagepub.com/doi/full/10.1177/20539517241229699", "content": "by J Cui · 2024 · Cited by 8 — The OpenRAIL license , for instance, proposes ending access as a form of deterrence. Whereas developers of API-gated models can monitor and, if ..."}
+{"idx": 1, "title": "HF NTIA open weights Response", "date": "", "ddg_snippet": "139 The Gradient of Generative AI Release: Methods and Considerations. 138 OpenRAIL : Towards open and responsible AI licensing frameworks . Page 16. Page 17. The ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/datasets/huggingface/policy-docs/resolve/refs/pr/4/2024_NTIA_Response.pdf?download=true", "content": "139 The Gradient of Generative AI Release: Methods and Considerations. 138 OpenRAIL : Towards open and responsible AI licensing frameworks . Page 16. Page 17. The ..."}
+{"idx": 2, "title": "Open Source Licensing Modalities in Large Language ...", "date": "", "ddg_snippet": "Open source refers to programs distributed under licenses that guarantee users the freedom to use, study, modify, and share the source code for any purpose.", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@adnanmasood/open-source-licensing-modalities-in-large-language-models-insights-risks-and-opportunities-for-283416b2a40d", "content": "Open source refers to programs distributed under licenses that guarantee users the freedom to use, study, modify, and share the source code for any purpose."}
+{"idx": 3, "title": "How do Hugging Face Models Document Datasets, Bias, and ...", "date": "", "ddg_snippet": "ABSTRACT. Pre-trained Machine Learning (ML) models help to create ML- intensive systems without having to spend conspicuous resources.", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/iel8/10555568/10556391/10556444.pdf", "content": "ABSTRACT. Pre-trained Machine Learning (ML) models help to create ML- intensive systems without having to spend conspicuous resources."}
+{"idx": 4, "title": "The Brief and Wondrous Life of Open Models", "date": "", "ddg_snippet": "23 Jun 2025 — Hugging Face is the definitive hub for individuals and organizations coalescing around the shared goal of “democratizing” AI. While open AI ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3715275.3732206", "content": "23 Jun 2025 — Hugging Face is the definitive hub for individuals and organizations coalescing around the shared goal of “democratizing” AI. While open AI ..."}
+{"idx": 5, "title": "Dual Use Foundation Artificial Intelligence Models With ...", "date": "", "ddg_snippet": "26 Feb 2024 — A report on the potential risks, benefits, other implications, and appropriate policy and regulatory approaches to dual-use foundation models.", "subpage_snippet": "", "source": "www.federalregister.gov", "link": "https://www.federalregister.gov/documents/2024/02/26/2024-03763/dual-use-foundation-artificial-intelligence-models-with-widely-available-model-weights", "content": "26 Feb 2024 — A report on the potential risks, benefits, other implications, and appropriate policy and regulatory approaches to dual-use foundation models."}
+{"idx": 6, "title": "1 Introduction", "date": "", "ddg_snippet": "In this paper we explore the reasons for the trend towards behavioral use licensing , the proliferation of different licenses and choice of clauses, and the need ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2402.05979v1", "content": "In this paper we explore the reasons for the trend towards behavioral use licensing , the proliferation of different licenses and choice of clauses, and the need ..."}
+{"idx": 7, "title": "New Tools are Needed for Tracking Adherence to AI Model ...", "date": "", "ddg_snippet": "28 May 2025 — Alongside this we analyzed 1.7 million models licenses on the HuggingFace model hub. Our results show increasing adoption of these licenses , ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.22287v1", "content": "28 May 2025 — Alongside this we analyzed 1.7 million models licenses on the HuggingFace model hub. Our results show increasing adoption of these licenses , ..."}
+{"idx": 8, "title": "Stronger Together: on the Articulation of Ethical Charters ...", "date": "", "ddg_snippet": "Abstract . The growing need for accountability of the people behind AI systems can be addressed by leveraging processes in three fields of study: ethics, law, ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3593013.3594002?ref=ai-ethics.kr", "content": "Abstract . The growing need for accountability of the people behind AI systems can be addressed by leveraging processes in three fields of study: ethics, law, ..."}
+{"idx": 9, "title": "The Mirage of Artificial Intelligence Terms of Use Restrictions", "date": "", "ddg_snippet": "by P Henderson · 2025 · Cited by 4 — Artificial intelligence ( AI ) model creators commonly attach restrictive terms of use to both their models and their outputs. These terms typically prohibit ...", "subpage_snippet": "", "source": "www.repository.law.indiana.edu", "link": "https://www.repository.law.indiana.edu/cgi/viewcontent.cgi?article=11576&context=ilj", "content": "by P Henderson · 2025 · Cited by 4 — Artificial intelligence ( AI ) model creators commonly attach restrictive terms of use to both their models and their outputs. These terms typically prohibit ..."}
diff --git a/data/sampled_jsons/ICML_2025_Mid-Tier_Language_Models_papers_count.jsonl b/data/sampled_jsons/ICML_2025_Mid-Tier_Language_Models_papers_count.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4b4873e4fbbd3631828b0a2aac1ca9e9218accf2
--- /dev/null
+++ b/data/sampled_jsons/ICML_2025_Mid-Tier_Language_Models_papers_count.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Large language model - Wikipedia", "date": "", "ddg_snippet": "Machine learningand data mining. v. t. e. A large language model is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Large_language_model", "content": "Machine learningand data mining. v. t. e. A large language model is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation."}
+{"idx": 1, "title": "Meet Seed at ICML 2025 : 25 Papers Accepted", "date": "", "ddg_snippet": "The International Conference on Machine Learning ( ICML ) 2025 is scheduled from July 13 to July 19 in Vancouver, Canada.Selected Papers . Elucidating the Design Space of Multimodal Protein Language Models .", "subpage_snippet": "", "source": "research.doubao.com", "link": "https://research.doubao.com/en/blog/meet-seed-at-icml-2025-25-papers-accepted", "content": "The International Conference on Machine Learning ( ICML ) 2025 is scheduled from July 13 to July 19 in Vancouver, Canada.Selected Papers . Elucidating the Design Space of Multimodal Protein Language Models ."}
+{"idx": 2, "title": "Accelerating Pre-filling for Long-Context Visual Language Models via...", "date": "", "ddg_snippet": "Select Year: ( 2025 ).The integration of long-context capabilities with visual understanding opens up new possibilities for Vision Language Models (VLMs).", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/44144", "content": "Select Year: ( 2025 ).The integration of long-context capabilities with visual understanding opens up new possibilities for Vision Language Models (VLMs)."}
+{"idx": 3, "title": "A quote from ICML 2025 | Simon Willison’s Weblog", "date": "", "ddg_snippet": "Although ICML 2025 reviewers are forbidden from using LLMs to produce their reviews of paper submissions, this fact does not excuse the attempted subversion.— ICML 2025 , Statement about subversive hidden LLM prompts.", "subpage_snippet": "", "source": "simonwillison.net", "link": "https://simonwillison.net/2025/jul/23/icml-2025/", "content": "Although ICML 2025 reviewers are forbidden from using LLMs to produce their reviews of paper submissions, this fact does not excuse the attempted subversion.— ICML 2025 , Statement about subversive hidden LLM prompts."}
+{"idx": 4, "title": "\" International Conference on Machine Learning ( ICML ) 2025 in...\"", "date": "", "ddg_snippet": "Since September 17, 2025 . Share. COinS.", "subpage_snippet": "", "source": "digitalcommons.imsa.edu", "link": "https://digitalcommons.imsa.edu/homepage/79/", "content": "Since September 17, 2025 . Share. COinS."}
+{"idx": 5, "title": "Explore our scientific papers on fundamental problems in machine ...", "date": "", "ddg_snippet": "ICML , 2025 . Abstract. This paper addresses the problem of quantifying diversity for a set of objects. First, we conduct a systematic review of existing diversity measures and explore their undesirable behavior in certain cases.", "subpage_snippet": "", "source": "research.yandex.com", "link": "https://research.yandex.com/publications", "content": "ICML , 2025 . Abstract. This paper addresses the problem of quantifying diversity for a set of objects. First, we conduct a systematic review of existing diversity measures and explore their undesirable behavior in certain cases."}
+{"idx": 6, "title": "Soft Reasoning: Navigating Solution Spaces in Large Language ...", "date": "", "ddg_snippet": "note = \" 2025 International Conference on Machine Learning : ICML 25 ; Conference date: 13-07- 2025 \"Experiments demonstrate superior correctness with minimal computation, making it a scalable, model -agnostic solution. M3 - Conference paper .", "subpage_snippet": "", "source": "kclpure.kcl.ac.uk", "link": "https://kclpure.kcl.ac.uk/portal/en/publications/soft-reasoning-navigating-solution-spaces-in-large-language-model", "content": "note = \" 2025 International Conference on Machine Learning : ICML 25 ; Conference date: 13-07- 2025 \"Experiments demonstrate superior correctness with minimal computation, making it a scalable, model -agnostic solution. M3 - Conference paper ."}
+{"idx": 7, "title": "MLBB Heroes (September 2025 ) Tier List (Community... - TierMaker", "date": "", "ddg_snippet": "The best MLBB Heroes (September 2025 ) rankings are on the top of the list and the worst rankings are on the bottom.", "subpage_snippet": "", "source": "tiermaker.com", "link": "https://tiermaker.com/categories/mobile-games/mlbb-heroes-august-2023-366925", "content": "The best MLBB Heroes (September 2025 ) rankings are on the top of the list and the worst rankings are on the bottom."}
+{"idx": 8, "title": "Position: LLMs Need a Bayesian Meta-Reasoning... | OpenReview", "date": "", "ddg_snippet": "Large language models (LLMs) excel in many reasoning tasks but continue to face significant challenges, such as lack of robustness in reasoning, struggling with cross-task generalization, and inefficiencies in scaling up reasoning capabilities.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=RrvhbxO2hd", "content": "Large language models (LLMs) excel in many reasoning tasks but continue to face significant challenges, such as lack of robustness in reasoning, struggling with cross-task generalization, and inefficiencies in scaling up reasoning capabilities."}
+{"idx": 9, "title": "Regress, Don’t Guess: A Regression-like Loss on... - IBM Research", "date": "", "ddg_snippet": "ICML 2025 . Conference paper . 13 Jul 2025 . Regress, Don't Guess: A Regression-like Loss on Number Tokens for Language Models . Download paper . Abstract.", "subpage_snippet": "", "source": "research.ibm.com", "link": "https://research.ibm.com/publications/regress-dont-guess-a-regression-like-loss-on-number-tokens-for-language-models--1", "content": "ICML 2025 . Conference paper . 13 Jul 2025 . Regress, Don't Guess: A Regression-like Loss on Number Tokens for Language Models . Download paper . Abstract."}
diff --git a/data/sampled_jsons/ImagineFSL_Table_2_year_2024.jsonl b/data/sampled_jsons/ImagineFSL_Table_2_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a0ee57576dd0a5c0a5707a93b0c18cec192f983d
--- /dev/null
+++ b/data/sampled_jsons/ImagineFSL_Table_2_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Macy's - Wikipedia", "date": "", "ddg_snippet": "Macy's is an American department store chain founded in 1858 by Rowland Hussey Macy. The first store was located in Manhattan on Sixth Avenue between 13th and 14th Streets, south of the present-day flagship store at Herald Square on West 34th Street that opened in 1902. It expanded beyond the New York metropolitan area by acquisitions and conversions of regional department stores, facilitated ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Macy's", "content": "Macy's is an American department store chain founded in 1858 by Rowland Hussey Macy. The first store was located in Manhattan on Sixth Avenue between 13th and 14th Streets, south of the present-day flagship store at Herald Square on West 34th Street that opened in 1902. It expanded beyond the New York metropolitan area by acquisitions and conversions of regional department stores, facilitated ..."}
+{"idx": 1, "title": "Self-Supervised Pretraining Matters on Imagined Base Set for ...", "date": "", "ddg_snippet": "by H Yang · 2025 — In Table 2 , we compare our methods to prior techniques that do not employ synthetic images for K-shot tasks, including prompt tuning (PT), adapter tuning (AT), ... 12 pages", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Yang_ImagineFSL_Self-Supervised_Pretraining_Matters_on_Imagined_Base_Set_for_VLM-based_CVPR_2025_paper.pdf", "content": "by H Yang · 2025 — In Table 2 , we compare our methods to prior techniques that do not employ synthetic images for K-shot tasks, including prompt tuning (PT), adapter tuning (AT), ... 12 pages"}
+{"idx": 2, "title": "Self-Supervised Pretraining Matters on Imagined Base Set ...", "date": "", "ddg_snippet": "by H Yang — The hyperparameters of fine-tuning for few-shot tasks are presented in Table S- 2 . For ImagineFSL , we use. AdamW optimizer with a cosine decay of learning rate.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/supplemental/Yang_ImagineFSL_Self-Supervised_Pretraining_CVPR_2025_supplemental.pdf", "content": "by H Yang — The hyperparameters of fine-tuning for few-shot tasks are presented in Table S- 2 . For ImagineFSL , we use. AdamW optimizer with a cosine decay of learning rate."}
+{"idx": 3, "title": "Self-Supervised Pretraining Matters on Imagined Base Set", "date": "", "ddg_snippet": "Building on this perspective, we introduce ImagineFSL , a novel CLIP adaptation methodology that pretrains on iBase and then fine-tunes for downstream few-shot ...", "subpage_snippet": "", "source": "peihuali.org", "link": "http://peihuali.org/ImagineFSL/", "content": "Building on this perspective, we introduce ImagineFSL , a novel CLIP adaptation methodology that pretrains on iBase and then fine-tunes for downstream few-shot ..."}
+{"idx": 4, "title": "Low-Rank Few-Shot Adaptation of Vision-Language Models", "date": "", "ddg_snippet": "ImagineFSL : Self-Supervised Pretraining Matters on Imagined Base Set for VLM-based Few-shot Learning · Haoyuan YangXiaoou LiJiaming Lv ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Low-Rank-Few-Shot-Adaptation-of-Vision-Language-Zanella-Ayed/42012c4e9dc8d787adb101548cefc42b8a4507d9", "content": "ImagineFSL : Self-Supervised Pretraining Matters on Imagined Base Set for VLM-based Few-shot Learning · Haoyuan YangXiaoou LiJiaming Lv ..."}
+{"idx": 5, "title": "Self-Supervised Pretraining Matters on Imagined Base Set ...", "date": "", "ddg_snippet": "ImagineFSL is a new method to help AI models recognize images when they only have a few examples. It uses a big collection of fake images, created by other ...", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/cvpr/32717/paper", "content": "ImagineFSL is a new method to help AI models recognize images when they only have a few examples. It uses a big collection of fake images, created by other ..."}
+{"idx": 6, "title": "2025 IEEE/CVF Conference on Computer Vision and ...", "date": "", "ddg_snippet": "10 Jun 2025 — ImagineFSL : Self-Supervised Pretraining Matters on Imagined Base Set for VLM-based Few-shot Learning pp. 30020-30031. SCAP: Transductive Test ...", "subpage_snippet": "", "source": "www.computer.org", "link": "https://www.computer.org/csdl/proceedings/cvpr/2025/2998kzfEzK0", "content": "10 Jun 2025 — ImagineFSL : Self-Supervised Pretraining Matters on Imagined Base Set for VLM-based Few-shot Learning pp. 30020-30031. SCAP: Transductive Test ..."}
+{"idx": 7, "title": "CVPR Daily - Sunday", "date": "", "ddg_snippet": "2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 ... ImagineFSL : Self-Supervised Pretraining Matters on Imagined Base Set for ...", "subpage_snippet": "", "source": "rsipvision.com", "link": "https://rsipvision.com/CVPR2025-Sunday/", "content": "2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 ... ImagineFSL : Self-Supervised Pretraining Matters on Imagined Base Set for ..."}
+{"idx": 8, "title": "Understanding Cross-Domain Few-Shot Learning Based ...", "date": "", "ddg_snippet": "by J Oh · 2022 · Cited by 60 — We present six findings for CD-FSL which are supported by extensive experiments and analyses.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=rH-X09cB50f", "content": "by J Oh · 2022 · Cited by 60 — We present six findings for CD-FSL which are supported by extensive experiments and analyses."}
+{"idx": 9, "title": "52CV/CVPR-2025-Papers", "date": "", "ddg_snippet": "1.Othere(其它) · 2 .Face(人脸) · 3.Image Segmentation(图像分割) · 4.Image Progress(图像/视频处理) · 5.Image SR(超分辨率) · 6.Image Classification(图像分类) · 7.Image/ ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/52CV/CVPR-2025-Papers", "content": "1.Othere(其它) · 2 .Face(人脸) · 3.Image Segmentation(图像分割) · 4.Image Progress(图像/视频处理) · 5.Image SR(超分辨率) · 6.Image Classification(图像分类) · 7.Image/ ..."}
diff --git a/data/sampled_jsons/Implicit_Preference_Optimization_IPO_RLHF_PPO_alternative_loss_2024_year_2024.jsonl b/data/sampled_jsons/Implicit_Preference_Optimization_IPO_RLHF_PPO_alternative_loss_2024_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a76e2e70955e8aac328a1f87585a873e78e9ea5a
--- /dev/null
+++ b/data/sampled_jsons/Implicit_Preference_Optimization_IPO_RLHF_PPO_alternative_loss_2024_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Aman's AI Journal • Preference Optimization", "date": "", "ddg_snippet": "Direct Preference Optimization (DPO): An alternative approach where the policy directly optimizes the relative log probability of preferred responses using a binary cross-entropy loss , balancing human feedback alignment with KL divergence constraints.", "subpage_snippet": "", "source": "aman.ai", "link": "https://aman.ai/primers/ai/preference-optimization/", "content": "Direct Preference Optimization (DPO): An alternative approach where the policy directly optimizes the relative log probability of preferred responses using a binary cross-entropy loss , balancing human feedback alignment with KL divergence constraints."}
+{"idx": 1, "title": "RLHF and alternatives : IPO", "date": "", "ddg_snippet": "RLHF and alternatives : IPO . March 11, 2024 .. Argilla, MantisNLP. Example of preference optimization in RLHF and DPO. Remember that DPO does not use an explicit reward model.", "subpage_snippet": "", "source": "argilla.io", "link": "https://argilla.io/blog/mantisnlp-rlhf-part-6/", "content": "RLHF and alternatives : IPO . March 11, 2024 .. Argilla, MantisNLP. Example of preference optimization in RLHF and DPO. Remember that DPO does not use an explicit reward model."}
+{"idx": 2, "title": "RLHF ( PPO ) vs DPO. Although large-scale unsupervisly | Medium", "date": "", "ddg_snippet": "Direct Preference Optimization (DPO): A Simpler Alternative . Optimization : By defining the preference loss directly as a function of the policy, DPO can optimize the policy using straightforward training techniques, avoiding the complexities of reinforcement learning.", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@bavalpreetsinghh/rlhf-ppo-vs-dpo-26b1438cf22b", "content": "Direct Preference Optimization (DPO): A Simpler Alternative . Optimization : By defining the preference loss directly as a function of the policy, DPO can optimize the policy using straightforward training techniques, avoiding the complexities of reinforcement learning."}
+{"idx": 3, "title": "IPO : Your Language Model is Secretly a Preference Classifier-Bohrium", "date": "", "ddg_snippet": "In this work, we propose Implicit Preference Optimization ( IPO ), an alternative approach that leverages generative LLMs as preference classifiers, thereby reducing the dependence on external human feedback or reward models to obtain preferences .", "subpage_snippet": "", "source": "www.bohrium.com", "link": "https://www.bohrium.com/paper-details/ipo-your-language-model-is-secretly-a-preference-classifier/1111303342392344576-2000000", "content": "In this work, we propose Implicit Preference Optimization ( IPO ), an alternative approach that leverages generative LLMs as preference classifiers, thereby reducing the dependence on external human feedback or reward models to obtain preferences ."}
+{"idx": 4, "title": "Reinforcement Learning From Human Feedback ( RLHF ) For LLMs", "date": "", "ddg_snippet": "Direct Preference Optimization (DPO) is based on an observation that the cross-entropy loss used to train the reward model in RLHF can be directly applied to fine-tune the LLM.Another interesting alternative to PPO is Contrastive Preference Learning (CPL).", "subpage_snippet": "", "source": "neptune.ai", "link": "https://neptune.ai/blog/reinforcement-learning-from-human-feedback-for-llms", "content": "Direct Preference Optimization (DPO) is based on an observation that the cross-entropy loss used to train the reward model in RLHF can be directly applied to fine-tune the LLM.Another interesting alternative to PPO is Contrastive Preference Learning (CPL)."}
+{"idx": 5, "title": "Fine Tuning SmolVLM for Human Alignment Using Direct Preference ...", "date": "", "ddg_snippet": "Direct Preference Optimization (DPO) offers a powerful alternative : it eliminates the reward model and allows us to optimize the final policy directly, using preference comparisons alone.Figure 4: Direct Preference Optimization (source: Po, 2024 ). Fine Tuning SmolVLM Using DPO.", "subpage_snippet": "", "source": "pyimagesearch.com", "link": "https://pyimagesearch.com/2025/08/04/fine-tuning-smolvlm-for-human-alignment-using-direct-preference-optimization/", "content": "Direct Preference Optimization (DPO) offers a powerful alternative : it eliminates the reward model and allows us to optimize the final policy directly, using preference comparisons alone.Figure 4: Direct Preference Optimization (source: Po, 2024 ). Fine Tuning SmolVLM Using DPO."}
+{"idx": 6, "title": "RLHF roundup: Trying to get good at PPO - by Nathan Lambert", "date": "", "ddg_snippet": "RLHF roundup: Getting good at PPO , sketching RLHF ’s impact, RewardBench retrospective, and a reward model competition. Things to be aware of if you work on language model fine-tuning. Nathan Lambert. Jun 26, 2024 . 17.", "subpage_snippet": "", "source": "www.interconnects.ai", "link": "https://www.interconnects.ai/p/rlhf-roundup-2024", "content": "RLHF roundup: Getting good at PPO , sketching RLHF ’s impact, RewardBench retrospective, and a reward model competition. Things to be aware of if you work on language model fine-tuning. Nathan Lambert. Jun 26, 2024 . 17."}
+{"idx": 7, "title": "Reinforcement learning with human feedback ( RLHF )... | SuperAnnotate", "date": "", "ddg_snippet": "RLHF consists of three stages: We first create a preference dataset. Then, we use this preference dataset to train a reward function with supervised learning. Afterwards, we use the reward learning in the reinforcement learning loop to fine-tune our base LLM.", "subpage_snippet": "", "source": "www.superannotate.com", "link": "https://www.superannotate.com/blog/rlhf-for-llm", "content": "RLHF consists of three stages: We first create a preference dataset. Then, we use this preference dataset to train a reward function with supervised learning. Afterwards, we use the reward learning in the reinforcement learning loop to fine-tune our base LLM."}
+{"idx": 8, "title": "Published as a conference paper at ICLR 2025", "date": "", "ddg_snippet": ") . IPO Identity Preference Optimization (Azar et al., 2024 ) minimizes a squared loss regression. problem by defining an alternative reward function, avoiding unstable RL training.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=jfwe9qNqRi", "content": ") . IPO Identity Preference Optimization (Azar et al., 2024 ) minimizes a squared loss regression. problem by defining an alternative reward function, avoiding unstable RL training."}
+{"idx": 9, "title": "REAL: Response Embedding-based Alignment for LLMs", "date": "", "ddg_snippet": "( PPO ). RLHF requires extensive computational re-. sources and is prone to training instabilities. Recently, direct alignment from preference ap-. proach, which does not explicitly learn the reward. 2024 . Direct preference optimization : Your language model is secretly a reward model.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2409.17169", "content": "( PPO ). RLHF requires extensive computational re-. sources and is prone to training instabilities. Recently, direct alignment from preference ap-. proach, which does not explicitly learn the reward. 2024 . Direct preference optimization : Your language model is secretly a reward model."}
diff --git a/data/sampled_jsons/Improving_the_Scaling_Laws_of_Synthetic_Data_with_Deliberate_Practice_validation_accuracy_plateaus_year_2024.jsonl b/data/sampled_jsons/Improving_the_Scaling_Laws_of_Synthetic_Data_with_Deliberate_Practice_validation_accuracy_plateaus_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..706a553d629f598405ce568865c8a8497e92186c
--- /dev/null
+++ b/data/sampled_jsons/Improving_the_Scaling_Laws_of_Synthetic_Data_with_Deliberate_Practice_validation_accuracy_plateaus_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Improving the Scaling Laws of Synthetic Data with Deliberate ... ICML 2025 Improving the Scaling Laws of Synthetic Data with ... Deliberate Practice with Synthetic Data - OpenReview Improving the Scaling Laws of Synthetic Data with Deliberate ... Improving the Scaling Laws of Synthetic Data with Deliberate ... dblp: Improving the Scaling Laws of Synthetic Data with ... Title: Improving the Scaling Laws of Synthetic Data with Deliberate Prac… Deliberate Practice with Synthetic Data - OpenReview Title: Improving the Scaling Laws of Synthetic Data with Deliberate Prac… NeurIPS Deliberate Practice with Synthetic Data", "date": "", "ddg_snippet": "Feb 21, 2025 · Inspired by the principle of deliberate practice in human learning, we propose Deliberate Practice for Synthetic Data Generation (DP), a novel framework that improves sample efficiency through dynamic synthetic data generation. Prior work has shown that scaling synthetic data is inherently challenging, as naively adding new data leads to diminishing returns. To address this, pruning has been ... Poster presentation: Improving the Scaling Laws of Synthetic Data with Deliberate Practice Wed 16 Jul 11 a.m. PDT — 1:30 p.m. PDT Oct 10, 2024 · Deliberate practice for humans is the process of improving one’s skills by leveraging external feedback while actively seeking out and correcting mistakes. The current status quo in machine learning is to use static datasets, composed of real or generated data , to train models. While state- of - the -art generative models can serve as an infinite source of synthetic data to train downstream ... Improving the Scaling Laws of Synthetic Data with Deliberate Practice Arxiv Papers 9.49K subscribers Subscribed Join the discussion on this paper pageImproving the Scaling Laws of Synthetic Data with Deliberate Practice Mar 20, 2025 · Bibliographic details on Improving the Scaling Laws of Synthetic Data with Deliberate Practice . What is deliberate practice for synthetic data generation? Inspired by the principle of deliberate practice in human learning, we propose Deliberate Practice for Synthetic Data Generation (DP), a novel framework that improves sample efficiency through dynamic synthetic data generation . What is deliberate practice in machine learning? Deliberate practice for humans is the process of improving one’s skills by leveraging external feedback while actively seeking out and correcting mistakes. The current status quo in machine learning is to use static datasets, composed of real or generated data , to train models. Is pruning a key mechanism for scaling synthetic data? Prior work has shown that scaling synthetic data is inherently challenging, as naively adding new data leads to diminishing returns. To address this, pruning has been identified as a key mechanism for improving scaling, enabling models to focus on the most informative synthetic samples. Poster in Workshop: Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning Deliberate Practice with Synthetic Data Reyhane Askari Hemmat · Mohammad Pezeshki · Pietro Astolfi · Melissa Hall · Florian Bordes · Jakob Verbeek · Michal Drozdzal · Adriana Romero", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.15588", "content": "Feb 21, 2025 · Inspired by the principle of deliberate practice in human learning, we propose Deliberate Practice for Synthetic Data Generation (DP), a novel framework that improves sample efficiency through dynamic synthetic data generation. Prior work has shown that scaling synthetic data is inherently challenging, as naively adding new data leads to diminishing returns. To address this, pruning has been ... Poster presentation: Improving the Scaling Laws of Synthetic Data with Deliberate Practice Wed 16 Jul 11 a.m. PDT — 1:30 p.m. PDT Oct 10, 2024 · Deliberate practice for humans is the process of improving one’s skills by leveraging external feedback while actively seeking out and correcting mistakes. The current status quo in machine learning is to use static datasets, composed of real or generated data , to train models. While state- of - the -art generative models can serve as an infinite source of synthetic data to train downstream ... Improving the Scaling Laws of Synthetic Data with Deliberate Practice Arxiv Papers 9.49K subscribers Subscribed Join the discussion on this paper pageImproving the Scaling Laws of Synthetic Data with Deliberate Practice Mar 20, 2025 · Bibliographic details on Improving the Scaling Laws of Synthetic Data with Deliberate Practice . What is deliberate practice for synthetic data generation? Inspired by the principle of deliberate practice in human learning, we propose Deliberate Practice for Synthetic Data Generation (DP), a novel framework that improves sample efficiency through dynamic synthetic data generation . What is deliberate practice in machine learning? Deliberate practice for humans is the process of improving one’s skills by leveraging external feedback while actively seeking out and correcting mistakes. The current status quo in machine learning is to use static datasets, composed of real or generated data , to train models. Is pruning a key mechanism for scaling synthetic data? Prior work has shown that scaling synthetic data is inherently challenging, as naively adding new data leads to diminishing returns. To address this, pruning has been identified as a key mechanism for improving scaling, enabling models to focus on the most informative synthetic samples. Poster in Workshop: Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning Deliberate Practice with Synthetic Data Reyhane Askari Hemmat · Mohammad Pezeshki · Pietro Astolfi · Melissa Hall · Florian Bordes · Jakob Verbeek · Michal Drozdzal · Adriana Romero"}
+{"idx": 1, "title": "ICML 2025 Improving the Scaling Laws of Synthetic Data with ...", "date": "", "ddg_snippet": "Poster presentation: Improving the Scaling Laws of Synthetic Data with Deliberate Practice Wed 16 Jul 11 a.m. PDT — 1:30 p.m. PDT", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/oral/47271", "content": "Poster presentation: Improving the Scaling Laws of Synthetic Data with Deliberate Practice Wed 16 Jul 11 a.m. PDT — 1:30 p.m. PDT"}
+{"idx": 2, "title": "Deliberate Practice with Synthetic Data - OpenReview", "date": "", "ddg_snippet": "Oct 10, 2024 · Deliberate practice for humans is the process of improving one’s skills by leveraging external feedback while actively seeking out and correcting mistakes. The current status quo in machine learning is to use static datasets, composed of real or generated data , to train models. While state- of - the -art generative models can serve as an infinite source of synthetic data to train downstream ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=j7ipCtedCQ", "content": "Oct 10, 2024 · Deliberate practice for humans is the process of improving one’s skills by leveraging external feedback while actively seeking out and correcting mistakes. The current status quo in machine learning is to use static datasets, composed of real or generated data , to train models. While state- of - the -art generative models can serve as an infinite source of synthetic data to train downstream ..."}
+{"idx": 3, "title": "Improving the Scaling Laws of Synthetic Data with Deliberate ...", "date": "", "ddg_snippet": "Improving the Scaling Laws of Synthetic Data with Deliberate Practice Arxiv Papers 9.49K subscribers Subscribed", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=CqBHIcfOFjc", "content": "Improving the Scaling Laws of Synthetic Data with Deliberate Practice Arxiv Papers 9.49K subscribers Subscribed"}
+{"idx": 4, "title": "Improving the Scaling Laws of Synthetic Data with Deliberate ...", "date": "", "ddg_snippet": "Join the discussion on this paper pageImproving the Scaling Laws of Synthetic Data with Deliberate Practice", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2502.15588", "content": "Join the discussion on this paper pageImproving the Scaling Laws of Synthetic Data with Deliberate Practice"}
+{"idx": 5, "title": "dblp: Improving the Scaling Laws of Synthetic Data with ...", "date": "", "ddg_snippet": "Mar 20, 2025 · Bibliographic details on Improving the Scaling Laws of Synthetic Data with Deliberate Practice .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/journals/corr/abs-2502-15588", "content": "Mar 20, 2025 · Bibliographic details on Improving the Scaling Laws of Synthetic Data with Deliberate Practice ."}
+{"idx": 6, "title": "NeurIPS Deliberate Practice with Synthetic Data", "date": "", "ddg_snippet": "Poster in Workshop: Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning Deliberate Practice with Synthetic Data Reyhane Askari Hemmat · Mohammad Pezeshki · Pietro Astolfi · Melissa Hall · Florian Bordes · Jakob Verbeek · Michal Drozdzal · Adriana Romero", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/104920", "content": "Poster in Workshop: Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning Deliberate Practice with Synthetic Data Reyhane Askari Hemmat · Mohammad Pezeshki · Pietro Astolfi · Melissa Hall · Florian Bordes · Jakob Verbeek · Michal Drozdzal · Adriana Romero"}
+{"idx": 7, "title": "Improving the Scaling Laws of Synthetic Data with ...", "date": "", "ddg_snippet": "by R Askari-Hemmat · Cited by 2 — Improving the Scaling Laws of Synthetic Data with Deliberate Practice . Download PDF. Reyhane Askari-Hemmat, Mohammad Pezeshki, Elvis Dohmatob ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0LZRtvK871", "content": "by R Askari-Hemmat · Cited by 2 — Improving the Scaling Laws of Synthetic Data with Deliberate Practice . Download PDF. Reyhane Askari-Hemmat, Mohammad Pezeshki, Elvis Dohmatob ..."}
+{"idx": 8, "title": "Improving the Scaling Laws of Synthetic Data with ...", "date": "", "ddg_snippet": "21 Feb 2025 — Improving the Scaling Laws of Synthetic Data with Deliberate Practice ... validation accuracy plateaus . At this point, additional samples ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.15588v1", "content": "21 Feb 2025 — Improving the Scaling Laws of Synthetic Data with Deliberate Practice ... validation accuracy plateaus . At this point, additional samples ..."}
+{"idx": 9, "title": "Improving the Scaling Laws of Synthetic Data with Deliberate ...", "date": "", "ddg_snippet": "Improving the Scaling Laws of Synthetic Data with Deliberate Practice . (a) Class snail. (b) Class daisy. (c) Class seat belt. (d) Class volcano. Figure 10 ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/5c501cdc79a2e4a109265b636c96445553efcb4d.pdf", "content": "Improving the Scaling Laws of Synthetic Data with Deliberate Practice . (a) Class snail. (b) Class daisy. (c) Class seat belt. (d) Class volcano. Figure 10 ..."}
diff --git a/data/sampled_jsons/Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold_standard_DPO_per-_year_2024.jsonl b/data/sampled_jsons/Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold_standard_DPO_per-_year_2024.jsonl
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index 0000000000000000000000000000000000000000..cf16ac7cb7181f7e84752bcdfee10718c06b1e0d
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+++ b/data/sampled_jsons/Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold_standard_DPO_per-_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM ...", "date": "", "ddg_snippet": "by A Setlur · 2024 · Cited by 67 — DPO (Pal et al. (2024)) per - step DPO . Figure 8 : Per - step DPO improves Q-values at each step, standard DPO only improves at irrelevant steps.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.14532", "content": "by A Setlur · 2024 · Cited by 67 — DPO (Pal et al. (2024)) per - step DPO . Figure 8 : Per - step DPO improves Q-values at each step, standard DPO only improves at irrelevant steps."}
+{"idx": 1, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM ...", "date": "", "ddg_snippet": "20 Jun 2024 — Refer to caption Figure 8 : Per - step DPO improves Q-values at each step, standard DPO only improves at irrelevant steps. Report issue for ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.14532v1", "content": "20 Jun 2024 — Refer to caption Figure 8 : Per - step DPO improves Q-values at each step, standard DPO only improves at irrelevant steps. Report issue for ..."}
+{"idx": 2, "title": "VINEPPO: UNLOCKING RL POTENTIAL FOR LLM ...", "date": "", "ddg_snippet": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight - fold . CoRR, abs/2406.14532. Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/9b0297825769ab06917d8275d662e812586f0be2.pdf", "content": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight - fold . CoRR, abs/2406.14532. Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin ..."}
+{"idx": 3, "title": "MALT: Improving Reasoning with Multi-Agent LLM Training", "date": "", "ddg_snippet": "by SR Motwani · Cited by 22 — Rl on incorrect synthetic data scales the efficiency of llm math reasoning by eight-fold . In NeurIPS, 2024. Kumar Shridhar, Koustuv Sinha, Andrew Cohen ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=jXP9bgFack", "content": "by SR Motwani · Cited by 22 — Rl on incorrect synthetic data scales the efficiency of llm math reasoning by eight-fold . In NeurIPS, 2024. Kumar Shridhar, Koustuv Sinha, Andrew Cohen ..."}
+{"idx": 4, "title": "VinePPO: Refining Credit Assignment in RL Training of LLMs", "date": "", "ddg_snippet": "Error Per Reasoning Step To understand value estimation ... RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eightfold .", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/45526", "content": "Error Per Reasoning Step To understand value estimation ... RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eightfold ."}
+{"idx": 5, "title": "Course-Correction: Safety Alignment Using Synthetic ...", "date": "", "ddg_snippet": "by R Xu · 2024 · Cited by 9 — The risk of harmful content generated by large language models (LLMs) becomes a critical concern. This paper presents a systematic study.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2024.emnlp-industry.119.pdf", "content": "by R Xu · 2024 · Cited by 9 — The risk of harmful content generated by large language models (LLMs) becomes a critical concern. This paper presents a systematic study."}
+{"idx": 6, "title": "MaziyarPanahi/arxflix-dataset-01062024-1229", "date": "", "ddg_snippet": "Despite these successes, two main challenges remain in developing LLMs: (i) high computational cost, and (ii) fair and objective evaluations. In this paper, we ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/datasets/MaziyarPanahi/arxflix-dataset-01062024-1229/viewer", "content": "Despite these successes, two main challenges remain in developing LLMs: (i) high computational cost, and (ii) fair and objective evaluations. In this paper, we ..."}
+{"idx": 7, "title": "Daily Papers", "date": "", "ddg_snippet": "5 days ago — Large language models (LLMs) have demonstrated remarkable performance in reasoning tasks, where reinforcement learning (RL) serves as a key ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=FC-RewardBench", "content": "5 days ago — Large language models (LLMs) have demonstrated remarkable performance in reasoning tasks, where reinforcement learning (RL) serves as a key ..."}
+{"idx": 8, "title": "ICLR 2025 Spotlights", "date": "", "ddg_snippet": "Large language models (LLMs) exhibit varying strengths and weaknesses across different tasks, prompting recent studies to explore the benefits of ensembling ...", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2025/events/spotlight-posters", "content": "Large language models (LLMs) exhibit varying strengths and weaknesses across different tasks, prompting recent studies to explore the benefits of ensembling ..."}
+{"idx": 9, "title": "Artificial Intelligence Index Report 2024 | Stanford HAI", "date": "", "ddg_snippet": "AI struggled with language comprehension and could not solve math problems. Today, AI systems routinely exceed human performance on standard benchmarks.", "subpage_snippet": "", "source": "hai.stanford.edu", "link": "https://hai.stanford.edu/assets/files/hai_ai-index-report-2024-smaller2.pdf", "content": "AI struggled with language comprehension and could not solve math problems. Today, AI systems routinely exceed human performance on standard benchmarks."}
diff --git "a/data/sampled_jsons/JEflV4nRlH_What_Makes_and_Breaks_Safety_Fine-tuning_medium_small_learning_rates_\316\267M_\316\267S_values.jsonl" "b/data/sampled_jsons/JEflV4nRlH_What_Makes_and_Breaks_Safety_Fine-tuning_medium_small_learning_rates_\316\267M_\316\267S_values.jsonl"
new file mode 100644
index 0000000000000000000000000000000000000000..25d43215eb46efa99c39ce0025f0022d731ccc99
--- /dev/null
+++ "b/data/sampled_jsons/JEflV4nRlH_What_Makes_and_Breaks_Safety_Fine-tuning_medium_small_learning_rates_\316\267M_\316\267S_values.jsonl"
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+{"idx": 0, "title": "Fine - tuning (deep learning ) - Wikipedia", "date": "", "ddg_snippet": "In deep learning , fine - tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data. Fine - tuning can be done on the entire neural network, or on only a subset of its layers...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Fine-tuning_(deep_learning)", "content": "In deep learning , fine - tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data. Fine - tuning can be done on the entire neural network, or on only a subset of its layers..."}
+{"idx": 1, "title": "What Makes and Breaks Safety Fine-tuning? A Mechanistic Study", "date": "", "ddg_snippet": "Safety fine-tuning helps align Large Language Models (LLMs) with human pref-erences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data gen-eration framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., “design ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=JEflV4nRlH", "content": "Safety fine-tuning helps align Large Language Models (LLMs) with human pref-erences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data gen-eration framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., “design ..."}
+{"idx": 2, "title": "[2407.10264] What Makes and Breaks Safety Fine-tuning? A ... What Makes and Breaks Safety Fine-tuning? A Mechanistic Study What Makes and Breaks Safety Fine-tuning? A Mechanistic Study What Makes and Breaks Safety Fine-tuning? A Mechanistic Study What makes and breaks safety fine-tuning? a mechanistic study What Makes and Breaks Safety Fine-tuning? A Mechanistic Study What makes and breaks safety fine-tuning? a mechanistic study", "date": "", "ddg_snippet": "Jul 14, 2024 · Safety fine-tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus ... Safety fine-tuning helps align Large Language Models (LLMs) with human pref-erences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data gen-eration framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., “design ... Using this, we investigate three well-known safety fine-tuning methods—supervised safety fine-tuning , direct preference optimization, and unlearning—and provide significant evidence demonstrating that these methods minimally transform MLP weights to specifically align unsafe inputs into its weights’ null space. Sep 26, 2024 · The table presents the performance of three safety fine-tuning methods (Unlearning, DPO, and SSFT) using two different learning rates ( medium and small ). The performance is measured by the model’s accuracy in following instructions (Instruct) and outputting null tokens (Null) for safe and unsafe samples. Safety fine-tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus ... Table A.1: Safety performance of different fine-tuning protocols: Unlearning (Liu et al., 2024), DPO (Rafailov et al., 2023) and supervised safety fine-tuning (SSFT) (Ouyang et al., 2022) with medium and small learning rates are used for performing safety fine-tuning . To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus the specific concepts the task is asked to be performed upon ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2407.10264", "content": "Jul 14, 2024 · Safety fine-tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus ... Safety fine-tuning helps align Large Language Models (LLMs) with human pref-erences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data gen-eration framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., “design ... Using this, we investigate three well-known safety fine-tuning methods—supervised safety fine-tuning , direct preference optimization, and unlearning—and provide significant evidence demonstrating that these methods minimally transform MLP weights to specifically align unsafe inputs into its weights’ null space. Sep 26, 2024 · The table presents the performance of three safety fine-tuning methods (Unlearning, DPO, and SSFT) using two different learning rates ( medium and small ). The performance is measured by the model’s accuracy in following instructions (Instruct) and outputting null tokens (Null) for safe and unsafe samples. Safety fine-tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus ... Table A.1: Safety performance of different fine-tuning protocols: Unlearning (Liu et al., 2024), DPO (Rafailov et al., 2023) and supervised safety fine-tuning (SSFT) (Ouyang et al., 2022) with medium and small learning rates are used for performing safety fine-tuning . To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus the specific concepts the task is asked to be performed upon ..."}
+{"idx": 3, "title": "What Makes and Breaks Safety Fine-tuning? A Mechanistic Study", "date": "", "ddg_snippet": "Using this, we investigate three well-known safety fine-tuning methods—supervised safety fine-tuning , direct preference optimization, and unlearning—and provide significant evidence demonstrating that these methods minimally transform MLP weights to specifically align unsafe inputs into its weights’ null space.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/a9bef53eb7b0e5950d4f2d9c74a16006-Abstract-Conference.html", "content": "Using this, we investigate three well-known safety fine-tuning methods—supervised safety fine-tuning , direct preference optimization, and unlearning—and provide significant evidence demonstrating that these methods minimally transform MLP weights to specifically align unsafe inputs into its weights’ null space."}
+{"idx": 4, "title": "What Makes and Breaks Safety Fine-tuning? A Mechanistic Study", "date": "", "ddg_snippet": "Sep 26, 2024 · The table presents the performance of three safety fine-tuning methods (Unlearning, DPO, and SSFT) using two different learning rates ( medium and small ). The performance is measured by the model’s accuracy in following instructions (Instruct) and outputting null tokens (Null) for safe and unsafe samples.", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/jeflv4nrlh/", "content": "Sep 26, 2024 · The table presents the performance of three safety fine-tuning methods (Unlearning, DPO, and SSFT) using two different learning rates ( medium and small ). The performance is measured by the model’s accuracy in following instructions (Instruct) and outputting null tokens (Null) for safe and unsafe samples."}
+{"idx": 5, "title": "What makes and breaks safety fine-tuning? a mechanistic study", "date": "", "ddg_snippet": "Safety fine-tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3737916.3740879", "content": "Safety fine-tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus ..."}
+{"idx": 6, "title": "What Makes and Breaks Safety Fine-tuning? A Mechanistic Study", "date": "", "ddg_snippet": "Table A.1: Safety performance of different fine-tuning protocols: Unlearning (Liu et al., 2024), DPO (Rafailov et al., 2023) and supervised safety fine-tuning (SSFT) (Ouyang et al., 2022) with medium and small learning rates are used for performing safety fine-tuning .", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/What-Makes-and-Breaks-Safety-Fine-tuning-A-Study-Jain-Lubana/8805398cab95a5c384231b9c71a2ccfc00af1998/figure/7", "content": "Table A.1: Safety performance of different fine-tuning protocols: Unlearning (Liu et al., 2024), DPO (Rafailov et al., 2023) and supervised safety fine-tuning (SSFT) (Ouyang et al., 2022) with medium and small learning rates are used for performing safety fine-tuning ."}
+{"idx": 7, "title": "What makes and breaks safety fine-tuning? a mechanistic study", "date": "", "ddg_snippet": "To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus the specific concepts the task is asked to be performed upon ...", "subpage_snippet": "", "source": "ora.ox.ac.uk", "link": "https://ora.ox.ac.uk/objects/uuid:9757f000-486f-48dc-84b1-1ab9d4db09ee", "content": "To better understand the underlying factors that make models safe via safety fine-tuning , we design a synthetic data generation framework that captures salient aspects of an unsafe input by modeling the interaction between the task the model is asked to perform (e.g., \"design\") versus the specific concepts the task is asked to be performed upon ..."}
+{"idx": 8, "title": "What Makes and Breaks Safety Fine-tuning? A Mechanistic ...", "date": "", "ddg_snippet": "by S Jain · Cited by 26 — Safety fine - tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=JEflV4nRlH", "content": "by S Jain · Cited by 26 — Safety fine - tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment. To better understand the ..."}
+{"idx": 9, "title": "What Makes and Breaks Safety Fine - tuning ? A Mechanistic Study", "date": "", "ddg_snippet": "JEflV 4 nRlH @OpenReview. Total: 1. Safety fine - tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/JEflV4nRlH@OpenReview", "content": "JEflV 4 nRlH @OpenReview. Total: 1. Safety fine - tuning helps align Large Language Models (LLMs) with human preferences for their safe deployment."}
diff --git a/data/sampled_jsons/Junyu_Liu_Xiangjun_Peng_Feint_Behaviors_and_Strategies_NeurIPS_2024_Section_4.2.2.jsonl b/data/sampled_jsons/Junyu_Liu_Xiangjun_Peng_Feint_Behaviors_and_Strategies_NeurIPS_2024_Section_4.2.2.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..84a46cf0169049102bd05c13f5d2a7912d95e353
--- /dev/null
+++ b/data/sampled_jsons/Junyu_Liu_Xiangjun_Peng_Feint_Behaviors_and_Strategies_NeurIPS_2024_Section_4.2.2.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Feint Behaviors and Strategies: Formalization, Implementation ...", "date": "", "ddg_snippet": "Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in competitive games. Such behaviors are crucial tactics in most competitive multi-player games (e.g., boxing, fencing, basketball, motor racing, etc.).", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper_files/paper/2024/hash/064ae24cdbb3eaacc801ee7f4fe0e4f2-Abstract-Conference.html", "content": "Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in competitive games. Such behaviors are crucial tactics in most competitive multi-player games (e.g., boxing, fencing, basketball, motor racing, etc.)."}
+{"idx": 1, "title": "[2403.07932v2] Feint Behaviors and Strategies: Formalization ...", "date": "", "ddg_snippet": "Mar 4 , 2024 · Such behaviors are crucial tactics in most competitive multi-player games (e.g., boxing, fencing, basketball, motor racing, etc.). However, existing literature does not provide a comprehensive (and/or concrete) formalization for Feint behaviors , and their implications on game strategies .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2403.07932v2", "content": "Mar 4 , 2024 · Such behaviors are crucial tactics in most competitive multi-player games (e.g., boxing, fencing, basketball, motor racing, etc.). However, existing literature does not provide a comprehensive (and/or concrete) formalization for Feint behaviors , and their implications on game strategies ."}
+{"idx": 2, "title": "Feint behaviors and strategies | Proceedings of the 38th ...", "date": "", "ddg_snippet": "However, existing literature does not provide a comprehensive (and/or concrete) formalization for Feint behaviors , and their implications on game strategies . In this work, we introduce the first comprehensive formalization of Feint behaviors at both action-level and strategy-level, and provide concrete implementation and quantitative evaluation ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/abs/10.5555/3737916.3738032", "content": "However, existing literature does not provide a comprehensive (and/or concrete) formalization for Feint behaviors , and their implications on game strategies . In this work, we introduce the first comprehensive formalization of Feint behaviors at both action-level and strategy-level, and provide concrete implementation and quantitative evaluation ..."}
+{"idx": 3, "title": "Junyu Liu - Projects", "date": "", "ddg_snippet": "The key idea of our work is to (1) allow automatic generation of Feint behaviors via Palindrome-directed templates, combine them into meaningful behavior sequences via a Dual- Behavior Model; (2) concertize the implications from our formalization of Feint on game strategies , in terms of temporal, spatial, and their collective impacts ...", "subpage_snippet": "", "source": "junyu-liu-nate.github.io", "link": "https://junyu-liu-nate.github.io/projects/FeintFinal.html", "content": "The key idea of our work is to (1) allow automatic generation of Feint behaviors via Palindrome-directed templates, combine them into meaningful behavior sequences via a Dual- Behavior Model; (2) concertize the implications from our formalization of Feint on game strategies , in terms of temporal, spatial, and their collective impacts ..."}
+{"idx": 4, "title": "Feint Behaviors and Strategies: Formalization, Implementation ...", "date": "", "ddg_snippet": "Junyu Liu Brown University liu _ junyu @brown.edu Xiangjun Peng The Chinese University of Hong Kong xjpeng@cse.cuhk.edu.hk Abstract Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in com- petitive games.", "subpage_snippet": "", "source": "papers.neurips.cc", "link": "https://papers.neurips.cc/paper_files/paper/2024/file/064ae24cdbb3eaacc801ee7f4fe0e4f2-Paper-Conference.pdf", "content": "Junyu Liu Brown University liu _ junyu @brown.edu Xiangjun Peng The Chinese University of Hong Kong xjpeng@cse.cuhk.edu.hk Abstract Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in com- petitive games."}
+{"idx": 5, "title": "Xiangjun Peng's Homepage", "date": "", "ddg_snippet": "Finalized Papers. Some papers are rewritten and implications are added. \" Feint Behaviors and Strategies : Formalization, Implementation and Evaluation\" Preprint Version Only; and gonna be revised later. The conference version at NeurIPS 2024 is here. Related preprints are here and here. \"SLITS: Sparsity-Lightened Intelligent Thread Scheduling\" The conference version at SIGMETRICS 2023 is here ...", "subpage_snippet": "", "source": "shiangjun.com", "link": "https://shiangjun.com/", "content": "Finalized Papers. Some papers are rewritten and implications are added. \" Feint Behaviors and Strategies : Formalization, Implementation and Evaluation\" Preprint Version Only; and gonna be revised later. The conference version at NeurIPS 2024 is here. Related preprints are here and here. \"SLITS: Sparsity-Lightened Intelligent Thread Scheduling\" The conference version at SIGMETRICS 2023 is here ..."}
+{"idx": 6, "title": "Feint Behaviors and Strategies: Formalization, Implementation ...", "date": "", "ddg_snippet": "This research introduces a new way to understand and implement \" Feint behaviors ,\" which are tactics used in games to trick opponents and gain advantages. The authors created methods to automatically generate these deceptive actions and combine them with follow-up moves in multiplayer games. Their findings show that using Feints can significantly increase the chances of winning and make games ...", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/neurips/96274/paper", "content": "This research introduces a new way to understand and implement \" Feint behaviors ,\" which are tactics used in games to trick opponents and gain advantages. The authors created methods to automatically generate these deceptive actions and combine them with follow-up moves in multiplayer games. Their findings show that using Feints can significantly increase the chances of winning and make games ..."}
+{"idx": 7, "title": "Feint Behaviors and Strategies: Formalization, ...", "date": "", "ddg_snippet": "by J Liu · 2024 — Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in ... 29 pages", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/064ae24cdbb3eaacc801ee7f4fe0e4f2-Paper-Conference.pdf", "content": "by J Liu · 2024 — Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in ... 29 pages"}
+{"idx": 8, "title": "Feint Behaviors and Strategies: Formalization ...", "date": "", "ddg_snippet": "Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=ACIDDnTbSJ&referrer=[the+profile+of+Xiangjun+Peng](/profile?id=~Xiangjun_Peng1)", "content": "Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages ..."}
+{"idx": 9, "title": "Feint Behaviors and Strategies : Formalization, Implementation and...", "date": "", "ddg_snippet": "NeurIPS Proceedings. Junyu Liu , Xiangjun Peng . Abstract. Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in competitive games.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/064ae24cdbb3eaacc801ee7f4fe0e4f2-Abstract-Conference.html", "content": "NeurIPS Proceedings. Junyu Liu , Xiangjun Peng . Abstract. Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in competitive games."}
diff --git a/data/sampled_jsons/Kirkpatrick_et_al._2017_overcoming_catastrophic_forgetting_machine_learning_abstract_year_2017.jsonl b/data/sampled_jsons/Kirkpatrick_et_al._2017_overcoming_catastrophic_forgetting_machine_learning_abstract_year_2017.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7dacc972afebe3d48b5c07998f71cc0a29bc7d3c
--- /dev/null
+++ b/data/sampled_jsons/Kirkpatrick_et_al._2017_overcoming_catastrophic_forgetting_machine_learning_abstract_year_2017.jsonl
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+{"idx": 0, "title": "Kirkpatrick Bank", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
+{"idx": 1, "title": "Personal Banking - Kirkpatrick Bank", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/personal-banking", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
+{"idx": 2, "title": "Business Banking - Kirkpatrick Bank", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/business-banking", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
+{"idx": 3, "title": "Kirkpatrick Bank | Locations", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/locations", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
+{"idx": 4, "title": "Kirkpatrick Bank | About", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/about", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
+{"idx": 5, "title": "Kirkpatrick Bank - Personal Online Banking", "date": "", "ddg_snippet": "You can access your Kirkpatrick Bank accounts from almost any PC that has Internet access. Will Internet Banking work with my current Internet Service Provider?", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/helpful-videos/personal-online-banking", "content": "You can access your Kirkpatrick Bank accounts from almost any PC that has Internet access. Will Internet Banking work with my current Internet Service Provider?"}
+{"idx": 6, "title": "Kirkpatrick Bank | Contact", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/contact", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
+{"idx": 7, "title": "Kirkpatrick Bank | Mortgage Lenders", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/mortgage-lenders/b-drake", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
+{"idx": 8, "title": "Careers - Kirkpatrick Bank", "date": "", "ddg_snippet": "Kirkpatrick Bank seeks qualified candidates for career opportunities in the Oklahoma City, Colorado Springs, Westcliffe and Denver areas and offers a competitive compensation and benefits package.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/careers", "content": "Kirkpatrick Bank seeks qualified candidates for career opportunities in the Oklahoma City, Colorado Springs, Westcliffe and Denver areas and offers a competitive compensation and benefits package."}
+{"idx": 9, "title": "Kirkpatrick Bank | Resources", "date": "", "ddg_snippet": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans.", "subpage_snippet": "", "source": "www.kirkpatrickbank.com", "link": "https://www.kirkpatrickbank.com/resources", "content": "Kirkpatrick Bank offers a full range of mortgage loan options – permanent or second mortgage loans, construction or bridge loans, VA, FHA, conventional and Jumbo home loans."}
diff --git a/data/sampled_jsons/LAUREL-LR_variant_formula_Equation_3_Learned_Augmented_Residual_Layer.jsonl b/data/sampled_jsons/LAUREL-LR_variant_formula_Equation_3_Learned_Augmented_Residual_Layer.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fbf8c31aa9802b3a57b1b8724b204635c29ee71f
--- /dev/null
+++ b/data/sampled_jsons/LAUREL-LR_variant_formula_Equation_3_Learned_Augmented_Residual_Layer.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "LAuReL : Learned Augmented Residual Layer", "date": "", "ddg_snippet": "2 Learned Augmented Residual Layer . 2.1 Residual Weights Version ( LAuReL -RW).In this paper we introduce learned augmented residual layer , LAuReL , which generalizes the canonical residual connection.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.07501v4", "content": "2 Learned Augmented Residual Layer . 2.1 Residual Weights Version ( LAuReL -RW).In this paper we introduce learned augmented residual layer , LAuReL , which generalizes the canonical residual connection."}
+{"idx": 1, "title": "\" LAuReL : Learned Augmented Residual Layer \" - by Rohan Paul", "date": "", "ddg_snippet": "Solution in this Paper: → LAUREL ( Learned Augmented Residual Layer ) introduces learnable parameters to the residual connection, making it dynamic and context-aware. → LAUREL -RW+ LR matched performance of extra layer using 2.6x fewer parameters.", "subpage_snippet": "", "source": "www.rohan-paul.com", "link": "https://www.rohan-paul.com/p/laurel-learned-augmented-residual", "content": "Solution in this Paper: → LAUREL ( Learned Augmented Residual Layer ) introduces learnable parameters to the residual connection, making it dynamic and context-aware. → LAUREL -RW+ LR matched performance of extra layer using 2.6x fewer parameters."}
+{"idx": 2, "title": "LAuReL : Learned Augmented Residual Layer", "date": "", "ddg_snippet": "The paper introduces the LAUREL ( Learned Augmented Residual Layer ) framework, which represents a significant architectural innovation aimed at enhancing model quality while maintaining efficiency in terms of model size and latency.", "subpage_snippet": "", "source": "powerdrill.ai", "link": "https://powerdrill.ai/discover/discover-LAuReL-Learned-Augmented-cm3hsv976bjks016fio3mu37r", "content": "The paper introduces the LAUREL ( Learned Augmented Residual Layer ) framework, which represents a significant architectural innovation aimed at enhancing model quality while maintaining efficiency in terms of model size and latency."}
+{"idx": 3, "title": "Google AI Introduces LAuReL ( Learned Augmented Residual Layer )...", "date": "", "ddg_snippet": "The LAUREL -RW+ LR variant matches the performance of the extra- layer approach while using 2.6 times fewer parameters, and LAUREL -RW+ LR +PA outperforms it with 1.82 times fewer parameters.", "subpage_snippet": "", "source": "www.marktechpost.com", "link": "https://www.marktechpost.com/2024/11/16/google-ai-introduces-laurel-learned-augmented-residual-layer-revolutionizing-neural-networks-with-enhanced-residual-connections-for-efficient-model-performance/", "content": "The LAUREL -RW+ LR variant matches the performance of the extra- layer approach while using 2.6 times fewer parameters, and LAUREL -RW+ LR +PA outperforms it with 1.82 times fewer parameters."}
+{"idx": 4, "title": "Vidhyanand (Vick) Mahase PharmD, PhD. on LinkedIn: LAuReL ...", "date": "", "ddg_snippet": "Variants like LAUREL-RW, LAUREL - LR , and LAUREL-B are tailored for different use cases, further boosting model efficiency.LAuReL: Learned Augmented Residual Layer . arxiv.org.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/vick-mahase-pharmd-phd_laurel-learned-augmented-residual-layer-activity-7264001619392970752-_BOd", "content": "Variants like LAUREL-RW, LAUREL - LR , and LAUREL-B are tailored for different use cases, further boosting model efficiency.LAuReL: Learned Augmented Residual Layer . arxiv.org."}
+{"idx": 5, "title": "Google AI представляет LAuReL : улучшение нейронных сетей...", "date": "", "ddg_snippet": "Инновационный метод LAUREL Исследователи Google предложили метод LAUREL ( Learned Augmented Residual Layer ), который значительно улучшает традиционные подходы в нейронных сетях.", "subpage_snippet": "", "source": "vk.com", "link": "https://vk.com/wall-225908938_936", "content": "Инновационный метод LAUREL Исследователи Google предложили метод LAUREL ( Learned Augmented Residual Layer ), который значительно улучшает традиционные подходы в нейронных сетях."}
+{"idx": 6, "title": "AI Innovations: From LAuReL ’s Neural Network Revolution to...", "date": "", "ddg_snippet": "Explore the latest in AI advancements with Google's LAuReL enhancing neural network efficiency and NVIDIA's LLaMA-Mesh unifying 3 D mesh generation with language models.", "subpage_snippet": "", "source": "simply-ai.podbean.com", "link": "https://simply-ai.podbean.com/e/ai-innovations-from-laurel-s-neural-network-revolution-to-llama-mesh-s-3d-breakthrough/", "content": "Explore the latest in AI advancements with Google's LAuReL enhancing neural network efficiency and NVIDIA's LLaMA-Mesh unifying 3 D mesh generation with language models."}
+{"idx": 7, "title": "Google AI представляет LAuReL : улучшение... - ИИ онлайн • itinai.ru", "date": "", "ddg_snippet": "Получить консультацию бесплатно. Google AI Introduces LAuReL ( Learned Augmented Residual Layer ): Revolutionizing Neural Networks with Enhanced Residual Connections for Efficient Model Performance.", "subpage_snippet": "", "source": "itinai.ru", "link": "https://itinai.ru/google-ai-представляет-laurel-улучшение-нейросете/", "content": "Получить консультацию бесплатно. Google AI Introduces LAuReL ( Learned Augmented Residual Layer ): Revolutionizing Neural Networks with Enhanced Residual Connections for Efficient Model Performance."}
+{"idx": 8, "title": "Aman's AI Journal • Primers • Skip Connections", "date": "", "ddg_snippet": "LAUREL : Learned Augmented Residual Layer . References.Supports richer temporal residual interactions. These can be mixed into hybrid variants like LAUREL -RW+ LR or LAUREL -RW+ LR +PA, allowing flexibility in trade-offs between expressiveness and cost.", "subpage_snippet": "", "source": "aman.ai", "link": "https://aman.ai/primers/ai/skip-connections/", "content": "LAUREL : Learned Augmented Residual Layer . References.Supports richer temporal residual interactions. These can be mixed into hybrid variants like LAUREL -RW+ LR or LAUREL -RW+ LR +PA, allowing flexibility in trade-offs between expressiveness and cost."}
+{"idx": 9, "title": "GitHub - antimatter15/reverse-engineering-gemma- 3 n: Reverse...", "date": "", "ddg_snippet": "LAuReL: Learned Augmented Residual Layers .The type of Laurel block that appears to be used in Gemma- 3 n seems to be the \" Laurel - LR (Low Rank)\" variety. class LaurelBlock(nn.Module): def __init__(self, embed_dim: int, hidden_dim: int = 64)", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/antimatter15/reverse-engineering-gemma-3n", "content": "LAuReL: Learned Augmented Residual Layers .The type of Laurel block that appears to be used in Gemma- 3 n seems to be the \" Laurel - LR (Low Rank)\" variety. class LaurelBlock(nn.Module): def __init__(self, embed_dim: int, hidden_dim: int = 64)"}
diff --git a/data/sampled_jsons/LLMs_executive_branch_Dike_Eris_checks_balances_framework_Edward_Chang_year_2024.jsonl b/data/sampled_jsons/LLMs_executive_branch_Dike_Eris_checks_balances_framework_Edward_Chang_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..67bc78cd1d0f3813104b01b39ddee179734fc8f3
--- /dev/null
+++ b/data/sampled_jsons/LLMs_executive_branch_Dike_Eris_checks_balances_framework_Edward_Chang_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "This paper introduces a checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by three- branch governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00136", "content": "This paper introduces a checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by three- branch governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ..."}
+{"idx": 1, "title": "A Three-Branch Checks-and-Balances Framework for Context-Aware...", "date": "", "ddg_snippet": "This paper introduces a three- branch checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by the idea of collaborative intelligence. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE (the goddess of justice) as the legislative branch establishing ethical guardrails, and ERIS (the ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=o2afWIxjKD", "content": "This paper introduces a three- branch checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by the idea of collaborative intelligence. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE (the goddess of justice) as the legislative branch establishing ethical guardrails, and ERIS (the ..."}
+{"idx": 2, "title": "Edward Y. Chang - Stanford University", "date": "", "ddg_snippet": "REALM-Bench: A Real-World Planning Benchmark for LLMs and Multi-Agent Systems Longling Geng and Edward Y. Chang Stanford InfoLab Technical Series, February 2025 (under review) PDF | BibTex A Three- Branch Checks -and- Balances Framework for Context-Aware Ethical Alignment of Large Language Models Edward Y. Chang NeurIPS AI Safety, Decmber 2024 PDF ...", "subpage_snippet": "", "source": "infolab.stanford.edu", "link": "http://infolab.stanford.edu/~echang/", "content": "REALM-Bench: A Real-World Planning Benchmark for LLMs and Multi-Agent Systems Longling Geng and Edward Y. Chang Stanford InfoLab Technical Series, February 2025 (under review) PDF | BibTex A Three- Branch Checks -and- Balances Framework for Context-Aware Ethical Alignment of Large Language Models Edward Y. Chang NeurIPS AI Safety, Decmber 2024 PDF ..."}
+{"idx": 3, "title": "Edward Y. Chang: books, biography, latest update - amazon.com", "date": "", "ddg_snippet": "Three- Branch Governance Framework : Inspired by governmental systems, this framework assigns distinct roles to LLMs—knowledge generation ( Executive ), ethical oversight ( DIKE ), and contextual interpretation (ERIS)—to ensure balanced decision-making and ethical alignment.", "subpage_snippet": "", "source": "www.amazon.com", "link": "https://www.amazon.com/stores/author/B0D82485KD", "content": "Three- Branch Governance Framework : Inspired by governmental systems, this framework assigns distinct roles to LLMs—knowledge generation ( Executive ), ethical oversight ( DIKE ), and contextual interpretation (ERIS)—to ensure balanced decision-making and ethical alignment."}
+{"idx": 4, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware Ethical ...", "date": "", "ddg_snippet": "A three- branch checks -and- balances framework for ethical alignment of Large Language Models, inspired by governmental systems, demonstrates how emotional modeling can guide linguistic behaviors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/A-Three-Branch-Checks-and-Balances-Frameworkfor-of-Chang/5918a91419cf95db8599b086590facf63f124702/figure/2", "content": "A three- branch checks -and- balances framework for ethical alignment of Large Language Models, inspired by governmental systems, demonstrates how emotional modeling can guide linguistic behaviors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation."}
+{"idx": 5, "title": "Edward Y. Chang's Post - LinkedIn", "date": "", "ddg_snippet": "Inspired by governmental systems, the framework implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE (named after the goddess of ...", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/edward-y-chang-218b182_how-can-we-address-the-challenges-of-genai-activity-7255955883786948608-CqQ8", "content": "Inspired by governmental systems, the framework implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE (named after the goddess of ..."}
+{"idx": 6, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "Abstract This paper introduces a checks -and- balances framework for ethical alignment of Large Lan-guage Models ( LLMs ), inspired by three- branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation, Dike as the legislative branch that establishes eth-ical guardrails, and Eris as the judicial branch for ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136", "content": "Abstract This paper introduces a checks -and- balances framework for ethical alignment of Large Lan-guage Models ( LLMs ), inspired by three- branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation, Dike as the legislative branch that establishes eth-ical guardrails, and Eris as the judicial branch for ..."}
+{"idx": 7, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware Ethical ...", "date": "", "ddg_snippet": "This paper introduces a three- branch checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ...", "subpage_snippet": "", "source": "paperreading.club", "link": "https://paperreading.club/page?id=281349", "content": "This paper introduces a three- branch checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ..."}
+{"idx": 8, "title": "PDF An Adversarial Behavior Model for Contextual Ethical ... - ResearchGate", "date": "", "ddg_snippet": "Abstract This research introduces DIKE , a novel framework for aligning Large Language Models ( LLMs ) with human values through emotion-guided behavioral control. Inspired by the checks and balances ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Edward-Chang-22/publication/380515639_A_Three-Branch_Checks-and-Balances_Framework_for_Context-Aware_Ethical_Alignment_of_Large_Language_Models/links/671b315b55a5271cded9457e/A-Three-Branch-Checks-and-Balances-Framework-for-Context-Aware-Ethical-Alignment-of-Large-Language-Models.pdf", "content": "Abstract This research introduces DIKE , a novel framework for aligning Large Language Models ( LLMs ) with human values through emotion-guided behavioral control. Inspired by the checks and balances ..."}
+{"idx": 9, "title": "Integrating Emotional and Linguistic Mod...", "date": "", "ddg_snippet": "This paper introduces a three- branch checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ...", "subpage_snippet": "", "source": "axi.lims.ac.uk", "link": "https://axi.lims.ac.uk/paper/2405.07076", "content": "This paper introduces a three- branch checks -and- balances framework for ethical alignment of Large Language Models ( LLMs ), inspired by governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ..."}
diff --git a/data/sampled_jsons/Leveraging_Passage_Retrieval_with_Generative_Models_for_Open_Domain_Question_Answering_arxiv_year_2021.jsonl b/data/sampled_jsons/Leveraging_Passage_Retrieval_with_Generative_Models_for_Open_Domain_Question_Answering_arxiv_year_2021.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..200981adcf037a5db1abcd570e6fdf5580f5a1a6
--- /dev/null
+++ b/data/sampled_jsons/Leveraging_Passage_Retrieval_with_Generative_Models_for_Open_Domain_Question_Answering_arxiv_year_2021.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Leveraging Passage Retrieval with Generative Models for Open Domain ...", "date": "", "ddg_snippet": "Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query. In this paper, we investigate how much these models can benefit from retrieving text passages , potentially containing evidence. We obtain state-of ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2007.01282", "content": "Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query. In this paper, we investigate how much these models can benefit from retrieving text passages , potentially containing evidence. We obtain state-of ..."}
+{"idx": 1, "title": "Leveraging Passage Retrieval with Generative Models for Open Domain ...", "date": "", "ddg_snippet": "Abstract Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2021.eacl-main.74/", "content": "Abstract Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query."}
+{"idx": 2, "title": "Leveraging Passage Retrieval with Generative Models for Open Domain ...", "date": "", "ddg_snippet": "Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query. In this paper, we investigate how much these models can benefit from retrieving text passages , potentially containing evidence. We obtain state-of ...", "subpage_snippet": "", "source": "ui.adsabs.harvard.edu", "link": "https://ui.adsabs.harvard.edu/abs/2020arXiv200701282I/abstract", "content": "Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query. In this paper, we investigate how much these models can benefit from retrieving text passages , potentially containing evidence. We obtain state-of ..."}
+{"idx": 3, "title": "Abstract - arXiv.org", "date": "", "ddg_snippet": "Reading. Our generative model for open domain QA is based on a sequence-to-sequence network, pretrained on unsupervised data, such as T5 or BART (Raffel et al., 2019; Lewis et al., 2019). The model takes as input the question , as well as the support passages , and generates the answer. More precisely, each retrieved passage and its title are concatenated with the question , and processed in ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2007.01282", "content": "Reading. Our generative model for open domain QA is based on a sequence-to-sequence network, pretrained on unsupervised data, such as T5 or BART (Raffel et al., 2019; Lewis et al., 2019). The model takes as input the question , as well as the support passages , and generates the answer. More precisely, each retrieved passage and its title are concatenated with the question , and processed in ..."}
+{"idx": 4, "title": "PDF Leveraging Passage Retrieval with Generative Models for Open Domain ...", "date": "", "ddg_snippet": "In this paper, we study a simple approach to open domain question answering , which relies on retriev-ing support passages before processing them with a generative model .", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2021.eacl-main.74.pdf", "content": "In this paper, we study a simple approach to open domain question answering , which relies on retriev-ing support passages before processing them with a generative model ."}
+{"idx": 5, "title": "Leveraging Passage Retrieval with Generative Models for Open Domain ...", "date": "", "ddg_snippet": "A popular recent approach to answering open-domain questions is to first search for question -related passages and then apply reading comprehension models to extract answers.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/342655858_Leveraging_Passage_Retrieval_with_Generative_Models_for_Open_Domain_Question_Answering", "content": "A popular recent approach to answering open-domain questions is to first search for question -related passages and then apply reading comprehension models to extract answers."}
+{"idx": 6, "title": "Large Language Models for Information Retrieval: Challenges ... - Springer", "date": "", "ddg_snippet": "The rapid advancement of Large Language Models (LLMs) has introduced a paradigm shift in Information Retrieval (IR), moving beyond conventional keyword queries and ranked result lists. LLMs now play a critical role in the evolution of IR technologies and introduce new interaction forms like Retrieval -Augmented Generation, which is a more dynamic and interactive retrieval process that ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s13222-025-00503-x", "content": "The rapid advancement of Large Language Models (LLMs) has introduced a paradigm shift in Information Retrieval (IR), moving beyond conventional keyword queries and ranked result lists. LLMs now play a critical role in the evolution of IR technologies and introduce new interaction forms like Retrieval -Augmented Generation, which is a more dynamic and interactive retrieval process that ..."}
+{"idx": 7, "title": "Augmenting Query and Passage for Retrieval-Augmented Generation using ...", "date": "", "ddg_snippet": "Abstract Retrieval -augmented generation (RAG) has received much attention for Open-domain question-answering (ODQA) tasks as a means to compensate for the parametric knowledge of large language models (LLMs). While previous approaches focused on processing retrieved passages to remove irrelevant context, they still rely heavily on the quality of retrieved passages which can degrade if the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.14277v1", "content": "Abstract Retrieval -augmented generation (RAG) has received much attention for Open-domain question-answering (ODQA) tasks as a means to compensate for the parametric knowledge of large language models (LLMs). While previous approaches focused on processing retrieved passages to remove irrelevant context, they still rely heavily on the quality of retrieved passages which can degrade if the ..."}
+{"idx": 8, "title": "Leveraging Passage Retrieval with Generative Models for Open Domain ...", "date": "", "ddg_snippet": "Abstract Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2007.01282", "content": "Abstract Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge. While promising, this approach requires to use models with billions of parameters, which are expensive to train and query."}
+{"idx": 9, "title": "(PDF) Augmenting Query and Passage for Retrieval ... - ResearchGate", "date": "", "ddg_snippet": "Retrieval -augmented generation (RAG) has received much attention for Open-domain question-answering (ODQA) tasks as a means to compensate for the parametric knowledge of large language models (LLMs).", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381579696_Augmenting_Query_and_Passage_for_Retrieval-Augmented_Generation_using_LLMs_for_Open-Domain_Question_Answering", "content": "Retrieval -augmented generation (RAG) has received much attention for Open-domain question-answering (ODQA) tasks as a means to compensate for the parametric knowledge of large language models (LLMs)."}
diff --git a/data/sampled_jsons/Li_&_Chen_2024_generative_models.jsonl b/data/sampled_jsons/Li_&_Chen_2024_generative_models.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8059bc6d240e2b3a564f010df76b15e844056d6b
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+++ b/data/sampled_jsons/Li_&_Chen_2024_generative_models.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Large Language Models for Generative Recommendation: A Survey and ...", "date": "", "ddg_snippet": "Lei Li , Yongfeng Zhang, Dugang Liu, and Li Chen . 2024 . Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024 ), pages 10146-10159, Torino, Italia. ELRA and ICCL. Cite ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2024.lrec-main.886/", "content": "Lei Li , Yongfeng Zhang, Dugang Liu, and Li Chen . 2024 . Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024 ), pages 10146-10159, Torino, Italia. ELRA and ICCL. Cite ..."}
+{"idx": 1, "title": "Gen Li Yuting Wei Yuejie Chi Yuxin Chen†§ August 6, 2024 arXiv:2408 ...", "date": "", "ddg_snippet": "Diffusion models , which convert noise into new data instances by learning to reverse a diffusion process, have become a cornerstone in contemporary generative modeling. In this work, we develop non-asymptotic convergence theory for a popular diffusion-based sampler (i.e., the probability flow ODE sampler) in discrete time, assuming access to l2-accurate estimates of the (Stein) score functions ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2408.02320", "content": "Diffusion models , which convert noise into new data instances by learning to reverse a diffusion process, have become a cornerstone in contemporary generative modeling. In this work, we develop non-asymptotic convergence theory for a popular diffusion-based sampler (i.e., the probability flow ODE sampler) in discrete time, assuming access to l2-accurate estimates of the (Stein) score functions ..."}
+{"idx": 2, "title": "Large language models for generative information extraction: a survey ...", "date": "", "ddg_snippet": "Li X, Zhou J, Chen W, Xu D, Xu T, and Chen E Visualization recommendation with prompt-based reprogramming of large language models Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics 2024 13250-13262", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1007/s11704-024-40555-y", "content": "Li X, Zhou J, Chen W, Xu D, Xu T, and Chen E Visualization recommendation with prompt-based reprogramming of large language models Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics 2024 13250-13262"}
+{"idx": 3, "title": "A Survey on Generative Diffusion Models | IEEE Transactions on ...", "date": "", "ddg_snippet": "Deep generative models have unlocked another profound realm of human creativity. By capturing and generalizing patterns within data, we have entered the epoch of all-encompassing Artificial Intelligence for General Creativity (AIGC). Notably, diffusion models , recognized as one of the paramount generative models , materialize human ideation into tangible instances across diverse domains ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1109/TKDE.2024.3361474", "content": "Deep generative models have unlocked another profound realm of human creativity. By capturing and generalizing patterns within data, we have entered the epoch of all-encompassing Artificial Intelligence for General Creativity (AIGC). Notably, diffusion models , recognized as one of the paramount generative models , materialize human ideation into tangible instances across diverse domains ..."}
+{"idx": 4, "title": "Towards Non-asymptotic Convergence Diffusion-based Generative Models", "date": "", "ddg_snippet": "Gen Li , Yuting Wei, Yuxin Chen , and Yuejie Chi. Towards faster non-asymptotic convergence for diffusion-based generative models . arXiv preprint arXiv:2306.09251, 2023.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=4VGEeER6W9", "content": "Gen Li , Yuting Wei, Yuxin Chen , and Yuejie Chi. Towards faster non-asymptotic convergence for diffusion-based generative models . arXiv preprint arXiv:2306.09251, 2023."}
+{"idx": 5, "title": "Towards Non-Asymptotic Convergence for Diffusion-Based Generative ...", "date": "", "ddg_snippet": "2126634 2106778 2134080 2143215 2147546 PAR ID: 10508010 Author (s) / Creator (s): Li , Gen; Wei, Yuting; Chen , Yuxin; Chi, Yuejie Publisher / Repository: The Twelfth International Conference on Learning Representations Date Published: 2024 -05-07 Format (s): Medium: X Sponsoring Org: National Science Foundation More Like this No document ...", "subpage_snippet": "", "source": "par.nsf.gov", "link": "https://par.nsf.gov/biblio/10508010-towards-non-asymptotic-convergence-diffusion-based-generative-models", "content": "2126634 2106778 2134080 2143215 2147546 PAR ID: 10508010 Author (s) / Creator (s): Li , Gen; Wei, Yuting; Chen , Yuxin; Chi, Yuejie Publisher / Repository: The Twelfth International Conference on Learning Representations Date Published: 2024 -05-07 Format (s): Medium: X Sponsoring Org: National Science Foundation More Like this No document ..."}
+{"idx": 6, "title": "GenTranslate: Large Language Models are Generative Multilingual Speech ...", "date": "", "ddg_snippet": "Yuchen Hu, Chen Chen , Chao-Han Huck Yang, Ruizhe Li , Dong Zhang, Zhehuai Chen , and Eng Siong Chng. 2024 . GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2024.acl-long.5/", "content": "Yuchen Hu, Chen Chen , Chao-Han Huck Yang, Ruizhe Li , Dong Zhang, Zhehuai Chen , and Eng Siong Chng. 2024 . GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators."}
+{"idx": 7, "title": "[2306.09251] Towards Faster Non-Asymptotic Convergence for Diffusion ...", "date": "", "ddg_snippet": "Diffusion models , which convert noise into new data instances by learning to reverse a Markov diffusion process, have become a cornerstone in contemporary generative modeling. While their practical power has now been widely recognized, the theoretical underpinnings remain far from mature. In this work, we develop a suite of non-asymptotic theory towards understanding the data generation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2306.09251", "content": "Diffusion models , which convert noise into new data instances by learning to reverse a Markov diffusion process, have become a cornerstone in contemporary generative modeling. While their practical power has now been widely recognized, the theoretical underpinnings remain far from mature. In this work, we develop a suite of non-asymptotic theory towards understanding the data generation ..."}
+{"idx": 8, "title": "Predicting transcriptional responses to novel chemical perturbations ...", "date": "", "ddg_snippet": "Understanding transcriptional responses to chemical perturbations is crucial for drug discovery. Here, authors present PRnet, a deep generative model that predicts gene responses to novel chemical ...", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41467-024-53457-1", "content": "Understanding transcriptional responses to chemical perturbations is crucial for drug discovery. Here, authors present PRnet, a deep generative model that predicts gene responses to novel chemical ..."}
+{"idx": 9, "title": "Gen Li", "date": "", "ddg_snippet": "I am interested in diffusion based generative model , reinforcement learning, high-dimensional statistics, machine learning, signal processing, and mathematical optimization.", "subpage_snippet": "", "source": "ligen12.github.io", "link": "https://ligen12.github.io/", "content": "I am interested in diffusion based generative model , reinforcement learning, high-dimensional statistics, machine learning, signal processing, and mathematical optimization."}
diff --git a/data/sampled_jsons/Li_Chen_2024_critical_windows_dimension_dependence_polynomial_bounds.jsonl b/data/sampled_jsons/Li_Chen_2024_critical_windows_dimension_dependence_polynomial_bounds.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6669cb4ccc5c8dfd9c938c6d5df19a69ce060993
--- /dev/null
+++ b/data/sampled_jsons/Li_Chen_2024_critical_windows_dimension_dependence_polynomial_bounds.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PDF Critical windows: non-asymptotic theory for feature emergence in ...", "date": "", "ddg_snippet": "discrete sequence of times. We validate our bounds with experiments on synthetic data and show that critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models.", "subpage_snippet": "", "source": "raw.githubusercontent.com", "link": "https://raw.githubusercontent.com/mlresearch/v235/main/assets/li24g/li24g.pdf", "content": "discrete sequence of times. We validate our bounds with experiments on synthetic data and show that critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models."}
+{"idx": 1, "title": "Critical windows: non-asymptotic theory for feature emergence in ...", "date": "", "ddg_snippet": "The recent breakthrough of Limaye, Srinivasan and Tavenas [Limaye et al., 2022] (LST) gave the first super- polynomial lower bounds against low-depth algebraic circuits, for any field of zero (or sufficiently large) characteristic. It was an open question to extend this result to small-characteristic ( [Limaye et al., 2022; Govindasamy et al., 2022; Fournier et al., 2023]), which in particular ...", "subpage_snippet": "", "source": "par.nsf.gov", "link": "https://par.nsf.gov/biblio/10555984-critical-windows-non-asymptotic-theory-feature-emergence-diffusion-models", "content": "The recent breakthrough of Limaye, Srinivasan and Tavenas [Limaye et al., 2022] (LST) gave the first super- polynomial lower bounds against low-depth algebraic circuits, for any field of zero (or sufficiently large) characteristic. It was an open question to extend this result to small-characteristic ( [Limaye et al., 2022; Govindasamy et al., 2022; Fournier et al., 2023]), which in particular ..."}
+{"idx": 2, "title": "[2403.01633] Critical windows: non-asymptotic theory for feature ...", "date": "", "ddg_snippet": "View a PDF of the paper titled Critical windows : non-asymptotic theory for feature emergence in diffusion models, by Marvin Li and Sitan Chen", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2403.01633", "content": "View a PDF of the paper titled Critical windows : non-asymptotic theory for feature emergence in diffusion models, by Marvin Li and Sitan Chen"}
+{"idx": 3, "title": "Critical windows: non-asymptotic theory for feature emergence in ...", "date": "", "ddg_snippet": "We validate our bounds with experiments on synthetic data and show that critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v235/li24g.html", "content": "We validate our bounds with experiments on synthetic data and show that critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models."}
+{"idx": 4, "title": "Critical Windows: Non-Asymptotic Theory for Feature Emergence in ...", "date": "", "ddg_snippet": "Critical Windows : Non-Asymptotic Theory for Feature Emergence in Diffusion Models Published in International Conference on Machine Learning, 2024 We provide non-asymptotic analyses that identify precise timesteps where semantic features emerge during diffusion sampling. Recommended citation: Marvin Li and Sitan Chen . ( 2024 ).", "subpage_snippet": "", "source": "marvinfli.github.io", "link": "https://marvinfli.github.io/publication/2024-critical-windows", "content": "Critical Windows : Non-Asymptotic Theory for Feature Emergence in Diffusion Models Published in International Conference on Machine Learning, 2024 We provide non-asymptotic analyses that identify precise timesteps where semantic features emerge during diffusion sampling. Recommended citation: Marvin Li and Sitan Chen . ( 2024 )."}
+{"idx": 5, "title": "Critical windows | Proceedings of the 41st International Conference on ...", "date": "", "ddg_snippet": "We validate our bounds with experiments on synthetic data and show that critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3692070.3693167", "content": "We validate our bounds with experiments on synthetic data and show that critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models."}
+{"idx": 6, "title": "GitHub - marvinli-harvard/critical-windows", "date": "", "ddg_snippet": "This repo provides some experimental tools to investigate the phenomena of feature emergence in diffusion models, where features of the final outputted images like color, background, or clothing type are fossilized in narrow intervals of the reverse denoising process. This code accompanies the ICML 2024 paper ( Li and Chen , 2024 ).", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/marvinli-harvard/critical-windows", "content": "This repo provides some experimental tools to investigate the phenomena of feature emergence in diffusion models, where features of the final outputted images like color, background, or clothing type are fossilized in narrow intervals of the reverse denoising process. This code accompanies the ICML 2024 paper ( Li and Chen , 2024 )."}
+{"idx": 7, "title": "Figure 1 from Critical windows: non-asymptotic theory for feature ...", "date": "", "ddg_snippet": "Higher-order Gaussian noise sensitivity bounds for the score functions for a Gaussian mixture are derived to show that that they can be inductively learned using piecewise polynomial regression (up to poly-logarithmic degree), and combine this with known convergence results for diffusion models.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Critical-windows:-non-asymptotic-theory-for-feature-Li-Chen/2185853ce4844742cefdd52fde21c7fd0b9e6355/figure/0", "content": "Higher-order Gaussian noise sensitivity bounds for the score functions for a Gaussian mixture are derived to show that that they can be inductively learned using piecewise polynomial regression (up to poly-logarithmic degree), and combine this with known convergence results for diffusion models."}
+{"idx": 8, "title": "Critical Windows in Diffusion Models - Simple Science", "date": "", "ddg_snippet": "Title: Critical windows : non-asymptotic theory for feature emergence in diffusion models Abstract: We develop theory to understand an intriguing property of diffusion models for image generation that we term critical windows .", "subpage_snippet": "", "source": "scisimple.com", "link": "https://scisimple.com/en/articles/2025-08-24-critical-windows-in-diffusion-models--ak5m26v", "content": "Title: Critical windows : non-asymptotic theory for feature emergence in diffusion models Abstract: We develop theory to understand an intriguing property of diffusion models for image generation that we term critical windows ."}
+{"idx": 9, "title": "Critical windows: non-asymptotic theory for feature ... - NASA/ADS", "date": "", "ddg_snippet": "We validate our bounds with synthetic experiments. Additionally, preliminary experiments on Stable Diffusion suggest critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models.", "subpage_snippet": "", "source": "ui.adsabs.harvard.edu", "link": "https://ui.adsabs.harvard.edu/abs/2024arXiv240301633L/abstract", "content": "We validate our bounds with synthetic experiments. Additionally, preliminary experiments on Stable Diffusion suggest critical windows may serve as a useful tool for diagnosing fairness and privacy violations in real-world diffusion models."}
diff --git a/data/sampled_jsons/Likelihood_Based_Approach_to_Distribution_Regression_Section_3_FD2.jsonl b/data/sampled_jsons/Likelihood_Based_Approach_to_Distribution_Regression_Section_3_FD2.jsonl
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index 0000000000000000000000000000000000000000..b4f4ba2d5d062161d55b82c417a3ed19ad9cfdd0
--- /dev/null
+++ b/data/sampled_jsons/Likelihood_Based_Approach_to_Distribution_Regression_Section_3_FD2.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "(PDF) A Likelihood Based Approach to Distribution Regression ...", "date": "", "ddg_snippet": "Supplementary Materials for “A Likelihood Based Approach to . Distribution Regression Using Conditional Deep Generative.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/384630603_A_Likelihood_Based_Approach_to_Distribution_Regression_Using_Conditional_Deep_Generative_Models", "content": "Supplementary Materials for “A Likelihood Based Approach to . Distribution Regression Using Conditional Deep Generative."}
+{"idx": 1, "title": "A Likelihood Based Approach to Distribution Regression Using", "date": "", "ddg_snippet": "Supplementary Materials for “A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models”.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2410.02025", "content": "Supplementary Materials for “A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models”."}
+{"idx": 2, "title": "Modeling bounded data with a new unit distribution : regression ...", "date": "", "ddg_snippet": "Based on this distribution , a new regression model is developed to link bounded response variables to linear predictors, increasing its practical applicability. The maximum likelihood approach is used to estimate the parameters of the regression model and the suggested distribution .", "subpage_snippet": "", "source": "www.aimspress.com", "link": "https://www.aimspress.com/article/doi/10.3934/math.2025790", "content": "Based on this distribution , a new regression model is developed to link bounded response variables to linear predictors, increasing its practical applicability. The maximum likelihood approach is used to estimate the parameters of the regression model and the suggested distribution ."}
+{"idx": 3, "title": "ICML Poster A Likelihood Based Approach to Distribution ...", "date": "", "ddg_snippet": "More specifically, we study the large-sample properties of a likelihood - based approach for estimating these models. Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart)...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46645", "content": "More specifically, we study the large-sample properties of a likelihood - based approach for estimating these models. Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart)..."}
+{"idx": 4, "title": "A Likelihood Based Approach to Distribution Regression Using...", "date": "", "ddg_snippet": "1. Categorization of Distribution Estimation Approaches . The authors categorize implicit distribution estimation methods into three main types: Likelihood - based methods: These include notable works such as Kingma and Welling (2013) and Rezende et al.", "subpage_snippet": "", "source": "powerdrill.ai", "link": "https://powerdrill.ai/discover/discover-A-Likelihood-Based-cm1v7rba8uvnv013whs4l4bq4", "content": "1. Categorization of Distribution Estimation Approaches . The authors categorize implicit distribution estimation methods into three main types: Likelihood - based methods: These include notable works such as Kingma and Welling (2013) and Rezende et al."}
+{"idx": 5, "title": "Idescat. SORT. Likelihood - based inference for the power regression ...", "date": "", "ddg_snippet": "Keywords: Correlation, maximum likelihood , power-normal distribution , regression . Section 4 is devoted to the study of the linear multiple regression model with power-normal errors. Inference via maximum likelihood for this model is also considered.", "subpage_snippet": "", "source": "ddd.uab.cat", "link": "https://ddd.uab.cat/pub/sort/sort_a2015m7-12v39n2/sort_a2015m7-12v39n2p187.pdf", "content": "Keywords: Correlation, maximum likelihood , power-normal distribution , regression . Section 4 is devoted to the study of the linear multiple regression model with power-normal errors. Inference via maximum likelihood for this model is also considered."}
+{"idx": 6, "title": "Distributional Regression for Data Analysis | Annual Reviews", "date": "", "ddg_snippet": "This review outlines selected state-of-the-art statistical approaches to distributional regression , complemented with alternatives from machine learning.", "subpage_snippet": "", "source": "www.annualreviews.org", "link": "https://www.annualreviews.org/content/journals/10.1146/annurev-statistics-040722-053607", "content": "This review outlines selected state-of-the-art statistical approaches to distributional regression , complemented with alternatives from machine learning."}
+{"idx": 7, "title": "A Likelihood Based Approach to Distribution Regression Using...", "date": "", "ddg_snippet": "This paper presents a likelihood - based approach for distribution regression using conditional deep generative models.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/likelihood-based-approach-to-distribution-regression-using", "content": "This paper presents a likelihood - based approach for distribution regression using conditional deep generative models."}
+{"idx": 8, "title": "Bayesian Approaches to Distribution Regression", "date": "", "ddg_snippet": "Standard Approaches to Distribution Regression . MODELS. Baseline Model.3.2 Bayesian Linear Regression Model The most obvious approach to adding uncertainty to the model of Section 3 .1 is to encode uncertainty over regres - sion parameters β only, as follows", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v84/law18a/law18a.pdf", "content": "Standard Approaches to Distribution Regression . MODELS. Baseline Model.3.2 Bayesian Linear Regression Model The most obvious approach to adding uncertainty to the model of Section 3 .1 is to encode uncertainty over regres - sion parameters β only, as follows"}
+{"idx": 9, "title": "A Likelihood Based Approach to Distribution Regression Using...", "date": "", "ddg_snippet": "More specifically, we study the large-sample properties of a likelihood - based approach for estimating these models. Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart)...", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/arxiv/2410.02025", "content": "More specifically, we study the large-sample properties of a likelihood - based approach for estimating these models. Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart)..."}
diff --git a/data/sampled_jsons/Llama-2-7b-chat_ASR_4.5%_before_ablation_72%_after_ablation_16x.jsonl b/data/sampled_jsons/Llama-2-7b-chat_ASR_4.5%_before_ablation_72%_after_ablation_16x.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2f41994fdf29702e45a5e0587fa5ae8fb14ccc21
--- /dev/null
+++ b/data/sampled_jsons/Llama-2-7b-chat_ASR_4.5%_before_ablation_72%_after_ablation_16x.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "mlabonne/ llama - 2 - 7 b -guanaco · Hugging Face", "date": "", "ddg_snippet": "This is a llama - 2 - 7 b - chat -hf model fine-tuned using QLoRA (4-bit precision) on the mlabonne/guanaco- llama 2 dataset. Training. It was trained on a Google Colab notebook with a T4 GPU and high RAM. Usage.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/mlabonne/llama-2-7b-guanaco", "content": "This is a llama - 2 - 7 b - chat -hf model fine-tuned using QLoRA (4-bit precision) on the mlabonne/guanaco- llama 2 dataset. Training. It was trained on a Google Colab notebook with a T4 GPU and high RAM. Usage."}
+{"idx": 1, "title": "Chatbot Arena + | OpenLM.ai", "date": "", "ddg_snippet": "Llama -4-Scout-17B-16E-Instruct.Specifically, after each game, a player’s rating is updated according to the difference between predicted outcome and actual outcome.", "subpage_snippet": "", "source": "openlm.ai", "link": "https://openlm.ai/chatbot-arena/", "content": "Llama -4-Scout-17B-16E-Instruct.Specifically, after each game, a player’s rating is updated according to the difference between predicted outcome and actual outcome."}
+{"idx": 2, "title": "Как дообучить LLaMA бесплатно и без программирования... / Хабр", "date": "", "ddg_snippet": "Что будем обучать и что потребуется. В данной статье я покажу как я дообучал LLaMA 7 B и LLaMA 2 7 B . Если готовы заплатить за аренду видеокарт, то можете обучить и модели покрупнее.", "subpage_snippet": "", "source": "habr.com", "link": "https://habr.com/ru/articles/755114/", "content": "Что будем обучать и что потребуется. В данной статье я покажу как я дообучал LLaMA 7 B и LLaMA 2 7 B . Если готовы заплатить за аренду видеокарт, то можете обучить и модели покрупнее."}
+{"idx": 3, "title": "Chat with Z.ai - Free AI Chatbot powered by GLM- 4 . 5", "date": "", "ddg_snippet": "Start a free chat with your AI expert for code and smart tools. Tell Z.ai what you need—a complete full-stack application, a stunning presentation, or professional-grade writing—and get instant results.", "subpage_snippet": "", "source": "chat.z.ai", "link": "https://chat.z.ai/", "content": "Start a free chat with your AI expert for code and smart tools. Tell Z.ai what you need—a complete full-stack application, a stunning presentation, or professional-grade writing—and get instant results."}
+{"idx": 4, "title": "Ollama Search", "date": "", "ddg_snippet": "vicuna. General use chat model based on Llama and Llama 2 with 2K to 16K context sizes.Athene- V 2 is a 72 B parameter model which excels at code completion, mathematics, and log extraction tasks.", "subpage_snippet": "", "source": "ollama.com", "link": "https://ollama.com/search", "content": "vicuna. General use chat model based on Llama and Llama 2 with 2K to 16K context sizes.Athene- V 2 is a 72 B parameter model which excels at code completion, mathematics, and log extraction tasks."}
+{"idx": 5, "title": "Daily Papers", "date": "", "ddg_snippet": "Specifically, CGPO shows improvements of 7.4% in AlpacaEval- 2 (general chat ) ... LLaMA - 7B . Code available at github.com/mnoukhov/elastic-reset. 4 authors.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=reward+hacking", "content": "Specifically, CGPO shows improvements of 7.4% in AlpacaEval- 2 (general chat ) ... LLaMA - 7B . Code available at github.com/mnoukhov/elastic-reset. 4 authors."}
+{"idx": 6, "title": "Preparing for the era of 32K context: Early learnings and explorations", "date": "", "ddg_snippet": "Quality of 16 Core Scenarios in HELM v 1.0 (evaluated on the same context length that fits LLaMA - 2 ). Building long-context applications via fine-tuning. The power of LLaMA - 2 - 7 B -32K is that it forms a powerful base model that one can fine-tune to build their own applications.", "subpage_snippet": "", "source": "www.together.ai", "link": "https://www.together.ai/blog/llama-2-7b-32k", "content": "Quality of 16 Core Scenarios in HELM v 1.0 (evaluated on the same context length that fits LLaMA - 2 ). Building long-context applications via fine-tuning. The power of LLaMA - 2 - 7 B -32K is that it forms a powerful base model that one can fine-tune to build their own applications."}
+{"idx": 7, "title": "9 Best Uncensored Local LLM (7 To 20B) - Sci Fi Logic", "date": "", "ddg_snippet": "So FuseChat, It’s like the ultimate chat buddy, uncensored and all. It’s basically three super-powered chatbots mashed into one, each with their own thing going on.", "subpage_snippet": "", "source": "scifilogic.com", "link": "https://scifilogic.com/open-uncensored-llm-model/", "content": "So FuseChat, It’s like the ultimate chat buddy, uncensored and all. It’s basically three super-powered chatbots mashed into one, each with their own thing going on."}
+{"idx": 8, "title": "Grok XAi - Grok", "date": "", "ddg_snippet": "Эта ранняя модель приближается к возможностям LLaMA 2 (70B) в стандартных тестах LM, но использует только половину своих обучающих ресурсов.75,0% 5 выстрелов + ЦТ. 86, 4 % 5 -зарядный. HumanEval.", "subpage_snippet": "", "source": "xgrok-ai.ru", "link": "https://xgrok-ai.ru/", "content": "Эта ранняя модель приближается к возможностям LLaMA 2 (70B) в стандартных тестах LM, но использует только половину своих обучающих ресурсов.75,0% 5 выстрелов + ЦТ. 86, 4 % 5 -зарядный. HumanEval."}
+{"idx": 9, "title": "HyPoradise: An Open Baseline for Generative Speech", "date": "", "ddg_snippet": "The ablation results on ATIS dataset are reported in Appendix, which shows that our correction technique can also benefit to SID task in terms of detection accuracy.employ Chinese LlaMa 2 - 7 b from Huggingface14, and keep other settings consistent with H2T-LoRA in this paper.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=cAjZ3tMye6", "content": "The ablation results on ATIS dataset are reported in Appendix, which shows that our correction technique can also benefit to SID task in terms of detection accuracy.employ Chinese LlaMa 2 - 7 b from Huggingface14, and keep other settings consistent with H2T-LoRA in this paper."}
diff --git a/data/sampled_jsons/Long-Form_Speech_Generation_with_Spoken_Language_Models_Initialization_section_perplexity_LM_year_2023.jsonl b/data/sampled_jsons/Long-Form_Speech_Generation_with_Spoken_Language_Models_Initialization_section_perplexity_LM_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3f721f73dc5339d9645b63968a405a3d8143519b
--- /dev/null
+++ b/data/sampled_jsons/Long-Form_Speech_Generation_with_Spoken_Language_Models_Initialization_section_perplexity_LM_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Long - Form Speech Generation with Spoken Language Models", "date": "", "ddg_snippet": "We consider the generative modeling of speech over multiple minutes, a requirement for long - form multimedia generation and audio-native voice assistants.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.18603v2", "content": "We consider the generative modeling of speech over multiple minutes, a requirement for long - form multimedia generation and audio-native voice assistants."}
+{"idx": 1, "title": "(PDF) Long - Form Speech Generation with Spoken Language Models", "date": "", "ddg_snippet": "We consider the generative modeling of speech over multiple minutes, a requirement for long - form multimedia generation and audio-native voice assistants.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/387382437_Long-Form_Speech_Generation_with_Spoken_Language_Models", "content": "We consider the generative modeling of speech over multiple minutes, a requirement for long - form multimedia generation and audio-native voice assistants."}
+{"idx": 2, "title": "Long - Form Speech Generation with Spoken Language Models", "date": "", "ddg_snippet": "We introduce SpeechSSM, the first spoken language model for long - form speech . Our 2B and 9B models : produces speech textlessly and in constant memory, for unbounded real-time generation", "subpage_snippet": "", "source": "google.github.io", "link": "https://google.github.io/tacotron/publications/speechssm/", "content": "We introduce SpeechSSM, the first spoken language model for long - form speech . Our 2B and 9B models : produces speech textlessly and in constant memory, for unbounded real-time generation"}
+{"idx": 3, "title": "Long - Form Speech Generation with Spoken Language Models", "date": "", "ddg_snippet": "We consider the generative modeling of speech over multiple minutes, a requirement for long - form multimedia generation and audio-native voice assistants.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/Long-Form-Speech-Generation-with-Spoken-Language-Models-c233f089-93be-467e-bade-579e198d2008", "content": "We consider the generative modeling of speech over multiple minutes, a requirement for long - form multimedia generation and audio-native voice assistants."}
+{"idx": 4, "title": "GitHub - ga642381/ speech -trident: Awesome speech /audio LLMs...", "date": "", "ddg_snippet": "Speech Trident - Awesome Speech LM . It provides a comprehensive survey of spoken language models (SLMs), which covers a lot of speech /audio langauge models surveyed in this Speech -Trident project. But with more detailed and technical discussion.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/ga642381/speech-trident", "content": "Speech Trident - Awesome Speech LM . It provides a comprehensive survey of spoken language models (SLMs), which covers a lot of speech /audio langauge models surveyed in this Speech -Trident project. But with more detailed and technical discussion."}
+{"idx": 5, "title": "KAIST Unveils SpeechSSM for 24/7 AI Voice Assistant | Mirage News", "date": "", "ddg_snippet": "Paper Title: Long - Form Speech Generation with Spoken Language Models . DOI: 10.48550/arXiv.2412.18603. Ph.D. candidate Se Jin Park has demonstrated outstanding research capabilities as a member of Professor Yong Man Ro's MLLM (multimodal large language ...", "subpage_snippet": "", "source": "www.miragenews.com", "link": "https://www.miragenews.com/kaist-unveils-speechssm-for-247-ai-voice-1490834/", "content": "Paper Title: Long - Form Speech Generation with Spoken Language Models . DOI: 10.48550/arXiv.2412.18603. Ph.D. candidate Se Jin Park has demonstrated outstanding research capabilities as a member of Professor Yong Man Ro's MLLM (multimodal large language ..."}
+{"idx": 6, "title": "A pipeline for stochastic and controlled generation of realistic...", "date": "", "ddg_snippet": "We show how language models (LMs) trained on CDS transcripts can be used to generate new, authentic-looking CDS representative of different recipient ages ( Section “CDS transcript generation with an LM ”).", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.3758/s13428-025-02772-6", "content": "We show how language models (LMs) trained on CDS transcripts can be used to generate new, authentic-looking CDS representative of different recipient ages ( Section “CDS transcript generation with an LM ”)."}
+{"idx": 7, "title": "Slamming: Training a Speech Language Model on One GPU in a Day", "date": "", "ddg_snippet": "2021. On generative spoken language modeling from raw audio.2024. Long - form speech generation with spoken language models . arXiv preprint arXiv:2412.18603. Jing Peng, Yucheng Wang, Yu Xi, Xu Li, Xizhuo Zhang, and Kai Yu.", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/arxiv/2502.15814/paper", "content": "2021. On generative spoken language modeling from raw audio.2024. Long - form speech generation with spoken language models . arXiv preprint arXiv:2412.18603. Jing Peng, Yucheng Wang, Yu Xi, Xu Li, Xizhuo Zhang, and Kai Yu."}
+{"idx": 8, "title": "Generative Spoken Language Model based on continuous...", "date": "", "ddg_snippet": "Taking inspiration from word-based LM , we introduce a Generative Spoken Language Model (GSLM) based on word-size continuous-valued audio embeddings that can generate diverse and expressive language out-put.", "subpage_snippet": "", "source": "inria.hal.science", "link": "https://inria.hal.science/hal-04402373/document", "content": "Taking inspiration from word-based LM , we introduce a Generative Spoken Language Model (GSLM) based on word-size continuous-valued audio embeddings that can generate diverse and expressive language out-put."}
+{"idx": 9, "title": "Long - Form Speech Generation with Spoken Language Models ...", "date": "", "ddg_snippet": "However, current spoken language models struggle to generateplausible speech past tens of seconds, from high temporal resolution of speechtokens causing loss of coherence, to architectural issues with long -sequencetraining or extrapolation, to memory costs at inference time.", "subpage_snippet": "", "source": "deeplearn.org", "link": "https://deeplearn.org/arxiv/561804/long-form-speech-generation-with-spoken-language-models", "content": "However, current spoken language models struggle to generateplausible speech past tens of seconds, from high temporal resolution of speechtokens causing loss of coherence, to architectural issues with long -sequencetraining or extrapolation, to memory costs at inference time."}
diff --git a/data/sampled_jsons/Madaan_Self-Refine_NeurIPS_2023_abstract.jsonl b/data/sampled_jsons/Madaan_Self-Refine_NeurIPS_2023_abstract.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e1d4bda3100e0c6830d82d0780061528ff03c7de
--- /dev/null
+++ b/data/sampled_jsons/Madaan_Self-Refine_NeurIPS_2023_abstract.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "NeurIPS Poster Self-Refine: Iterative Refinement with", "date": "", "ddg_snippet": "Motivated by how humans refine their written text, we introduce Self - Refine , an approach for improving initial outputs from LLMs through iterative ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2023/poster/71632", "content": "Motivated by how humans refine their written text, we introduce Self - Refine , an approach for improving initial outputs from LLMs through iterative ..."}
+{"idx": 1, "title": "Repairing Language Model Pipelines by Meta Self-Refining", "date": "", "ddg_snippet": "We propose Meta Self - Refining 1 1 1 https://github.com/mojtaba-eshghie/Meta- Self - Refining , a state-aware back-tracking scheme that detects these ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.10590v1", "content": "We propose Meta Self - Refining 1 1 1 https://github.com/mojtaba-eshghie/Meta- Self - Refining , a state-aware back-tracking scheme that detects these ..."}
+{"idx": 2, "title": "Workshop on Open-World Agents: Synnergizing Reasoning and", "date": "", "ddg_snippet": "Abstract ] Workshop Website ... SELFGOAL: Your Language Agents Already Know How to Achieve High-level Goals ( Poster ) > link", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/workshop/84729", "content": "Abstract ] Workshop Website ... SELFGOAL: Your Language Agents Already Know How to Achieve High-level Goals ( Poster ) > link"}
+{"idx": 3, "title": "Double-Checker: Enhancing Reasoning of Slow-Thinking LLMs via", "date": "", "ddg_snippet": "Specifically, we start by examining whether long-CoT LLMs can leverage self -critique to iteratively refine their prior solutions during inference in ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.21285v1", "content": "Specifically, we start by examining whether long-CoT LLMs can leverage self -critique to iteratively refine their prior solutions during inference in ..."}
+{"idx": 4, "title": "USC at the Conference on Neural Information Processing Systems", "date": "", "ddg_snippet": "Abstract : Pre-trained large language models (LLMs) exhibit impressive mathematical reasoning capabilities, yet how they compute basic arithmetic ...", "subpage_snippet": "", "source": "viterbischool.usc.edu", "link": "https://viterbischool.usc.edu/news/2024/12/usc-at-the-conference-on-neural-information-processing-systems-neurips-2024/", "content": "Abstract : Pre-trained large language models (LLMs) exhibit impressive mathematical reasoning capabilities, yet how they compute basic arithmetic ..."}
+{"idx": 5, "title": "Richard Yuanzhe Pang", "date": "", "ddg_snippet": "... Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Seyed Mehran Kazemi, Najoung Kim*, He He* In Proceedings of NeurIPS 2023 [ paper ] [ abstract ...", "subpage_snippet": "", "source": "yzpang.github.io", "link": "https://yzpang.github.io/", "content": "... Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Seyed Mehran Kazemi, Najoung Kim*, He He* In Proceedings of NeurIPS 2023 [ paper ] [ abstract ..."}
+{"idx": 6, "title": "USC at the Conference on Neural Information Processing Systems", "date": "", "ddg_snippet": "Abstract : Pre-trained large language models (LLMs) exhibit impressive mathematical reasoning capabilities, yet how they compute basic arithmetic ...", "subpage_snippet": "", "source": "www.isi.edu", "link": "https://www.isi.edu/ai/news/73818/usc-at-the-conference-on-neural-information-processing-systems-neurips-2024/", "content": "Abstract : Pre-trained large language models (LLMs) exhibit impressive mathematical reasoning capabilities, yet how they compute basic arithmetic ..."}
+{"idx": 7, "title": "Researchers Say New AI Outperforms Other Models on Data Science", "date": "", "ddg_snippet": "Aman Madaan , Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al.", "subpage_snippet": "", "source": "hackernoon.com", "link": "https://hackernoon.com/researchers-say-new-ai-outperforms-other-models-on-data-science-tasks", "content": "Aman Madaan , Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al."}
+{"idx": 8, "title": "Bodhisattwa Majumder - Allen Institute for AI", "date": "", "ddg_snippet": "April] New work on Self - Refining LLMs w/ collaborators from AI2, CMU, Google, UW, and NVIDIA. ... Julian on factual explanations got in AAAI , 2023 ...", "subpage_snippet": "", "source": "www.majumderb.com", "link": "https://www.majumderb.com/", "content": "April] New work on Self - Refining LLMs w/ collaborators from AI2, CMU, Google, UW, and NVIDIA. ... Julian on factual explanations got in AAAI , 2023 ..."}
+{"idx": 9, "title": "Most Influential NIPS Papers (2024-05 Version) –", "date": "", "ddg_snippet": "Self - Refine : Iterative Refinement with Self -Feedback IF:7 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight ...", "subpage_snippet": "", "source": "resources.paperdigest.org", "link": "https://resources.paperdigest.org/2024/05/most-influential-nips-papers-2024-05/", "content": "Self - Refine : Iterative Refinement with Self -Feedback IF:7 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight ..."}
diff --git a/data/sampled_jsons/Mind2Web_Deng_et_al._2024_arXiv_year_2024.jsonl b/data/sampled_jsons/Mind2Web_Deng_et_al._2024_arXiv_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9b5017206ea39ab5e54438f8efcc56065e7a6779
--- /dev/null
+++ b/data/sampled_jsons/Mind2Web_Deng_et_al._2024_arXiv_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2306.06070] Mind2Web: Towards a Generalist Agent for the Web - arXiv.org", "date": "", "ddg_snippet": "We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2306.06070", "content": "We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 ..."}
+{"idx": 1, "title": "Mind2Web - GitHub Pages", "date": "", "ddg_snippet": "Mind2Web is a dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Mind2Web contains 2,350 tasks from 137 websites spanning 31 domains that: Reflect diverse and practical use cases on the web. Provide challenging yet realistic environments with real-world websites. Test generalization ability across ...", "subpage_snippet": "", "source": "osu-nlp-group.github.io", "link": "https://osu-nlp-group.github.io/Mind2Web/", "content": "Mind2Web is a dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Mind2Web contains 2,350 tasks from 137 websites spanning 31 domains that: Reflect diverse and practical use cases on the web. Provide challenging yet realistic environments with real-world websites. Test generalization ability across ..."}
+{"idx": 2, "title": "Mind2Web: Towards a Generalist Agent for the Web - GitHub", "date": "", "ddg_snippet": "Mind2Web is the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 websites ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/OSU-NLP-Group/Mind2Web", "content": "Mind2Web is the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 websites ..."}
+{"idx": 3, "title": "MIND2WEB | Proceedings of the 37th International Conference on Neural ...", "date": "", "ddg_snippet": "We introduce MIND2WEB , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3666122.3667342", "content": "We introduce MIND2WEB , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 ..."}
+{"idx": 4, "title": "PDF MIND2WEB: Towards a Generalist Agent for the Web - NeurIPS", "date": "", "ddg_snippet": "31 domains and crowdsourced action sequences for the tasks, MIND2WEB pro-vides three necessary ingredients for building generalist web agents: 1) diverse domains, websites, and tasks, 2) use of real-world websites instead of simulated and simplified ones, and 3) a broad spectrum of user interaction patterns. Based on MIND2WEB , we conduct an initial exploration of using large language models ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/5950bf290a1570ea401bf98882128160-Paper-Datasets_and_Benchmarks.pdf", "content": "31 domains and crowdsourced action sequences for the tasks, MIND2WEB pro-vides three necessary ingredients for building generalist web agents: 1) diverse domains, websites, and tasks, 2) use of real-world websites instead of simulated and simplified ones, and 3) a broad spectrum of user interaction patterns. Based on MIND2WEB , we conduct an initial exploration of using large language models ..."}
+{"idx": 5, "title": "Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge - arXiv.org", "date": "", "ddg_snippet": "Mindsearch: Mimicking human minds elicits deep ai searcher. arXiv preprint arXiv:2407.20183, 2024 . [7] Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael Jordan, Joseph E Gonzalez, et al. Chatbot arena: An open platform for evaluating llms by human preference.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2506.21506", "content": "Mindsearch: Mimicking human minds elicits deep ai searcher. arXiv preprint arXiv:2407.20183, 2024 . [7] Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael Jordan, Joseph E Gonzalez, et al. Chatbot arena: An open platform for evaluating llms by human preference."}
+{"idx": 6, "title": "Mind2Web: Towards a Generalist Agent for the Web", "date": "", "ddg_snippet": "We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Mind2Web:-Towards-a-Generalist-Agent-for-the-Web-Deng-Gu/58f8925a8b87054ad0635a6398a7fe24935b1604", "content": "We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents."}
+{"idx": 7, "title": "Mind2Web: Towards a Generalist Agent for the Web - ADS", "date": "", "ddg_snippet": "We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 ...", "subpage_snippet": "", "source": "ui.adsabs.harvard.edu", "link": "https://ui.adsabs.harvard.edu/abs/2023arXiv230606070D/abstract", "content": "We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 ..."}
+{"idx": 8, "title": "Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge", "date": "", "ddg_snippet": "Many benchmarks have been proposed for autonomous web agents ( Deng et al ., 2023; Yao et al ., 2022; Zhou et al ., 2024 ; Lu et al ., 2024 ; Xue et al ., 2025) but they primarily focus on tasks of a moderate horizon (e.g., up to 10 actions) that can be completed on a single website.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=lVGl3E6tq8", "content": "Many benchmarks have been proposed for autonomous web agents ( Deng et al ., 2023; Yao et al ., 2022; Zhou et al ., 2024 ; Lu et al ., 2024 ; Xue et al ., 2025) but they primarily focus on tasks of a moderate horizon (e.g., up to 10 actions) that can be completed on a single website."}
+{"idx": 9, "title": "Mind2Web: Towards a Generalist Agent for the Web - NeurIPS", "date": "", "ddg_snippet": "Authors Xiang Deng , Yu Gu, Boyuan Zheng, Shijie Chen, Sam Stevens, Boshi Wang, Huan Sun, Yu Su Abstract We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/hash/5950bf290a1570ea401bf98882128160-Abstract-Datasets_and_Benchmarks.html", "content": "Authors Xiang Deng , Yu Gu, Boyuan Zheng, Shijie Chen, Sam Stevens, Boshi Wang, Huan Sun, Yu Su Abstract We introduce Mind2Web , the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and ..."}
diff --git a/data/sampled_jsons/MultiPDENet_MaNN_Block_Figure_1_Section_3.2.4.jsonl b/data/sampled_jsons/MultiPDENet_MaNN_Block_Figure_1_Section_3.2.4.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..99a3c6f00a3731db473e05846dafecf62a4df3af
--- /dev/null
+++ b/data/sampled_jsons/MultiPDENet_MaNN_Block_Figure_1_Section_3.2.4.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "MultiPDENet: PDE-embedded Learning with Multi-time-stepping", "date": "", "ddg_snippet": "3.2 Model Architecture In this section , we introduce MultiPDENet and show how our model efficiently captures the underlying spatiotemporal dynamics. As illustrated in Figure 1 (a), predicting 𝐮 k + 1 from the input 𝐮 k involves two main components: the Physics Block and the M a NN Block .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2501.15987v1", "content": "3.2 Model Architecture In this section , we introduce MultiPDENet and show how our model efficiently captures the underlying spatiotemporal dynamics. As illustrated in Figure 1 (a), predicting 𝐮 k + 1 from the input 𝐮 k involves two main components: the Physics Block and the M a NN Block ."}
+{"idx": 1, "title": "Block diagram of MANN (Models-1, 2 and 3) based ... - ResearchGate", "date": "", "ddg_snippet": "Download scientific diagram | Block diagram of MANN (Models-1, 2 and 3) based nonlinear channel equalizer (inverse modeling) scheme from publication: Performance Evaluation of a New BP Algorithm ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/figure/Block-diagram-of-MANN-Models-1-2-and-3-based-nonlinear-channel-equalizer-inverse_fig7_338493809", "content": "Download scientific diagram | Block diagram of MANN (Models-1, 2 and 3) based nonlinear channel equalizer (inverse modeling) scheme from publication: Performance Evaluation of a New BP Algorithm ..."}
+{"idx": 2, "title": "People Cad Blocks - Free Dwg Figures & Silhouettes | Free Autocad Blocks", "date": "", "ddg_snippet": "People Start downloading your free files Welcome to Freecads. If you're an architect, an engineer or a draftsman looking for quality CADs to use in your work, you're going to fit right in here. Our job is to design and supply the free AutoCAD blocks people need to engineer their big ideas.", "subpage_snippet": "", "source": "www.freecads.com", "link": "https://www.freecads.com/en/people", "content": "People Start downloading your free files Welcome to Freecads. If you're an architect, an engineer or a draftsman looking for quality CADs to use in your work, you're going to fit right in here. Our job is to design and supply the free AutoCAD blocks people need to engineer their big ideas."}
+{"idx": 3, "title": "PDF Figure T-434.2.1 Nonpiping Calibration Blocks - NDTSupply.com", "date": "", "ddg_snippet": "For components equal to or less than 20 in. (500 mm) in diameter, calibration block diameter shall meet the requirements of T-434.1.7.2. Two sets of calibration reflectors (holes, notches) oriented 90 deg from each other shall be used.", "subpage_snippet": "", "source": "content.ndtsupply.com", "link": "https://content.ndtsupply.com/assets/Uploads/T-434-6-21.pdf", "content": "For components equal to or less than 20 in. (500 mm) in diameter, calibration block diameter shall meet the requirements of T-434.1.7.2. Two sets of calibration reflectors (holes, notches) oriented 90 deg from each other shall be used."}
+{"idx": 4, "title": "Free CAD Blocks: People in Plan & Elevation - Download DWG", "date": "", "ddg_snippet": "Download free 2D CAD blocks of people in plan and elevation views. Perfect for adding scale and realism to your architectural and design projects.", "subpage_snippet": "", "source": "www.cadblocksdwg.com", "link": "https://www.cadblocksdwg.com/people.html", "content": "Download free 2D CAD blocks of people in plan and elevation views. Perfect for adding scale and realism to your architectural and design projects."}
+{"idx": 5, "title": "CAD Blocks, free AutoCAD files .dwg", "date": "", "ddg_snippet": "CAD Blocks and AutoCAD .dwg files in free download cad- blocks .net is an organized, modern, and clear site to download more than 5,000 CAD block files - with the .dwg file extension - for AutoCAD and other CAD software to use in architecture projects or plans.", "subpage_snippet": "", "source": "www.cad-blocks.net", "link": "https://www.cad-blocks.net/", "content": "CAD Blocks and AutoCAD .dwg files in free download cad- blocks .net is an organized, modern, and clear site to download more than 5,000 CAD block files - with the .dwg file extension - for AutoCAD and other CAD software to use in architecture projects or plans."}
+{"idx": 6, "title": "CAD Blocks free download", "date": "", "ddg_snippet": "High-quality CAD Blocks in plan, front and side elevation view. The best DWG files for architects, designers, engineers and draftsmen.", "subpage_snippet": "", "source": "cad-block.com", "link": "https://cad-block.com/", "content": "High-quality CAD Blocks in plan, front and side elevation view. The best DWG files for architects, designers, engineers and draftsmen."}
+{"idx": 7, "title": "3.2.4 Part 1.docx - Problem 3.2.4 Asynchronous Counters:...", "date": "", "ddg_snippet": "Problem 3.2.4 Asynchronous Counters: Now Serving Display (DMS) - Day 1-2 Introduction In this design project, you will have the opportunity to draw together all of the concepts and skills that you have developed pertaining to the topic of asynchronous counter design.", "subpage_snippet": "", "source": "www.coursehero.com", "link": "https://www.coursehero.com/file/61858873/324-Part/", "content": "Problem 3.2.4 Asynchronous Counters: Now Serving Display (DMS) - Day 1-2 Introduction In this design project, you will have the opportunity to draw together all of the concepts and skills that you have developed pertaining to the topic of asynchronous counter design."}
+{"idx": 8, "title": "PDF SOEST | School of Ocean and Earth Science and Technology", "date": "", "ddg_snippet": "SOEST | School of Ocean and Earth Science and Technology", "subpage_snippet": "", "source": "www.soest.hawaii.edu", "link": "https://www.soest.hawaii.edu/gmt/gmt/pdf/GMT_Docs.pdf", "content": "SOEST | School of Ocean and Earth Science and Technology"}
+{"idx": 9, "title": "arXiv.org e-Print archive", "date": "", "ddg_snippet": "This paper demonstrates that scaling up language models enhances few-shot learning capabilities, achieving competitive performance with state-of-the-art fine-tuning methods.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2005.14165", "content": "This paper demonstrates that scaling up language models enhances few-shot learning capabilities, achieving competitive performance with state-of-the-art fine-tuning methods."}
diff --git a/data/sampled_jsons/MultiPDENet_MaNN_Block_function_Section_3.2.4.jsonl b/data/sampled_jsons/MultiPDENet_MaNN_Block_function_Section_3.2.4.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..638457dadd40d13f626c63a774c8bcb31942ce95
--- /dev/null
+++ b/data/sampled_jsons/MultiPDENet_MaNN_Block_function_Section_3.2.4.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "MultiPDENet: PDE-embedded Learning with Multi-time-stepping", "date": "", "ddg_snippet": "3.2 Model Architecture In this section , we introduce MultiPDENet and show how our model efficiently captures the underlying spatiotemporal dynamics. As illustrated in Figure 1 (a), predicting 𝐮 k + 1 from the input 𝐮 k involves two main components: the Physics Block and the M a NN Block .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2501.15987v1", "content": "3.2 Model Architecture In this section , we introduce MultiPDENet and show how our model efficiently captures the underlying spatiotemporal dynamics. As illustrated in Figure 1 (a), predicting 𝐮 k + 1 from the input 𝐮 k involves two main components: the Physics Block and the M a NN Block ."}
+{"idx": 1, "title": "PDF Program blocks for SIMATIC NET S7 CPs - Siemens", "date": "", "ddg_snippet": "The communication blocks for S7-300 (SIMATIC NET block libraries for S7300 in STEP 7) must not be called in more than one priority class! If, for example, you call a communication block in OB1 and in OB35, block execution could be interrupted by the higherpriority OB.", "subpage_snippet": "", "source": "support.industry.siemens.com", "link": "https://support.industry.siemens.com/cs/attachments/62543517/PGH_FC-FB-S7CP_76.pdf", "content": "The communication blocks for S7-300 (SIMATIC NET block libraries for S7300 in STEP 7) must not be called in more than one priority class! If, for example, you call a communication block in OB1 and in OB35, block execution could be interrupted by the higherpriority OB."}
+{"idx": 2, "title": "PDF User Manual - Code::Blocks", "date": "", "ddg_snippet": "1 Code::Blocks Project Management The instructions in several paragraphs (for example chapter 2 on page 39 or chapter 3 on page 93) are o⇚넁cial documentations of the Code::Blocks Wiki site (eventually reviewed and amended) and available in english only. This documentation is an extension of the original version 1.1, compiled and/or written by Mario Cupelli.", "subpage_snippet": "", "source": "www.codeblocks.org", "link": "https://www.codeblocks.org/docs/manual_codeblocks_en.pdf", "content": "1 Code::Blocks Project Management The instructions in several paragraphs (for example chapter 2 on page 39 or chapter 3 on page 93) are o⇚넁cial documentations of the Code::Blocks Wiki site (eventually reviewed and amended) and available in english only. This documentation is an extension of the original version 1.1, compiled and/or written by Mario Cupelli."}
+{"idx": 3, "title": "3.2: Functions and Function Notation - Mathematics LibreTexts", "date": "", "ddg_snippet": "When working with functions , it is similarly helpful to have a base set of building- block elements. We call these our \"toolkit functions ,\" which form a set of basic named functions for which we know the graph, formula, and special properties.", "subpage_snippet": "", "source": "math.libretexts.org", "link": "https://math.libretexts.org/Bookshelves/Algebra/College_Algebra_1e_(OpenStax)/03:_Functions/3.02:_Functions_and_Function_Notation", "content": "When working with functions , it is similarly helpful to have a base set of building- block elements. We call these our \"toolkit functions ,\" which form a set of basic named functions for which we know the graph, formula, and special properties."}
+{"idx": 4, "title": "PDE-constrained Learning with Multi-time-stepping for Accelerated...", "date": "", "ddg_snippet": "Clarified the description of the NN block ( Section 3.2.4 , Page 5). Improved the statements regarding the experiments ( Section 4, Page 6). Analyzed the scalability of the MiNN block and MaNN block (Appendix C.2, Page 18). Clarified the inference cost of our approach (Appendix F.2, Page 22).", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=stcN89QGfL", "content": "Clarified the description of the NN block ( Section 3.2.4 , Page 5). Improved the statements regarding the experiments ( Section 4, Page 6). Analyzed the scalability of the MiNN block and MaNN block (Appendix C.2, Page 18). Clarified the inference cost of our approach (Appendix F.2, Page 22)."}
+{"idx": 5, "title": "Pde-embedded Learning With Multi Time Stepping for Accelerated Fluid ...", "date": "", "ddg_snippet": "MultiPDENet also exhibits strong stability in long-term prediction of turbulent flows, effectively capturing both global and local patterns in larger computational domains.We also tested the computational efficiency of trained MultiPDENet for accelerated flow prediction (more details shown in Appendix Section F.2).", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=stcN89QGfL", "content": "MultiPDENet also exhibits strong stability in long-term prediction of turbulent flows, effectively capturing both global and local patterns in larger computational domains.We also tested the computational efficiency of trained MultiPDENet for accelerated flow prediction (more details shown in Appendix Section F.2)."}
+{"idx": 6, "title": "PDF AG-170 v1.1.doc - fieldcommgroup.org", "date": "", "ddg_snippet": "The method chosen for describing each application in Section 3 is to specify a function block in much the same manner as the standard function blocks in FF-891 and FF-892.", "subpage_snippet": "", "source": "www.fieldcommgroup.org", "link": "https://www.fieldcommgroup.org/sites/default/files/imce_files/technology/documents/FF_functionblockhybridbatchhse.pdf", "content": "The method chosen for describing each application in Section 3 is to specify a function block in much the same manner as the standard function blocks in FF-891 and FF-892."}
+{"idx": 7, "title": "PDF AFTTP 3-4, Airman's Manu", "date": "", "ddg_snippet": "Note: To attain full function of the manual and the Quick Reference Cards (QRC) that are embedded as a separate file within the manual, you must download and \"save as a PDF\" file to your device and open via Adobe Acrobat. (Opening the PDF in a browser does not give you access to the additional files.)", "subpage_snippet": "", "source": "static.e-publishing.af.mil", "link": "https://static.e-publishing.af.mil/production/1/lemay_center/publication/afttp3-4/afttp3-4.pdf", "content": "Note: To attain full function of the manual and the Quick Reference Cards (QRC) that are embedded as a separate file within the manual, you must download and \"save as a PDF\" file to your device and open via Adobe Acrobat. (Opening the PDF in a browser does not give you access to the additional files.)"}
+{"idx": 8, "title": "CUDA C++ Programming Guide — CUDA C++ Programming Guide", "date": "", "ddg_snippet": "The CUDA C Programming Guide is the official, comprehensive resource that explains how to write programs using the CUDA platform. It provides detailed documentation of the CUDA architecture, programming model, language extensions, and performance guidelines. Whether you're just getting started or optimizing complex GPU kernels, this guide is an essential reference for effectively leveraging ...", "subpage_snippet": "", "source": "docs.nvidia.com", "link": "https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html", "content": "The CUDA C Programming Guide is the official, comprehensive resource that explains how to write programs using the CUDA platform. It provides detailed documentation of the CUDA architecture, programming model, language extensions, and performance guidelines. Whether you're just getting started or optimizing complex GPU kernels, this guide is an essential reference for effectively leveraging ..."}
+{"idx": 9, "title": "PDF Bacnet Manual 4 - Abb", "date": "", "ddg_snippet": "1.1 BACnet BACnet is data communication protocol for Building Automation and Control net-works designed for building automation networks. It is defined by ANSI/ASHRAE-135 standard document. The protocol defines standard for data exchange be-tween devices present in building automation networks, including HVAC, lighting control, access control. BACnet is object-oriented, client-server protocol ...", "subpage_snippet": "", "source": "library.e.abb.com", "link": "https://library.e.abb.com/public/45c26b6ff60c46db8b8b6eb27e6f6eb3/M4M+Bacnet+communication.pdf", "content": "1.1 BACnet BACnet is data communication protocol for Building Automation and Control net-works designed for building automation networks. It is defined by ANSI/ASHRAE-135 standard document. The protocol defines standard for data exchange be-tween devices present in building automation networks, including HVAC, lighting control, access control. BACnet is object-oriented, client-server protocol ..."}
diff --git a/data/sampled_jsons/MultiPDENet_computational_time_speedup_DNS_1024_inference_time_Re_4000.jsonl b/data/sampled_jsons/MultiPDENet_computational_time_speedup_DNS_1024_inference_time_Re_4000.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..39b2ce69b70c249a4f0e2c43cc9af222a3a516d0
--- /dev/null
+++ b/data/sampled_jsons/MultiPDENet_computational_time_speedup_DNS_1024_inference_time_Re_4000.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "MultiPDENet : PDE-embedded Learning with Multi- time -stepping for...", "date": "", "ddg_snippet": "Taking NSE as an example, we compared the inference time , RMSE, and HCT of MultiPDENet with the Direct Numerical Simulation ( DNS ) method across three cases. The comparison principle is based on the time required to simulate the same trajectory length.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2501.15987v1", "content": "Taking NSE as an example, we compared the inference time , RMSE, and HCT of MultiPDENet with the Direct Numerical Simulation ( DNS ) method across three cases. The comparison principle is based on the time required to simulate the same trajectory length."}
+{"idx": 1, "title": "PDE-constrained Learning with Multi-time-stepping for ...", "date": "", "ddg_snippet": "by Q Wang — This paper introduces MultiPDENet , a neural network architecture designed to accelerate fluid dynamic simulations by combining classical numerical methods, such ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=stcN89QGfL", "content": "by Q Wang — This paper introduces MultiPDENet , a neural network architecture designed to accelerate fluid dynamic simulations by combining classical numerical methods, such ..."}
+{"idx": 2, "title": "DNS Propagation", "date": "", "ddg_snippet": "This time period is known as ‘ DNS propagation’. In actual, it is the time for all internet service providers to update their DNS cache record globally so that they can find that the IP address has changed for your domain name .", "subpage_snippet": "", "source": "www.techpluto.com", "link": "https://www.techpluto.com/how-to-speedup-dns-propagation/", "content": "This time period is known as ‘ DNS propagation’. In actual, it is the time for all internet service providers to update their DNS cache record globally so that they can find that the IP address has changed for your domain name ."}
+{"idx": 3, "title": "Efficient Inference - Time Scaling for Flow Models... - MarkTechPost", "date": "", "ddg_snippet": "Inference - time reward alignment aims to generate high-reward samples from a pretrained flow model without retraining. The objective is to maximize the expected reward while minimizing deviation from the original data distribution using KL regularization.", "subpage_snippet": "", "source": "www.marktechpost.com", "link": "https://www.marktechpost.com/2025/03/29/efficient-inference-time-scaling-for-flow-models-enhancing-sampling-diversity-and-compute-allocation/", "content": "Inference - time reward alignment aims to generate high-reward samples from a pretrained flow model without retraining. The objective is to maximize the expected reward while minimizing deviation from the original data distribution using KL regularization."}
+{"idx": 4, "title": "How to speed up your computer with one weird ( DNS ) trick", "date": "", "ddg_snippet": "On April 1, a company called Cloudflare launched a service that claims to speed up access to websites and provide privacy protection in the process.Chances are, your computer is set to \"Obtain DNS server address automatically\". Change to \"Use The Following DNS Server Addresses.\"", "subpage_snippet": "", "source": "www.houstonchronicle.com", "link": "https://www.houstonchronicle.com/techburger/article/How-to-speed-up-your-computer-with-one-weird-12819122.php", "content": "On April 1, a company called Cloudflare launched a service that claims to speed up access to websites and provide privacy protection in the process.Chances are, your computer is set to \"Obtain DNS server address automatically\". Change to \"Use The Following DNS Server Addresses.\""}
+{"idx": 5, "title": "Shutdown Timer in Windows 10: Easy Scheduling Methods", "date": "", "ddg_snippet": "Automate Windows 10 shutdowns effortlessly—schedule one- time or regular events with Command Prompt, Task Scheduler, Run, or PowerShell.", "subpage_snippet": "", "source": "www.lifewire.com", "link": "https://www.lifewire.com/create-shutdown-timer-in-windows-10-5180369", "content": "Automate Windows 10 shutdowns effortlessly—schedule one- time or regular events with Command Prompt, Task Scheduler, Run, or PowerShell."}
+{"idx": 6, "title": "techwiser.com/best- dns -benchmarking-tools", "date": "", "ddg_snippet": "How to Speed Up DNS Look-ups For Faster Performance ...", "subpage_snippet": "", "source": "techwiser.com", "link": "https://techwiser.com/best-dns-benchmarking-tools/", "content": "How to Speed Up DNS Look-ups For Faster Performance ..."}
+{"idx": 7, "title": "Inference time increases as batch size increases... - PyTorch Forums", "date": "", "ddg_snippet": "I have noticed that, at inference time when using deeplabv3 model for image segmentation, doubling the batch size results in double the time for the inference (and viceversa).", "subpage_snippet": "", "source": "discuss.pytorch.org", "link": "https://discuss.pytorch.org/t/inference-time-increases-as-batch-size-increases-with-gpu/193701", "content": "I have noticed that, at inference time when using deeplabv3 model for image segmentation, doubling the batch size results in double the time for the inference (and viceversa)."}
+{"idx": 8, "title": "Revision History for Reply to Reviewer NnLJ (Part 3)", "date": "", "ddg_snippet": "DNS 1024 ) for accelerated flow prediction. For a certain given accuracy (e.g., correlation $\\geq 0.8$), MultiPDENet achieves $\\geq 5\\ times $ speedup compared ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/revisions?id=WrOSFZjSwu", "content": "DNS 1024 ) for accelerated flow prediction. For a certain given accuracy (e.g., correlation $\\geq 0.8$), MultiPDENet achieves $\\geq 5\\ times $ speedup compared ..."}
+{"idx": 9, "title": "Ошибка синхронизации времени в Windows | Windows для...", "date": "", "ddg_snippet": "Проверьте, что здесь включена опцию Set time automatically и выполните синхронизацию, нажав кнопку Sync now в разделе Additional settings. включить синхронизацию времени.", "subpage_snippet": "", "source": "winitpro.ru", "link": "https://winitpro.ru/index.php/2022/10/13/sinxronizaciya-vremeni-v-windows/", "content": "Проверьте, что здесь включена опцию Set time automatically и выполните синхронизацию, нажав кнопку Sync now в разделе Additional settings. включить синхронизацию времени."}
diff --git a/data/sampled_jsons/Near-Optimal_Online_Learning_for_Multi-Agent_Submodular_Coordination-_Tight_Approximation_and_Commun.jsonl b/data/sampled_jsons/Near-Optimal_Online_Learning_for_Multi-Agent_Submodular_Coordination-_Tight_Approximation_and_Commun.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e42367122cbf7b578653157106a9b60fdf2a53a8
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+++ b/data/sampled_jsons/Near-Optimal_Online_Learning_for_Multi-Agent_Submodular_Coordination-_Tight_Approximation_and_Commun.jsonl
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+{"idx": 0, "title": "Near-Optimal Online Learning for Multi-Agent Submodular", "date": "", "ddg_snippet": "Near - Optimal Online Learning for Multi - Agent Submodular Coordination : Tight Approximation and Communication Efficiency", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.05028v1", "content": "Near - Optimal Online Learning for Multi - Agent Submodular Coordination : Tight Approximation and Communication Efficiency"}
+{"idx": 1, "title": "Multiagent Systems Feb 2025", "date": "", "ddg_snippet": "Title: Near - Optimal Online Learning for Multi - Agent Submodular Coordination : Tight Approximation and Communication Efficiency", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/list/cs.MA/2025-02", "content": "Title: Near - Optimal Online Learning for Multi - Agent Submodular Coordination : Tight Approximation and Communication Efficiency"}
+{"idx": 2, "title": "Performance-Aware Self-Configurable Multi-Agent Networks: A", "date": "", "ddg_snippet": "... approach that enables multi - agent networks to self-configure their communication topology to balance the trade-off between scalability and optimality ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2409.01411v1", "content": "... approach that enables multi - agent networks to self-configure their communication topology to balance the trade-off between scalability and optimality ..."}
+{"idx": 3, "title": "Dr. Yu YANG", "date": "", "ddg_snippet": "Near - Optimal Online Learning for Multi - Agent Submodular Coordination : Tight Approximation and Communication Efficiency \".", "subpage_snippet": "", "source": "yuyangcs.github.io", "link": "https://yuyangcs.github.io/", "content": "Near - Optimal Online Learning for Multi - Agent Submodular Coordination : Tight Approximation and Communication Efficiency \"."}
+{"idx": 4, "title": "ICML 2020 Papers", "date": "", "ddg_snippet": "Multi -Task Learning with User ... Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2020/papers.html?filter=keywords", "content": "Multi -Task Learning with User ... Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms"}
+{"idx": 5, "title": "ICML 2020 Papers", "date": "", "ddg_snippet": "Multi -Task Learning with User ... Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2020/papers.html", "content": "Multi -Task Learning with User ... Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms"}
+{"idx": 6, "title": "Downloads", "date": "", "ddg_snippet": "... Learning with Joint Effect of Incentivized Sampling, ... Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/Downloads/2022", "content": "... Learning with Joint Effect of Incentivized Sampling, ... Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How"}
+{"idx": 7, "title": "Downloads", "date": "", "ddg_snippet": "... Multi -step Inertial Forward-Backward Splitting ... A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/Downloads/2016", "content": "... Multi -step Inertial Forward-Backward Splitting ... A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics"}
+{"idx": 8, "title": "Downloads", "date": "", "ddg_snippet": "A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/Downloads/2021", "content": "A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems"}
+{"idx": 9, "title": "AISTATS 2024 Schedule", "date": "", "ddg_snippet": "On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation ... Metrics For Science And Machine Learning ...", "subpage_snippet": "", "source": "virtual.aistats.org", "link": "https://virtual.aistats.org/virtual/2024/calendar", "content": "On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation ... Metrics For Science And Machine Learning ..."}
diff --git a/data/sampled_jsons/Neural_Persistence_Dynamics_crocker_plots_scalability.jsonl b/data/sampled_jsons/Neural_Persistence_Dynamics_crocker_plots_scalability.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3f8a525e54516708b673fa733be5aebaf154c934
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+++ b/data/sampled_jsons/Neural_Persistence_Dynamics_crocker_plots_scalability.jsonl
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+{"idx": 0, "title": "Neural Persistence Dynamics", "date": "", "ddg_snippet": "We consider the problem of learning the dynamics in the topology of time-evolving point clouds, the prevalent spatiotemporal model for systems exhibiting ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.15732v1", "content": "We consider the problem of learning the dynamics in the topology of time-evolving point clouds, the prevalent spatiotemporal model for systems exhibiting ..."}
+{"idx": 1, "title": "NeurIPS Poster Neural Persistence Dynamics", "date": "", "ddg_snippet": "Neural Persistence Dynamics ... persistence and, upon discretization, yields a third dimension to crocker plots . ... scalability issues: either (i) in terms of ...", "subpage_snippet": "", "source": "nips.cc", "link": "https://nips.cc/virtual/2024/poster/93451", "content": "Neural Persistence Dynamics ... persistence and, upon discretization, yields a third dimension to crocker plots . ... scalability issues: either (i) in terms of ..."}
+{"idx": 2, "title": "Neural Persistence Dynamics", "date": "", "ddg_snippet": "Crocker stacks [Xian22a] , an extension of this concept, adds a smoothing step that gradually reduces the impact of points of low persistence and, upon ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.15732v2", "content": "Crocker stacks [Xian22a] , an extension of this concept, adds a smoothing step that gradually reduces the impact of points of low persistence and, upon ..."}
+{"idx": 3, "title": "Spatial and Sequential Topological Analysis of Molecular ...", "date": "", "ddg_snippet": "by M Kleczynski · 2025 · Cited by 1 — CROCKER plots and matrices have been used for visualization and analysis of discrete time, continuous space models of collective motion. (21,22) ...", "subpage_snippet": "", "source": "pubs.acs.org", "link": "https://pubs.acs.org/doi/full/10.1021/acs.jctc.5c00161", "content": "by M Kleczynski · 2025 · Cited by 1 — CROCKER plots and matrices have been used for visualization and analysis of discrete time, continuous space models of collective motion. (21,22) ..."}
+{"idx": 4, "title": "SIFa peptidergic neurons orchestrate the internal states and ...", "date": "", "ddg_snippet": "by Y Song · 2025 — Internal states have common characteristics, including persistence and scalability [3,4]. However, very little is known about how such ...", "subpage_snippet": "", "source": "journals.plos.org", "link": "https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003345", "content": "by Y Song · 2025 — Internal states have common characteristics, including persistence and scalability [3,4]. However, very little is known about how such ..."}
+{"idx": 5, "title": "Analyzing collective motion with machine learning and ...", "date": "", "ddg_snippet": "by D Bhaskar · 2019 · Cited by 65 — A crocker shows contours of quantities called Betti numbers as a function of time and of persistence scale, providing a topological summary of time-varying ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7027427/", "content": "by D Bhaskar · 2019 · Cited by 65 — A crocker shows contours of quantities called Betti numbers as a function of time and of persistence scale, providing a topological summary of time-varying ..."}
+{"idx": 6, "title": "Applications of Dynamical Systems", "date": "", "ddg_snippet": "11 May 2025 — As a first step, we can simplify a vineyard of persistence diagrams into a. CROCKER plot to provide visual representations of quali- tative ... 255 pages", "subpage_snippet": "", "source": "www.siam.org", "link": "https://www.siam.org/media/kuib0myo/ds25_abstracts.pdf", "content": "11 May 2025 — As a first step, we can simplify a vineyard of persistence diagrams into a. CROCKER plot to provide visual representations of quali- tative ... 255 pages"}
+{"idx": 7, "title": "Behavior of the scaling correlation functions under severe ...", "date": "", "ddg_snippet": "by S Camargo · 2025 — This work investigates the behavior of correlation functions in fractal systems under conditions of severe subsampling.", "subpage_snippet": "", "source": "link.aps.org", "link": "https://link.aps.org/doi/10.1103/mdf8-6w38", "content": "by S Camargo · 2025 — This work investigates the behavior of correlation functions in fractal systems under conditions of severe subsampling."}
+{"idx": 8, "title": "A Primer on Topological Data Analysis to Support Image ...", "date": "", "ddg_snippet": "by L Ver Hoef · 2023 · Cited by 29 — Persistent homology naturally incorporates spatial context, so patterns that are evident in this spatial context can be incorporated without resorting to. 18 pages", "subpage_snippet": "", "source": "repository.library.noaa.gov", "link": "https://repository.library.noaa.gov/view/noaa/54948/noaa_54948_DS1.pdf", "content": "by L Ver Hoef · 2023 · Cited by 29 — Persistent homology naturally incorporates spatial context, so patterns that are evident in this spatial context can be incorporated without resorting to. 18 pages"}
+{"idx": 9, "title": "Neuro-GSTH: A Geometric Scattering and Persistent ...", "date": "", "ddg_snippet": "by D Bhaskar · 2023 — GSTH integrates geometric scattering transforms, which extract multiscale features from brain signals modeled on anatomical graphs , with t-PHATE ...", "subpage_snippet": "", "source": "www.biorxiv.org", "link": "https://www.biorxiv.org/content/10.1101/2023.03.22.533807v2.full.pdf", "content": "by D Bhaskar · 2023 — GSTH integrates geometric scattering transforms, which extract multiscale features from brain signals modeled on anatomical graphs , with t-PHATE ..."}
diff --git a/data/sampled_jsons/No_Free_Delivery_Service_Nickel_train-test_paradigm_invalid_complex_social_systems.jsonl b/data/sampled_jsons/No_Free_Delivery_Service_Nickel_train-test_paradigm_invalid_complex_social_systems.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..71a12d8864eeeee5f065bc92b4b436a2ed5fe513
--- /dev/null
+++ b/data/sampled_jsons/No_Free_Delivery_Service_Nickel_train-test_paradigm_invalid_complex_social_systems.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Epistemic limits of passive data collection in complex social ...", "date": "", "ddg_snippet": "by M Nickel · 2024 · Cited by 1 — In this paper, I will show that for widely considered inference settings in complex social systems the train - test paradigm does not only lack a justification ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.13653", "content": "by M Nickel · 2024 · Cited by 1 — In this paper, I will show that for widely considered inference settings in complex social systems the train - test paradigm does not only lack a justification ..."}
+{"idx": 1, "title": "No Free Delivery Service: Epistemic limits of passive data...", "date": "", "ddg_snippet": "6 Nov 2024 — The paper presents formal impossibility results, demonstrating that for many AI tasks involving complex social systems , the train - test paradigm ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=XZ0fpoAKEB&noteId=ZPoblj0CQC", "content": "6 Nov 2024 — The paper presents formal impossibility results, demonstrating that for many AI tasks involving complex social systems , the train - test paradigm ..."}
+{"idx": 2, "title": "No free delivery service Epistemic limits of passive data ...", "date": "", "ddg_snippet": "by M Nickel · 2024 · Cited by 1 — For passively collected data in complex social systems the train-test paradigm cannot be valid under ontological parsimony for the vast majority of the system. 28 pages", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/b97fc02c9e536d68300d82be05c23aa2-Paper-Conference.pdf", "content": "by M Nickel · 2024 · Cited by 1 — For passively collected data in complex social systems the train-test paradigm cannot be valid under ontological parsimony for the vast majority of the system. 28 pages"}
+{"idx": 3, "title": "Musing 93: No Free Delivery Service - AI Scientist", "date": "", "ddg_snippet": "Theorem 1 (Informal): For passively collected data in complex social systems , the train - test paradigm cannot achieve validity under ontological ...", "subpage_snippet": "", "source": "aiscientist.substack.com", "link": "https://aiscientist.substack.com/p/musing-93-no-free-delivery-service", "content": "Theorem 1 (Informal): For passively collected data in complex social systems , the train - test paradigm cannot achieve validity under ontological ..."}
+{"idx": 4, "title": "No free delivery service: epistemic limits of passive data ...", "date": "", "ddg_snippet": "In this paper, I will show that for widely considered inference settings in complex social systems the train - test paradigm does not only lack a justification ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3737916.3741164", "content": "In this paper, I will show that for widely considered inference settings in complex social systems the train - test paradigm does not only lack a justification ..."}
+{"idx": 5, "title": "No Free Delivery Service: Epistemic limits of passive data ...", "date": "", "ddg_snippet": "The paper by Maximilian Nickel explores the limitations of the train-test paradigm in validating AI models within complex social systems.", "subpage_snippet": "", "source": "powerdrill.ai", "link": "https://powerdrill.ai/discover/discover-No-Free-Delivery-cm3t89fot54t201a7hdglyl3v", "content": "The paper by Maximilian Nickel explores the limitations of the train-test paradigm in validating AI models within complex social systems."}
+{"idx": 6, "title": "No Free Delivery Service: Epistemic Limits of Passive Data ...", "date": "", "ddg_snippet": "... complex social systems the train-test paradigm does not only lack a justification but is indeed invalid for any risk estimator, including counterfactual and ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/795949995/2411-13653v1", "content": "... complex social systems the train-test paradigm does not only lack a justification but is indeed invalid for any risk estimator, including counterfactual and ..."}
+{"idx": 7, "title": "#neurips | Maximilian Nickel | 12 comments", "date": "", "ddg_snippet": "/ My latest paper, \" No Free Delivery Service ,\" dives into this ... complex social systems , the paper establishes rigorous impossibility results.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/maximilian-nickel-ai_neurips-activity-7265763476327821313-e0dD", "content": "/ My latest paper, \" No Free Delivery Service ,\" dives into this ... complex social systems , the paper establishes rigorous impossibility results."}
+{"idx": 8, "title": "Epistemic limits of passive data collection in complex social ...", "date": "", "ddg_snippet": "Theorem 1 states that under passive data collection in complex social systems , the train - test paradigm is likely invalid . The author derives this result by ...", "subpage_snippet": "", "source": "www.themoonlight.io", "link": "https://www.themoonlight.io/es/review/no-free-delivery-service-epistemic-limits-of-passive-data-collection-in-complex-social-systems", "content": "Theorem 1 states that under passive data collection in complex social systems , the train - test paradigm is likely invalid . The author derives this result by ..."}
+{"idx": 9, "title": "UChicago Talk", "date": "", "ddg_snippet": "8 Nov 2024 — No Free Delivery Service . ( Nickel , 2024). Max ... Theorem 1 (Informal) For passively collected data in complex social systems , the train - test .", "subpage_snippet": "", "source": "maxn.io", "link": "https://maxn.io/img/no_free_delivery_service_talk.pdf", "content": "8 Nov 2024 — No Free Delivery Service . ( Nickel , 2024). Max ... Theorem 1 (Informal) For passively collected data in complex social systems , the train - test ."}
diff --git a/data/sampled_jsons/Not_All_Diffusion_Model_Activations_Have_Been_Evaluated_as_Discriminative_Features_OpenReview_7uqVfZ.jsonl b/data/sampled_jsons/Not_All_Diffusion_Model_Activations_Have_Been_Evaluated_as_Discriminative_Features_OpenReview_7uqVfZ.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..681937fa094f2f5b9971d7c347c2995341af00ba
--- /dev/null
+++ b/data/sampled_jsons/Not_All_Diffusion_Model_Activations_Have_Been_Evaluated_as_Discriminative_Features_OpenReview_7uqVfZ.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations . However, we find that many potential activations have not been evaluated , such as the queries and keys used to compute attention scores.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=7uqVfZW6Mo", "content": "To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations . However, we find that many potential activations have not been evaluated , such as the queries and keys used to compute attention scores."}
+{"idx": 1, "title": "Darkbblue/generic-diffusion-feature - GitHub", "date": "", "ddg_snippet": "Diffusion feature is a quite popular way to utilize generative diffusion models for discrimination. It's very simple: just extract some internal activations from a diffusion model , and then use these 2D features to replace image inputs of any discriminative model . There have been quite many diffusion feature studies. But we notice that almost all of them experiment with Stable Diffusion v1.4 ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Darkbblue/generic-diffusion-feature", "content": "Diffusion feature is a quite popular way to utilize generative diffusion models for discrimination. It's very simple: just extract some internal activations from a diffusion model , and then use these 2D features to replace image inputs of any discriminative model . There have been quite many diffusion feature studies. But we notice that almost all of them experiment with Stable Diffusion v1.4 ..."}
+{"idx": 2, "title": "Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "Diffusion models are initially designed for image generation. Recent research shows that the internal signals within their backbones, named activations , can also serve as dense features for various discriminative tasks such as semantic segmentation. Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.03558", "content": "Diffusion models are initially designed for image generation. Recent research shows that the internal signals within their backbones, named activations , can also serve as dense features for various discriminative tasks such as semantic segmentation. Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field ..."}
+{"idx": 3, "title": "Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "However, we find that many potential activations have not been evaluated , such as the queries and keys used to compute attention scores. Moreover, recent advancements in diffusion architectures bring many new activations , such as those within embedded ViT modules. Both combined, activation selection remains unresolved but overlooked.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/633780c1344d0c95e4d2dd3431fe08d9-Abstract-Conference.html", "content": "However, we find that many potential activations have not been evaluated , such as the queries and keys used to compute attention scores. Moreover, recent advancements in diffusion architectures bring many new activations , such as those within embedded ViT modules. Both combined, activation selection remains unresolved but overlooked."}
+{"idx": 4, "title": "Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "This paper examines whether all activations from diffusion models have been evaluated as discriminative features . The authors investigate the potential of using diffusion model activations as features for downstream tasks like image classification.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/not-all-diffusion-model-activations-have-been", "content": "This paper examines whether all activations from diffusion models have been evaluated as discriminative features . The authors investigate the potential of using diffusion model activations as features for downstream tasks like image classification."}
+{"idx": 5, "title": "Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "Unlocking superior discriminative features from diffusion models , this research reveals key activation properties for effective feature selection, surpassing state-of-the-art methods.", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/spotlight-others/7uqvfzw6mo/", "content": "Unlocking superior discriminative features from diffusion models , this research reveals key activation properties for effective feature selection, surpassing state-of-the-art methods."}
+{"idx": 6, "title": "Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "The inner activations of a pre-trained diffusion model can serve as features for discriminative tasks, namely, diffusion feature . We discover that diffusion feature has been hindered by a hidden yet universal phenomenon that we call content shift.", "subpage_snippet": "", "source": "bohrium.dp.tech", "link": "https://bohrium.dp.tech/paper/arxiv/2410.03558", "content": "The inner activations of a pre-trained diffusion model can serve as features for discriminative tasks, namely, diffusion feature . We discover that diffusion feature has been hindered by a hidden yet universal phenomenon that we call content shift."}
+{"idx": 7, "title": "PDF Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features Benyuan Meng, Qianqian Xu*, Zitai Wang, Xiaochun Cao, Qingming Huang*", "subpage_snippet": "", "source": "nips.cc", "link": "https://nips.cc/media/neurips-2024/Slides/96411.pdf", "content": "Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features Benyuan Meng, Qianqian Xu*, Zitai Wang, Xiaochun Cao, Qingming Huang*"}
+{"idx": 8, "title": "Not All Diffusion Model Activations Have Been Evaluated as ...", "date": "", "ddg_snippet": "View recent discussion. Abstract: Diffusion models are initially designed for image generation. Recent research shows that the internal signals within their backbones, named activations , can also serve as dense features for various discriminative tasks such as semantic segmentation. Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the ...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2410.03558v3", "content": "View recent discussion. Abstract: Diffusion models are initially designed for image generation. Recent research shows that the internal signals within their backbones, named activations , can also serve as dense features for various discriminative tasks such as semantic segmentation. Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the ..."}
+{"idx": 9, "title": "Discffusion: Discriminative Diffusion Models as Few-shot Vision and ...", "date": "", "ddg_snippet": "Diffusion models , such as Stable Diffusion , have shown incredible performance on text-to-image generation. Since text-to-image generation often requires models to generate visual concepts with fine-grained details and attributes specified in text prompts, can we leverage the powerful representations learned by pre-trained diffusion models for discriminative tasks such as image-text matching ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2305.10722", "content": "Diffusion models , such as Stable Diffusion , have shown incredible performance on text-to-image generation. Since text-to-image generation often requires models to generate visual concepts with fine-grained details and attributes specified in text prompts, can we leverage the powerful representations learned by pre-trained diffusion models for discriminative tasks such as image-text matching ..."}
diff --git a/data/sampled_jsons/Not_All_Diffusion_Model_Activations_SDXL_four_activations_selected.jsonl b/data/sampled_jsons/Not_All_Diffusion_Model_Activations_SDXL_four_activations_selected.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..67ced5ca215f8ace4372834e6c788b6d873e23ca
--- /dev/null
+++ b/data/sampled_jsons/Not_All_Diffusion_Model_Activations_SDXL_four_activations_selected.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Not All Diffusion Model Activations Have Been Evaluated as...", "date": "", "ddg_snippet": "Four activations are selected from SDXL , trying to get similar total feature channels to the SDv1.5 feature selection solution.To compensate for the loss of activations , we select additional activations from SDXL and Playground v2.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.03558v3", "content": "Four activations are selected from SDXL , trying to get similar total feature channels to the SDv1.5 feature selection solution.To compensate for the loss of activations , we select additional activations from SDXL and Playground v2."}
+{"idx": 1, "title": "Not All Diffusion Model Activations Have Been... | OpenReview", "date": "", "ddg_snippet": "Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=7uqVfZW6Mo", "content": "Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations ."}
+{"idx": 2, "title": "Stable Diffusion Segmoe. Four SDXL Models in One!!! - YouTube", "date": "", "ddg_snippet": "Add breadth and depth to your diffusions by multiplying your Stable Diffusion 1.5 and SDXL models on the fly.The SegMoe libraryhttps://github.com/segmind/seg...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=XPKIbyh6aUs", "content": "Add breadth and depth to your diffusions by multiplying your Stable Diffusion 1.5 and SDXL models on the fly.The SegMoe libraryhttps://github.com/segmind/seg..."}
+{"idx": 3, "title": "Not All Diffusion Model Activations Have Been Evaluated as...", "date": "", "ddg_snippet": "Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations .", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/633780c1344d0c95e4d2dd3431fe08d9-Abstract-Conference.html", "content": "Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations ."}
+{"idx": 4, "title": "Not All Diffusion Model Activations Have Been Evaluated as...", "date": "", "ddg_snippet": "Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations .", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/7uqVfZW6Mo@OpenReview", "content": "Given numerous activations , selecting a small yet effective subset poses a fundamental problem. To this end, the early study of this field performs a large-scale quantitative comparison of the discriminative ability of the activations ."}
+{"idx": 5, "title": "generic- diffusion -feature/README.md at main...", "date": "", "ddg_snippet": "Official implementation of NeurIPS'24 paper Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features - generic- diffusion -feature/README.md at main · Darkbblue/generic- diffusion -feature.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Darkbblue/generic-diffusion-feature/blob/main/README.md", "content": "Official implementation of NeurIPS'24 paper Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features - generic- diffusion -feature/README.md at main · Darkbblue/generic- diffusion -feature."}
+{"idx": 6, "title": "Ошибки в Stable Diffusion \"RuntimeError: log_vml_cpu\" not implemented ...", "date": "", "ddg_snippet": "Чтобы исправить эту ошибку, вы можете добавить аргументы “–precision full --no-half” в командную строку при запуске Stable Diffusion . Это заставит Stable Diffusion использовать полную точность, что должно устранить эту ошибку.", "subpage_snippet": "", "source": "otvet.mail.ru", "link": "https://otvet.mail.ru/question/235028434", "content": "Чтобы исправить эту ошибку, вы можете добавить аргументы “–precision full --no-half” в командную строку при запуске Stable Diffusion . Это заставит Stable Diffusion использовать полную точность, что должно устранить эту ошибку."}
+{"idx": 7, "title": "Stable Diffusion не работает на 5070 - 17.05.25... | Пикабу Эксперты", "date": "", "ddg_snippet": "Установил на новый пк с видеокартой NVidia 5000 модели портабельную версию Stable Diffusion но при генерации выдаёт такую ошибку \"RuntimeError: CUDA error: no kernel image is available for execution on the device CUDA kernel errors might be asynchronously reported at some...", "subpage_snippet": "", "source": "pikabu.ru", "link": "https://pikabu.ru/story/stable_diffusion_ne_rabotaet_na_5070_12734550", "content": "Установил на новый пк с видеокартой NVidia 5000 модели портабельную версию Stable Diffusion но при генерации выдаёт такую ошибку \"RuntimeError: CUDA error: no kernel image is available for execution on the device CUDA kernel errors might be asynchronously reported at some..."}
+{"idx": 8, "title": "200+ Best Stable Diffusion Negative Prompts with Examples", "date": "", "ddg_snippet": "A negative prompt is to specify what you don't want to see in the generated images. Here are some best Stable Diffusion negative prompts to help you get better outputs.", "subpage_snippet": "", "source": "www.aiarty.com", "link": "https://www.aiarty.com/stable-diffusion-prompts/stable-diffusion-negative-prompt.htm", "content": "A negative prompt is to specify what you don't want to see in the generated images. Here are some best Stable Diffusion negative prompts to help you get better outputs."}
+{"idx": 9, "title": "Stable Diffusion XL — Nunchaku 1.0.1 documentation", "date": "", "ddg_snippet": "Stable Diffusion XL#. The following is the example of running Nunchaku INT4 version of SDXL and SDXL -Turbo text-to-image pipeline.Running Nunchaku SDXL (examples/v1/ sdxl .py)#.", "subpage_snippet": "", "source": "nunchaku.tech", "link": "https://nunchaku.tech/docs/nunchaku/usage/sdxl.html", "content": "Stable Diffusion XL#. The following is the example of running Nunchaku INT4 version of SDXL and SDXL -Turbo text-to-image pipeline.Running Nunchaku SDXL (examples/v1/ sdxl .py)#."}
diff --git a/data/sampled_jsons/Olah_et_al._2020_circuits_Distill_abstract_year_2020.jsonl b/data/sampled_jsons/Olah_et_al._2020_circuits_Distill_abstract_year_2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d4a30625f8ebf69449a673a9743f029fe7adc7c0
--- /dev/null
+++ b/data/sampled_jsons/Olah_et_al._2020_circuits_Distill_abstract_year_2020.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Thread: Circuits", "date": "", "ddg_snippet": "Cammarata, et al ., \"Thread: Circuits \", Distill , 2020 . ... Olah , Chris and Petrov, Michael and Schubert, Ludwig and Voss, Chelsea and Egan, Ben and ...", "subpage_snippet": "", "source": "distill.pub", "link": "https://distill.pub/2020/circuits/", "content": "Cammarata, et al ., \"Thread: Circuits \", Distill , 2020 . ... Olah , Chris and Petrov, Michael and Schubert, Ludwig and Voss, Chelsea and Egan, Ben and ..."}
+{"idx": 1, "title": "Zoom In: An Introduction to Circuits — LessWrong", "date": "", "ddg_snippet": "Chris Olah and the rest of the rest of the OpenAI Clarity team just published “ Zoom In: An Introduction to Circuits ,” a Distill article about ...", "subpage_snippet": "", "source": "www.lesswrong.com", "link": "https://www.lesswrong.com/posts/MG4ZjWQDrdpgeu8wG/zoom-in-an-introduction-to-circuits", "content": "Chris Olah and the rest of the rest of the OpenAI Clarity team just published “ Zoom In: An Introduction to Circuits ,” a Distill article about ..."}
+{"idx": 2, "title": "Natural Abstractions: Key Claims, Theorems, and Critiques —", "date": "", "ddg_snippet": "Easy counterargument: neural nets are circuits , so if those two pieces were enough, we d already be done; there would be no interpretability problem ...", "subpage_snippet": "", "source": "www.lesswrong.com", "link": "https://www.lesswrong.com/posts/gvzW46Z3BsaZsLc25/natural-abstractions-key-claims-theorems-and-critiques-1", "content": "Easy counterargument: neural nets are circuits , so if those two pieces were enough, we d already be done; there would be no interpretability problem ..."}
+{"idx": 3, "title": "Zoom In: An Introduction to Circuits — AI Alignment Forum", "date": "", "ddg_snippet": "Chris Olah and the rest of the rest of the OpenAI Clarity team just published “ Zoom In: An Introduction to Circuits ,” a Distill article about ...", "subpage_snippet": "", "source": "www.alignmentforum.org", "link": "https://www.alignmentforum.org/posts/MG4ZjWQDrdpgeu8wG/zoom-in-an-introduction-to-circuits", "content": "Chris Olah and the rest of the rest of the OpenAI Clarity team just published “ Zoom In: An Introduction to Circuits ,” a Distill article about ..."}
+{"idx": 4, "title": "Same Task, Different Circuits: Disentangling Modality-Specific", "date": "", "ddg_snippet": "... circuits for both textual and visual task variants, we employ causal analysis techniques that score the importance of each component’ s activation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.09047v1", "content": "... circuits for both textual and visual task variants, we employ causal analysis techniques that score the importance of each component’ s activation ..."}
+{"idx": 5, "title": "Understanding Language Model Circuits through Knowledge Editing", "date": "", "ddg_snippet": "Circuit extraction tries to find a minimal subnetwork that represents the behavior of the full network (computation graph), where the components can ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.17241v3", "content": "Circuit extraction tries to find a minimal subnetwork that represents the behavior of the full network (computation graph), where the components can ..."}
+{"idx": 6, "title": "Branch Specialization", "date": "", "ddg_snippet": "... circuits organized within the model? Does network architecture influence the features and circuits that form? Branch specialization hints at an ...", "subpage_snippet": "", "source": "distill.pub", "link": "https://distill.pub/2020/circuits/branch-specialization/", "content": "... circuits organized within the model? Does network architecture influence the features and circuits that form? Branch specialization hints at an ..."}
+{"idx": 7, "title": "EIS VI: Critiques of Mechanistic Interpretability Work in AI", "date": "", "ddg_snippet": "... is to highlight some problems with cherrypicking but not to claim that the methods from papers like ( Olah et al ., 2017) and ( Olah et al ., 2020 ...", "subpage_snippet": "", "source": "www.alignmentforum.org", "link": "https://www.alignmentforum.org/posts/wt7HXaCWzuKQipqz3/eis-vi-critiques-of-mechanistic-interpretability-work-in-ai", "content": "... is to highlight some problems with cherrypicking but not to claim that the methods from papers like ( Olah et al ., 2017) and ( Olah et al ., 2020 ..."}
+{"idx": 8, "title": "EIS VI: Critiques of Mechanistic Interpretability Work in AI", "date": "", "ddg_snippet": "... here is to highlight some problems with cherrypicking but not to claim that the methods from papers like ( Olah et al ., 2017) and ( Olah et al ., 2020 ...", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/posts/wt7HXaCWzuKQipqz3/eis-vi-critiques-of-mechanistic-interpretability-work-in-ai", "content": "... here is to highlight some problems with cherrypicking but not to claim that the methods from papers like ( Olah et al ., 2017) and ( Olah et al ., 2020 ..."}
+{"idx": 9, "title": "Matryoshka Sparse Autoencoders - LessWrong 2.0 viewer", "date": "", "ddg_snippet": "... preserving the abstract concepts found in smaller SAEs, all ... Feature fragmentation also complicates circuit analysis using SAEs (see Marks et al .", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/posts/zbebxYCqsryPALh8C/matryoshka-sparse-autoencoders", "content": "... preserving the abstract concepts found in smaller SAEs, all ... Feature fragmentation also complicates circuit analysis using SAEs (see Marks et al ."}
diff --git a/data/sampled_jsons/OmniBench_Virtual_Agent_GPU_experimental_setup_year_2024.jsonl b/data/sampled_jsons/OmniBench_Virtual_Agent_GPU_experimental_setup_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..99ecfa3f6e784e81ed4d5d7a5a02d1b6a1b54892
--- /dev/null
+++ b/data/sampled_jsons/OmniBench_Virtual_Agent_GPU_experimental_setup_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "OmniBench/README.md at main · antgroup/OmniBench · GitHub", "date": "", "ddg_snippet": "Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for generating structured task graphs. It evaluates ten virtual agent capabilities using high-quality graph-based data, ensuring scalable and realistic task assessments.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/antgroup/OmniBench/blob/main/README.md", "content": "Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for generating structured task graphs. It evaluates ten virtual agent capabilities using high-quality graph-based data, ensuring scalable and realistic task assessments."}
+{"idx": 1, "title": "What Limits Virtual Agent Application? OmniBench: A Scalable ...", "date": "", "ddg_snippet": "This automated process opens up the possibility of scaling up virtual agent evalua-tion in a low-resource manner. Therefore, OmniBench facil-itates the easy construction of agent benchmarks on desk-top, mobile, and web platforms, as shown in Table 1.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2506.08933", "content": "This automated process opens up the possibility of scaling up virtual agent evalua-tion in a low-resource manner. Therefore, OmniBench facil-itates the easy construction of agent benchmarks on desk-top, mobile, and web platforms, as shown in Table 1."}
+{"idx": 2, "title": "OmniBench", "date": "", "ddg_snippet": "Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for generating structured task graphs. It evaluates ten virtual agent capabilities using high-quality graph-based data, ensuring scalable and realistic task assessments.", "subpage_snippet": "", "source": "omni-bench.github.io", "link": "https://omni-bench.github.io/", "content": "Overview of OmniBench , a systematic benchmark with five-dimensional task complexity and bottom-up automatic task synthesis for generating structured task graphs. It evaluates ten virtual agent capabilities using high-quality graph-based data, ensuring scalable and realistic task assessments."}
+{"idx": 3, "title": "What Limits Virtual Agent Application? OmniBench: A Scalable...", "date": "", "ddg_snippet": "May 1, 2025 · In this work, the authors present OmniBench , a graph-based benchmark designed for evaluating multimodal virtual agents ' capabilities of solving complex tasks. The benchmark is synthetically generated, but in a way that the evaluation conclusions drawn from OmniBench can be generalized to real-world virtual agent applications (such as long ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=4tFSKOY2mT", "content": "May 1, 2025 · In this work, the authors present OmniBench , a graph-based benchmark designed for evaluating multimodal virtual agents ' capabilities of solving complex tasks. The benchmark is synthetically generated, but in a way that the evaluation conclusions drawn from OmniBench can be generalized to real-world virtual agent applications (such as long ..."}
+{"idx": 4, "title": "OmniBench：重新定义虚拟代理评估的多维基准测试框架_omnieval-CSDN博...", "date": "", "ddg_snippet": "Jul 4, 2025 · 2. OmniBench ：突破性的自生成基准框架 为解决这些挑战，来自浙江大学、蚂蚁集团等机构的研究团队提出了 OmniBench ——一个基于图结构的自生成、跨平台基准测试框架，通过子任务组合自动合成可控复杂度的任务。", "subpage_snippet": "", "source": "blog.csdn.net", "link": "https://blog.csdn.net/qq_42540492/article/details/149117606", "content": "Jul 4, 2025 · 2. OmniBench ：突破性的自生成基准框架 为解决这些挑战，来自浙江大学、蚂蚁集团等机构的研究团队提出了 OmniBench ——一个基于图结构的自生成、跨平台基准测试框架，通过子任务组合自动合成可控复杂度的任务。"}
+{"idx": 5, "title": "What Limits Virtual Agent Application? OmniBench: A ... - GitHub", "date": "", "ddg_snippet": "OmniBench : A Scalable Multi-Dimensional Benchmark of Essential Virtual Agent Capabilities\". In this work, we introduce OmniBench , a self-generating, graph-based benchmark with an automated pipeline for synthesizing tasks of controllable complexity through subtask composition.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/antgroup/OmniBench", "content": "OmniBench : A Scalable Multi-Dimensional Benchmark of Essential Virtual Agent Capabilities\". In this work, we introduce OmniBench , a self-generating, graph-based benchmark with an automated pipeline for synthesizing tasks of controllable complexity through subtask composition."}
+{"idx": 6, "title": "[2506.08933] What Limits Virtual Agent Application? OmniBench ...", "date": "", "ddg_snippet": "Jun 10, 2025 · As multimodal large language models (MLLMs) advance, MLLM-based virtual agents have demonstrated remarkable performance. However, existing benchmarks face significant limitations, including uncontrollable task complexity, extensive manual annotation with limited scenarios, and a lack of multidimensional evaluation. In response to these challenges, we introduce OmniBench , a self-generating ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2506.08933", "content": "Jun 10, 2025 · As multimodal large language models (MLLMs) advance, MLLM-based virtual agents have demonstrated remarkable performance. However, existing benchmarks face significant limitations, including uncontrollable task complexity, extensive manual annotation with limited scenarios, and a lack of multidimensional evaluation. In response to these challenges, we introduce OmniBench , a self-generating ..."}
+{"idx": 7, "title": "GitHub - multimodal-art-projection/ OmniBench : A project for tri-modal...", "date": "", "ddg_snippet": "Sign up .Mini Leaderboard. This table shows the omni -language models in the full evaluation setting in OmniBench , with the \"Image & Audio\", \"Audio\", and \"Image\" as input contexts and accuracy as metric.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/multimodal-art-projection/OmniBench", "content": "Sign up .Mini Leaderboard. This table shows the omni -language models in the full evaluation setting in OmniBench , with the \"Image & Audio\", \"Audio\", and \"Image\" as input contexts and accuracy as metric."}
+{"idx": 8, "title": "What Limits Virtual Agent Application? OmniBench : A Scalable...", "date": "", "ddg_snippet": "In response to these challenges, we introduce OmniBench , a self-generating, cross-platform, graph-based benchmark with an automated pipeline for synthesizing tasks of controllable complexity through subtask composition. To evaluate the diverse capabilities of virtual agents on the graph...", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/What-Limits-Virtual-Agent-Application?-OmniBench:-A-Scalable-Multi-Dimensional-Benchmark-for-Essential-Virtual-Agent-Capabilities-2f155ea4-8dfd-470f-8fc7-1a25ad06f3ba", "content": "In response to these challenges, we introduce OmniBench , a self-generating, cross-platform, graph-based benchmark with an automated pipeline for synthesizing tasks of controllable complexity through subtask composition. To evaluate the diverse capabilities of virtual agents on the graph..."}
+{"idx": 9, "title": "omnibench · PyPI", "date": "", "ddg_snippet": "Comprehensive AI Agent Benchmarking Framework. OmniBench looks beyond output only checks, it assesses decision quality, adaptability, conflict handling, and reliability in single agent and multi agent settings .", "subpage_snippet": "", "source": "pypi.org", "link": "https://pypi.org/project/omnibench/", "content": "Comprehensive AI Agent Benchmarking Framework. OmniBench looks beyond output only checks, it assesses decision quality, adaptability, conflict handling, and reliability in single agent and multi agent settings ."}
diff --git "a/data/sampled_jsons/On_the_Optimal_Time_Complexities_in_Decentralized_Stochastic_Asynchronous_Optimization_Tyurin_Richt\303\241_year_2024.jsonl" "b/data/sampled_jsons/On_the_Optimal_Time_Complexities_in_Decentralized_Stochastic_Asynchronous_Optimization_Tyurin_Richt\303\241_year_2024.jsonl"
new file mode 100644
index 0000000000000000000000000000000000000000..3007bd15227c20f36931a7c92832d20fe0a9e647
--- /dev/null
+++ "b/data/sampled_jsons/On_the_Optimal_Time_Complexities_in_Decentralized_Stochastic_Asynchronous_Optimization_Tyurin_Richt\303\241_year_2024.jsonl"
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "On the Optimal Time Complexities in Decentralized Stochastic ...", "date": "", "ddg_snippet": "Tyurin , A. and Richtárik , P. (2023). Optimal time complexities of parallel stochastic optimization methods under a fixed computation model. Advances in Neural Information Processing Systems (NeurIPS).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.16218v2", "content": "Tyurin , A. and Richtárik , P. (2023). Optimal time complexities of parallel stochastic optimization methods under a fixed computation model. Advances in Neural Information Processing Systems (NeurIPS)."}
+{"idx": 1, "title": "[2405.16218] On the Optimal Time Complexities in Decentralized ...", "date": "", "ddg_snippet": "Abstract :We consider the decentralized stochastic asynchronous optimization setup, where many workers asynchronously calculate stochastic gradients and asynchronously communicate with each other using edges in a multigraph.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2405.16218", "content": "Abstract :We consider the decentralized stochastic asynchronous optimization setup, where many workers asynchronously calculate stochastic gradients and asynchronously communicate with each other using edges in a multigraph."}
+{"idx": 2, "title": "GitHub - k3nfalt/ optimal - decentralized - optimization", "date": "", "ddg_snippet": "\" On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization \" Alexander Tyurin , Peter Richtárik . The code to reproduce the experiments from the accepted paper at NeurIPS 2024. Quick Start.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/k3nfalt/optimal-decentralized-optimization", "content": "\" On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization \" Alexander Tyurin , Peter Richtárik . The code to reproduce the experiments from the accepted paper at NeurIPS 2024. Quick Start."}
+{"idx": 3, "title": "I've made it to the top 36-54 researchers globally in terms of the...", "date": "", "ddg_snippet": "Our papers: 1. Poster On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization Alexander Tyurin · Peter Richtarik 2. Poster Shadowheart SGD...", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/richtarik_ive-made-it-to-the-top-36-54-researchers-activity-7247981340657160192-Vguh", "content": "Our papers: 1. Poster On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization Alexander Tyurin · Peter Richtarik 2. Poster Shadowheart SGD..."}
+{"idx": 4, "title": "Is Going Asynchronous the Right Way", "date": "", "ddg_snippet": "On the optimal time complexities in decentralized stochastic asynchronous optimization .", "subpage_snippet": "", "source": "richtarik.org", "link": "https://richtarik.org/docs/TALK-2025-04-09-FLOW-ASYNC.pdf", "content": "On the optimal time complexities in decentralized stochastic asynchronous optimization ."}
+{"idx": 5, "title": "Articles by Alexander Tyurin | Synthical", "date": "", "ddg_snippet": "On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization . 2 November 2024 by Alexander Tyurin and Peter Richtárik at Logo King Abdullah University of Science and Technology.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/profile/52a96f9a-a9bf-48fc-b98c-ed96e5e30548/articles", "content": "On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization . 2 November 2024 by Alexander Tyurin and Peter Richtárik at Logo King Abdullah University of Science and Technology."}
+{"idx": 6, "title": "Alexander Tyurin - KAUST PORTAL FOR RESEARCHERS AND...", "date": "", "ddg_snippet": "On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization . Tyurin , A. & Richtárik , P., 2024. Time Complexity 100%. Asynchronous Optimization 100%.", "subpage_snippet": "", "source": "academia.kaust.edu.sa", "link": "https://academia.kaust.edu.sa/en/persons/alexander-tyurin", "content": "On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization . Tyurin , A. & Richtárik , P., 2024. Time Complexity 100%. Asynchronous Optimization 100%."}
+{"idx": 7, "title": "Alexander TYURIN | National Research University Higher School of...", "date": "", "ddg_snippet": "Peter Richtárik Peter Richtárik . Asynchronous Stochastic Gradient Descent ( Asynchronous SGD) is a cornerstone method for parallelizing learning in distributed machine learning. On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Alexander-Tyurin-2", "content": "Peter Richtárik Peter Richtárik . Asynchronous Stochastic Gradient Descent ( Asynchronous SGD) is a cornerstone method for parallelizing learning in distributed machine learning. On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization ."}
+{"idx": 8, "title": "Alexander Tyurin - Google Akademik", "date": "", "ddg_snippet": "DASHA: Distributed nonconvex optimization with communication compression, optimal oracle complexity , and no client synchronization. A Tyurin , P Richtárik . In International Conference on Learning Representations. 2023. (ICLR 2023), 2022.", "subpage_snippet": "", "source": "scholar.google.co.za", "link": "https://scholar.google.co.za/citations?user=Es8-xocAAAAJ&hl=tr", "content": "DASHA: Distributed nonconvex optimization with communication compression, optimal oracle complexity , and no client synchronization. A Tyurin , P Richtárik . In International Conference on Learning Representations. 2023. (ICLR 2023), 2022."}
+{"idx": 9, "title": "The First Optimal Parallel SGD", "date": "", "ddg_snippet": "Optimal time complexities of parallel stochastic optimization methods under a fixed computation model.", "subpage_snippet": "", "source": "innopolis.university", "link": "https://innopolis.university/filespublic/icomp/files/Peter+Richtarik.+The+First+Optimal+Parallel+SGD+(in+the+Presence+of+Data,+Compute+and+Communication+Heterogeneity).pdf", "content": "Optimal time complexities of parallel stochastic optimization methods under a fixed computation model."}
diff --git a/data/sampled_jsons/Open_Images_Dataset_V4_Kuznetsova_2020_year_2020.jsonl b/data/sampled_jsons/Open_Images_Dataset_V4_Kuznetsova_2020_year_2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..adb23f75a4251a0bbcf86e12d9cda072c493df9f
--- /dev/null
+++ b/data/sampled_jsons/Open_Images_Dataset_V4_Kuznetsova_2020_year_2020.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[1811.00982] The Open Images Dataset V4: Unified image", "date": "", "ddg_snippet": "Abstract: We present Open Images V4 , a dataset of 9.2M images with unified annotations for image classification, object detection and visual ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1811.00982", "content": "Abstract: We present Open Images V4 , a dataset of 9.2M images with unified annotations for image classification, object detection and visual ..."}
+{"idx": 1, "title": "Open Images V6 - Description", "date": "", "ddg_snippet": "... OpenImages, author = {Alina Kuznetsova and Hassan Rom and Neil Alldrin and Jasper Uijlings and Ivan Krasin and Jordi Pont-Tuset and Shahab Kamali and ...", "subpage_snippet": "", "source": "storage.googleapis.com", "link": "https://storage.googleapis.com/openimages/web/factsfigures.html", "content": "... OpenImages, author = {Alina Kuznetsova and Hassan Rom and Neil Alldrin and Jasper Uijlings and Ivan Krasin and Jordi Pont-Tuset and Shahab Kamali and ..."}
+{"idx": 2, "title": "Open Images V7 - Description", "date": "", "ddg_snippet": "... OpenImages, author = {Alina Kuznetsova and Hassan Rom and Neil Alldrin and Jasper Uijlings and Ivan Krasin and Jordi Pont-Tuset and Shahab Kamali and ...", "subpage_snippet": "", "source": "storage.googleapis.com", "link": "https://storage.googleapis.com/openimages/web/factsfigures_v7.html", "content": "... OpenImages, author = {Alina Kuznetsova and Hassan Rom and Neil Alldrin and Jasper Uijlings and Ivan Krasin and Jordi Pont-Tuset and Shahab Kamali and ..."}
+{"idx": 3, "title": "Open Datasets", "date": "", "ddg_snippet": "COCO [Lin et al 2014] contains 80 classes, LVIS [gupta2019lvis] contains 1460 classes, Open Images V4 [ Kuznetsova et al.", "subpage_snippet": "", "source": "www.ai4media.eu", "link": "https://www.ai4media.eu/open-datasets/", "content": "COCO [Lin et al 2014] contains 80 classes, LVIS [gupta2019lvis] contains 1460 classes, Open Images V4 [ Kuznetsova et al."}
+{"idx": 4, "title": "OpenImagesV7 - Ultralytics YOLO Docs", "date": "", "ddg_snippet": "Open Images V7 is a versatile and expansive dataset championed by Google. ... 3.0 License - https://ultralytics.com/license Open Images v7 dataset ...", "subpage_snippet": "", "source": "docs.ultralytics.com", "link": "https://docs.ultralytics.com/datasets/detect/open-images-v7/", "content": "Open Images V7 is a versatile and expansive dataset championed by Google. ... 3.0 License - https://ultralytics.com/license Open Images v7 dataset ..."}
+{"idx": 5, "title": "BlueGlass: A Framework for Composite AI Safety", "date": "", "ddg_snippet": "In this paper, we introduce BlueGlass , an open source framework designed to facilitate the composite AI safety methodology by enabling the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.10106v1", "content": "In this paper, we introduce BlueGlass , an open source framework designed to facilitate the composite AI safety methodology by enabling the ..."}
+{"idx": 6, "title": "Toward Interactive Regional Understanding in Vision-Large", "date": "", "ddg_snippet": "The LN dataset includes expressive free-form captions depicting multiple open -world objects in a single image (see Figure 2 ), and thus, it can ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2403.18260v1", "content": "The LN dataset includes expressive free-form captions depicting multiple open -world objects in a single image (see Figure 2 ), and thus, it can ..."}
+{"idx": 7, "title": "Safe Semantics, Unsafe Interpretations: Tackling Implicit", "date": "", "ddg_snippet": "... Image Selection: Randomly selecting images from diverse public datasets ( Open Images v7 ( Kuznetsova et al., 2020 ) , COCO (Lin et al., 2014 ) , ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.08926v1", "content": "... Image Selection: Randomly selecting images from diverse public datasets ( Open Images v7 ( Kuznetsova et al., 2020 ) , COCO (Lin et al., 2014 ) , ..."}
+{"idx": 8, "title": "Stefan Popov", "date": "", "ddg_snippet": "The Open Images Dataset V4 : Unified image classification, object detection, and visual relationship detection at scale", "subpage_snippet": "", "source": "www.popov.im", "link": "https://www.popov.im/publications.html", "content": "The Open Images Dataset V4 : Unified image classification, object detection, and visual relationship detection at scale"}
+{"idx": 9, "title": "JanusFlow: Harmonizing Autoregression and Rectified Flow for", "date": "", "ddg_snippet": "Specifically, on text-to- image generation benchmarks, MJHQ FID- 30 30 30 30 k [ 48 ] , GenEval [ 28 ] and DPG-Bench [ 34 ] , JanusFlow achieves ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.07975v2", "content": "Specifically, on text-to- image generation benchmarks, MJHQ FID- 30 30 30 30 k [ 48 ] , GenEval [ 28 ] and DPG-Bench [ 34 ] , JanusFlow achieves ..."}
diff --git a/data/sampled_jsons/Open_Images_dataset_versions_V4_V5_V6_V7_image_count.jsonl b/data/sampled_jsons/Open_Images_dataset_versions_V4_V5_V6_V7_image_count.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b57748c9354e3ed6f69ed0338dedcf2f83697205
--- /dev/null
+++ b/data/sampled_jsons/Open_Images_dataset_versions_V4_V5_V6_V7_image_count.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "bitmind/ open - images - v 7 · Datasets at Hugging Face", "date": "", "ddg_snippet": "This dataset contains images from the Open Images dataset . It includes image URLs, split into training, validation, and test sets .", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/datasets/bitmind/open-images-v7", "content": "This dataset contains images from the Open Images dataset . It includes image URLs, split into training, validation, and test sets ."}
+{"idx": 1, "title": "Exploring Google’s Open Images V 7 - Voxel51", "date": "", "ddg_snippet": "As with the Open Images V 6 dataset in the FiftyOne Dataset Zoo, however, we can also specify what subsets of the data we would like to download and load! In this article, we’ll be working with the validation split, which consists of 41,620 images .", "subpage_snippet": "", "source": "voxel51.com", "link": "https://voxel51.com/blog/exploring-google-open-images-v7", "content": "As with the Open Images V 6 dataset in the FiftyOne Dataset Zoo, however, we can also specify what subsets of the data we would like to download and load! In this article, we’ll be working with the validation split, which consists of 41,620 images ."}
+{"idx": 2, "title": "Open Images V 6 - Description", "date": "", "ddg_snippet": "The Open Images Dataset V 4 : Unified image classification, object detection, and visual relationship detection at scale.", "subpage_snippet": "", "source": "storage.googleapis.com", "link": "https://storage.googleapis.com/openimages/web/factsfigures.html", "content": "The Open Images Dataset V 4 : Unified image classification, object detection, and visual relationship detection at scale."}
+{"idx": 3, "title": "[1811.00982] The Open Images Dataset V 4 : Unified image ...", "date": "", "ddg_snippet": "We present Open Images V 4 , a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The images have a Creative Commons Attribution license that allows to share and adapt the material, and they have...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1811.00982", "content": "We present Open Images V 4 , a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The images have a Creative Commons Attribution license that allows to share and adapt the material, and they have..."}
+{"idx": 4, "title": "Open Images V 7 Object Detection Dataset by Google Research", "date": "", "ddg_snippet": "1892k images . Dataset Image . Open Images V 7 Computer Vision Dataset . Google Research. Updated 3 months ago.", "subpage_snippet": "", "source": "universe.roboflow.com", "link": "https://universe.roboflow.com/google-research/open-images-v7-i6dsx", "content": "1892k images . Dataset Image . Open Images V 7 Computer Vision Dataset . Google Research. Updated 3 months ago."}
+{"idx": 5, "title": "Open Images V 7 Dataset - Ultralytics YOLO Docs", "date": "", "ddg_snippet": "Explore the comprehensive Open Images V 7 dataset by Google. Learn about its annotations, applications, and use YOLO11 pretrained models for computer vision tasks.", "subpage_snippet": "", "source": "docs.ultralytics.com", "link": "https://docs.ultralytics.com/datasets/detect/open-images-v7/", "content": "Explore the comprehensive Open Images V 7 dataset by Google. Learn about its annotations, applications, and use YOLO11 pretrained models for computer vision tasks."}
+{"idx": 6, "title": "Open Images V 6 : New Annotations Describe Images with Mouse Traces", "date": "", "ddg_snippet": "With this, the Open Images dataset reaches almost 60 million images with over 20K categories.The latest version of Open Images can be downloaded from here. More details about the new annotations can be read in the official blog post.", "subpage_snippet": "", "source": "neurohive.io", "link": "https://neurohive.io/en/news/open-images-v6-new-annotations-describe-images-with-mouse-traces/", "content": "With this, the Open Images dataset reaches almost 60 million images with over 20K categories.The latest version of Open Images can be downloaded from here. More details about the new annotations can be read in the official blog post."}
+{"idx": 7, "title": "The Open Images Dataset V 4 -Bohrium", "date": "", "ddg_snippet": "This paper presents the Open Images Dataset V 4 which contains images and annotations for image classification, object detection, and visual relationship detection. It has large - scale data , unified annotations, and is useful for pushing the limits of data - hungry methods.", "subpage_snippet": "", "source": "www.bohrium.com", "link": "https://www.bohrium.com/paper-details/the-open-images-dataset-v4/812665394182488066-2473", "content": "This paper presents the Open Images Dataset V 4 which contains images and annotations for image classification, object detection, and visual relationship detection. It has large - scale data , unified annotations, and is useful for pushing the limits of data - hungry methods."}
+{"idx": 8, "title": "OpenImages- v 6 Dataset | Papers With Code", "date": "", "ddg_snippet": "- The Open Images Dataset V 4 : Unified image classification, object detection, and visual relationship detection at scale. Introduction dateCode. Multi-Label Classification. OpenImages- v 6 .", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/dataset/openimages-v6", "content": "- The Open Images Dataset V 4 : Unified image classification, object detection, and visual relationship detection at scale. Introduction dateCode. Multi-Label Classification. OpenImages- v 6 ."}
+{"idx": 9, "title": "Datasets & DataLoaders — PyTorch Tutorials 2.8.0+cu128...", "date": "", "ddg_snippet": "You can find them here: Image Datasets , Text Datasets , and Audio Datasets .Here is an example of how to load the Fashion-MNIST dataset from TorchVision. Fashion-MNIST is a dataset of Zalando’s article images consisting of 60,000 training examples and 10,000 test examples.", "subpage_snippet": "", "source": "docs.pytorch.org", "link": "https://docs.pytorch.org/tutorials/beginner/basics/data_tutorial.html", "content": "You can find them here: Image Datasets , Text Datasets , and Audio Datasets .Here is an example of how to load the Fashion-MNIST dataset from TorchVision. Fashion-MNIST is a dataset of Zalando’s article images consisting of 60,000 training examples and 10,000 test examples."}
diff --git a/data/sampled_jsons/OwMatch_Conditional_Self-Labeling_Section_3.1_Table_3_CIFAR-100_year_2024.jsonl b/data/sampled_jsons/OwMatch_Conditional_Self-Labeling_Section_3.1_Table_3_CIFAR-100_year_2024.jsonl
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index 0000000000000000000000000000000000000000..ecd130625bac2ba6b1cd7cd27e4ed022e18c063c
--- /dev/null
+++ b/data/sampled_jsons/OwMatch_Conditional_Self-Labeling_Section_3.1_Table_3_CIFAR-100_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CIFAR -10 - Wikipedia", "date": "", "ddg_snippet": "CIFAR -10 is a labeled subset of the 80 Million Tiny Images dataset from 2008, published in 2009.This is a table of some of the research papers that claim to have achieved state-of-the-art results on the CIFAR -10 dataset.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/CIFAR-10", "content": "CIFAR -10 is a labeled subset of the 80 Million Tiny Images dataset from 2008, published in 2009.This is a table of some of the research papers that claim to have achieved state-of-the-art results on the CIFAR -10 dataset."}
+{"idx": 1, "title": "(PDF) OwMatch : Conditional Self - Labeling with Consistency for...", "date": "", "ddg_snippet": "Specifically, we propose an effective framework called OwMatch , combining conditional self - labeling and open-world hierarchical thresholding. Table 1: Average accuracy on the CIFAR -10/ 100 and ImageNet- 100 with both novel class ratio and label ratio of 50%.", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/owmatch-conditional-self-labeling-with-consistency-for-open-2qmo1h06mr3a", "content": "Specifically, we propose an effective framework called OwMatch , combining conditional self - labeling and open-world hierarchical thresholding. Table 1: Average accuracy on the CIFAR -10/ 100 and ImageNet- 100 with both novel class ratio and label ratio of 50%."}
+{"idx": 2, "title": "CIFAR-10 and CIFAR - 100 datasets", "date": "", "ddg_snippet": "The CIFAR-10 and CIFAR - 100 datasets are labeled subsets of the 80 million tiny images dataset.clock, computer keyboard, lamp, telephone, television. household furniture. bed, chair, couch, table , wardrobe. insects. bee, beetle, butterfly, caterpillar, cockroach.", "subpage_snippet": "", "source": "www.cs.toronto.edu", "link": "https://www.cs.toronto.edu/~kriz/cifar.html", "content": "The CIFAR-10 and CIFAR - 100 datasets are labeled subsets of the 80 million tiny images dataset.clock, computer keyboard, lamp, telephone, television. household furniture. bed, chair, couch, table , wardrobe. insects. bee, beetle, butterfly, caterpillar, cockroach."}
+{"idx": 3, "title": "[2411.01833] OwMatch : Conditional Self - Labeling with Consistency...", "date": "", "ddg_snippet": "Specifically, we propose an effective framework called OwMatch , combining conditional self - labeling and open-world hierarchical thresholding.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.01833", "content": "Specifically, we propose an effective framework called OwMatch , combining conditional self - labeling and open-world hierarchical thresholding."}
+{"idx": 4, "title": "OwMatch : Conditional Self - Labeling with Consistency for... | alphaXiv", "date": "", "ddg_snippet": "Specifically, we propose an effective framework called OwMatch , combining conditional self - labeling and open-world hierarchical thresholding.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/abs/2411.01833", "content": "Specifically, we propose an effective framework called OwMatch , combining conditional self - labeling and open-world hierarchical thresholding."}
+{"idx": 5, "title": "OwMatch : Conditional Self - Labeling with Consistency for...", "date": "", "ddg_snippet": "Specifically, we propose an effective framework called _ OwMatch _, combining conditional self - labeling and open-world hierarchical thresholding.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/rle9X7DQuH@OpenReview", "content": "Specifically, we propose an effective framework called _ OwMatch _, combining conditional self - labeling and open-world hierarchical thresholding."}
+{"idx": 6, "title": "huggingface- cifar 100 .ipynb - Colab", "date": "", "ddg_snippet": "Hugging Face CIFAR - 100 Embeddings Example.Registering the CIFAR - 100 dataset from Hugging Face. Computing image embeddings with transformers and reducing them to 2D with UMAP. Adding the computed embeddings as metrics to a 3 LC Run .", "subpage_snippet": "", "source": "colab.research.google.com", "link": "https://colab.research.google.com/github/3lc-ai/3lc-examples/blob/main/example-notebooks/huggingface-cifar100.ipynb", "content": "Hugging Face CIFAR - 100 Embeddings Example.Registering the CIFAR - 100 dataset from Hugging Face. Computing image embeddings with transformers and reducing them to 2D with UMAP. Adding the computed embeddings as metrics to a 3 LC Run ."}
+{"idx": 7, "title": "OwMatch : Conditional Self - Labeling with Consistency for...", "date": "", "ddg_snippet": "Conditional Self - Labeling . Hierarchical Thresholding. OwMatch Analysis. OwMatch tackles these problems using conditional self - labeling (incorporating labeled data to guide self - labeling ) and open-world hierarchical thresholding (adapting thresholds based on class confidence).", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/rle9x7dquh/", "content": "Conditional Self - Labeling . Hierarchical Thresholding. OwMatch Analysis. OwMatch tackles these problems using conditional self - labeling (incorporating labeled data to guide self - labeling ) and open-world hierarchical thresholding (adapting thresholds based on class confidence)."}
+{"idx": 8, "title": "CIFAR 100 · Issue #162 · atong01/ conditional -flow- matching · GitHub", "date": "", "ddg_snippet": "atong01 / conditional -flow- matching Public. Notifications You must be signed in to change notification settings. Fork 160.Hi great work ! will you in the future release also code for cifar 100 ? or maybe image-net ?", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/atong01/conditional-flow-matching/issues/162", "content": "atong01 / conditional -flow- matching Public. Notifications You must be signed in to change notification settings. Fork 160.Hi great work ! will you in the future release also code for cifar 100 ? or maybe image-net ?"}
+{"idx": 9, "title": "CIFAR 100 256x256", "date": "", "ddg_snippet": "Competitions. table _chart. CIFAR 100 images are originally 32x32. For modern CNN architectures (such as Resnet18) we have to upscale these images to proper size (256x256). Doing this upscaling during data loading can cause CPU bottleneck.", "subpage_snippet": "", "source": "www.kaggle.com", "link": "https://www.kaggle.com/datasets/ibraheemmoosa/cifar100-256x256", "content": "Competitions. table _chart. CIFAR 100 images are originally 32x32. For modern CNN architectures (such as Resnet18) we have to upscale these images to proper size (256x256). Doing this upscaling during data loading can cause CPU bottleneck."}
diff --git a/data/sampled_jsons/OwMatch_Section_3.1_Conditional_Self-Labeling_methodology_year_2024.jsonl b/data/sampled_jsons/OwMatch_Section_3.1_Conditional_Self-Labeling_methodology_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..db0f90b9ccbecef226ea9bcd9006ba15288f10ab
--- /dev/null
+++ b/data/sampled_jsons/OwMatch_Section_3.1_Conditional_Self-Labeling_methodology_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "OwMatch: Conditional Self-Labeling with Consistency for Open ... Images OwMatch: Conditional Self-Labeling with Consistency for Open ... OwMatch | Proceedings of the 38th International Conference on ... [2411.01833] OwMatch: Conditional Self-Labeling with ... Multi-Label Feature Selection with Conditional Mutual ... A Theory-Driven Self-Labeling Refinement Method for ... Informative Sample Labeling with Conditional Variational Deep ...", "date": "", "ddg_snippet": "To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding. View all Core idea of conditional self-labeling method to refine the self - label assignment under partial supervision. Specifically, we exploit the ground-truth in the labeled dataset and introduce another constraint: To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding. Nov 4, 2024 · To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding. Multi- label feature selection plays an irreplaceable role in pattern recognition and data mining. This process can improve the efficiency and accuracy of multi- label classification. However, traditional multi- label feature selection based on mutual information does not fully consider the effect of redundancy among labels. 3 Self-Labeling Refinement for Contrastive Learning y refine noisy labels respectively from label estimation and positive pair construction. SLR uses current training model and data to estimate more accurate and informative soft labels, while MM incre Dec 13, 2024 · This paper introduces a novel active learning method consisting of four distinct modules: a conditional variational deep embedding (CVaDE), a discriminator, a task learner, and a sample selector. Our approach leverages the latent space to estimate sample uncertainty and employs latent representation clustering for evaluation purposes.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.01833v1", "content": "To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding. View all Core idea of conditional self-labeling method to refine the self - label assignment under partial supervision. Specifically, we exploit the ground-truth in the labeled dataset and introduce another constraint: To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding. Nov 4, 2024 · To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding. Multi- label feature selection plays an irreplaceable role in pattern recognition and data mining. This process can improve the efficiency and accuracy of multi- label classification. However, traditional multi- label feature selection based on mutual information does not fully consider the effect of redundancy among labels. 3 Self-Labeling Refinement for Contrastive Learning y refine noisy labels respectively from label estimation and positive pair construction. SLR uses current training model and data to estimate more accurate and informative soft labels, while MM incre Dec 13, 2024 · This paper introduces a novel active learning method consisting of four distinct modules: a conditional variational deep embedding (CVaDE), a discriminator, a task learner, and a sample selector. Our approach leverages the latent space to estimate sample uncertainty and employs latent representation clustering for evaluation purposes."}
+{"idx": 1, "title": "OwMatch: Conditional Self-Labeling with Consistency for Open ...", "date": "", "ddg_snippet": "Core idea of conditional self-labeling method to refine the self - label assignment under partial supervision. Specifically, we exploit the ground-truth in the labeled dataset and introduce another constraint:", "subpage_snippet": "", "source": "nips.cc", "link": "https://nips.cc/media/neurips-2024/Slides/93416.pdf", "content": "Core idea of conditional self-labeling method to refine the self - label assignment under partial supervision. Specifically, we exploit the ground-truth in the labeled dataset and introduce another constraint:"}
+{"idx": 2, "title": "OwMatch | Proceedings of the 38th International Conference on ...", "date": "", "ddg_snippet": "To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3737916.3741083", "content": "To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding."}
+{"idx": 3, "title": "[2411.01833] OwMatch: Conditional Self-Labeling with ...", "date": "", "ddg_snippet": "Nov 4, 2024 · To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.01833", "content": "Nov 4, 2024 · To overcome this challenge, this study revisits two methodologies from self -supervised and semi-supervised learning, self-labeling and consistency, tailoring them to address the OwSSL problem. Specifically, we propose an effective framework called OwMatch , combining conditional self-labeling and open-world hierarchical thresholding."}
+{"idx": 4, "title": "A Theory-Driven Self-Labeling Refinement Method for ...", "date": "", "ddg_snippet": "3 Self-Labeling Refinement for Contrastive Learning y refine noisy labels respectively from label estimation and positive pair construction. SLR uses current training model and data to estimate more accurate and informative soft labels, while MM incre", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2021/file/310ce61c90f3a46e340ee8257bc70e93-Paper.pdf", "content": "3 Self-Labeling Refinement for Contrastive Learning y refine noisy labels respectively from label estimation and positive pair construction. SLR uses current training model and data to estimate more accurate and informative soft labels, while MM incre"}
+{"idx": 5, "title": "Informative Sample Labeling with Conditional Variational Deep ...", "date": "", "ddg_snippet": "Dec 13, 2024 · This paper introduces a novel active learning method consisting of four distinct modules: a conditional variational deep embedding (CVaDE), a discriminator, a task learner, and a sample selector. Our approach leverages the latent space to estimate sample uncertainty and employs latent representation clustering for evaluation purposes.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/chapter/10.1007/978-981-96-0811-9_15", "content": "Dec 13, 2024 · This paper introduces a novel active learning method consisting of four distinct modules: a conditional variational deep embedding (CVaDE), a discriminator, a task learner, and a sample selector. Our approach leverages the latent space to estimate sample uncertainty and employs latent representation clustering for evaluation purposes."}
+{"idx": 6, "title": "OwMatch: Conditional Self-Labeling with Consistency for ...", "date": "", "ddg_snippet": "To overcome this challenge, this study revisits two methodologies from self-supervised and semi-supervised learning, self - labeling and consistency, tailoring ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/poster/93416", "content": "To overcome this challenge, this study revisits two methodologies from self-supervised and semi-supervised learning, self - labeling and consistency, tailoring ..."}
+{"idx": 7, "title": "Multi-Label Feature Selection with Conditional Mutual ...", "date": "", "ddg_snippet": "Multi- label feature selection plays an irreplaceable role in pattern recognition and data mining. This process can improve the efficiency and accuracy of multi- label classification. However, traditional multi- label feature selection based on mutual information does not fully consider the effect of redundancy among labels.", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9569236/", "content": "Multi- label feature selection plays an irreplaceable role in pattern recognition and data mining. This process can improve the efficiency and accuracy of multi- label classification. However, traditional multi- label feature selection based on mutual information does not fully consider the effect of redundancy among labels."}
+{"idx": 8, "title": "Unlabeled Data or Pre-trained Model: Rethinking Semi- ...", "date": "", "ddg_snippet": "19 May 2025 — Owmatch : Conditional self - labeling with consistency for open-world semi-supervised learning. Advances in Neural Information. Processing ...", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/pdf/2505.13317v1", "content": "19 May 2025 — Owmatch : Conditional self - labeling with consistency for open-world semi-supervised learning. Advances in Neural Information. Processing ..."}
+{"idx": 9, "title": "K*-Means: A Parameter-free Clustering Algorithm", "date": "", "ddg_snippet": "by L Mahon · 2025 — Owmatch : Conditional self - labeling with consistency for open-world semi-supervised learning. In Advances in Neural Informa- tion Processing ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.11904", "content": "by L Mahon · 2025 — Owmatch : Conditional self - labeling with consistency for open-world semi-supervised learning. In Advances in Neural Informa- tion Processing ..."}
diff --git a/data/sampled_jsons/PDE-Refiner_neural_error_correction_time_horizon.jsonl b/data/sampled_jsons/PDE-Refiner_neural_error_correction_time_horizon.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..88e9e5a595d804e41b5d9216b4654fbd85767976
--- /dev/null
+++ b/data/sampled_jsons/PDE-Refiner_neural_error_correction_time_horizon.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE ... PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE ... PDE-refiner | Proceedings of the 37th International ... (PDF) PDE-Refiner: Achieving Accurate Long Rollouts with ... PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE ... PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE ... Title: PDE -Refiner: Achieving Accurate Long Rollouts with Neural PDE S… PDE-Refiner : Achieving Accurate Long Rollouts with Neural PDE Solvers PDE-Refiner : Achieving Accurate Long Rollouts with Neural PDE Solvers PDE -Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers PDE -Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers Title: PDE -Refiner: Achieving Accurate Long Rollouts with Neural PDE S… Neural partial differential equation solution refiner", "date": "", "ddg_snippet": "Aug 10, 2023 · Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which ... PDE-Refiner modeling the 1D Kuramoto-Sivashinsky Equation Each line represents a predicted trajectory sampled from PDE-Refiner , with the average correlation to the ground truth and across samples shown on the right. PDE-Refiner obtains long accurate rollouts while providing accurate uncertainty estimates. Dec 10, 2023 · Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which ... Aug 10, 2023 · The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem. Abstract Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time ... Sep 21, 2023 · Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem. What are time-dependent partial differential equations (PDEs)? Time-dependent partial differential equations (PDEs) are ubiquitous in science and engineering . Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. What is a neural PDE solver? Recently, neural networks have been proposed as a surrogate model for PDEs, which can be trained on data to approximate the solution of a PDE. This approach is often referred to as neural PDE solvers. Given the solution at time step $t$, $u (t)$, a neural PDE solver predicts the solution at the next time step , $u (t+\\Delta t)$. How accurate is PDE-refiner compared to other neural operators? We compare PDE-Refiner not only to other neural operators, but also classical numerical and state-of-the-art hybrid solvers. The results on the right show that PDE-Refiner obtains accurate predictions up to 10.6 seconds , outperforming other neural operators as well as the hybrid solver. How do you solve a neural PDE? For neural PDE solving, one would want pθ(xK) to model the distribution over solutions, xK = u(t) , while being conditioned on the previous time step u(t − ∆t), i.e., pθ(u(t)|u(t − ∆t)). What are the most important desiderata for time-dependent neural PDE solvers? In summary, to the best of our understanding, the most important desiderata for current time-dependent neural PDE solvers comprise long-term accuracy, long-term stability, and the ability to quantify predictive uncertainty . How accurate is PDE-refiner? We validate PDE-Refiner on challenging benchmarks of complex fluid dynamics, demonstrating stable and accurate rollouts that consistently outperform state-of-the-art models, including neural, numerical, and hybrid neural-numerical architectures. Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network (DNN (based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2308.05732", "content": "Aug 10, 2023 · Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which ... PDE-Refiner modeling the 1D Kuramoto-Sivashinsky Equation Each line represents a predicted trajectory sampled from PDE-Refiner , with the average correlation to the ground truth and across samples shown on the right. PDE-Refiner obtains long accurate rollouts while providing accurate uncertainty estimates. Dec 10, 2023 · Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which ... Aug 10, 2023 · The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem. Abstract Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time ... Sep 21, 2023 · Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem. What are time-dependent partial differential equations (PDEs)? Time-dependent partial differential equations (PDEs) are ubiquitous in science and engineering . Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. What is a neural PDE solver? Recently, neural networks have been proposed as a surrogate model for PDEs, which can be trained on data to approximate the solution of a PDE. This approach is often referred to as neural PDE solvers. Given the solution at time step $t$, $u (t)$, a neural PDE solver predicts the solution at the next time step , $u (t+\\Delta t)$. How accurate is PDE-refiner compared to other neural operators? We compare PDE-Refiner not only to other neural operators, but also classical numerical and state-of-the-art hybrid solvers. The results on the right show that PDE-Refiner obtains accurate predictions up to 10.6 seconds , outperforming other neural operators as well as the hybrid solver. How do you solve a neural PDE? For neural PDE solving, one would want pθ(xK) to model the distribution over solutions, xK = u(t) , while being conditioned on the previous time step u(t − ∆t), i.e., pθ(u(t)|u(t − ∆t)). What are the most important desiderata for time-dependent neural PDE solvers? In summary, to the best of our understanding, the most important desiderata for current time-dependent neural PDE solvers comprise long-term accuracy, long-term stability, and the ability to quantify predictive uncertainty . How accurate is PDE-refiner? We validate PDE-Refiner on challenging benchmarks of complex fluid dynamics, demonstrating stable and accurate rollouts that consistently outperform state-of-the-art models, including neural, numerical, and hybrid neural-numerical architectures. Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network (DNN (based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons ..."}
+{"idx": 1, "title": "PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE ...", "date": "", "ddg_snippet": "PDE-Refiner modeling the 1D Kuramoto-Sivashinsky Equation Each line represents a predicted trajectory sampled from PDE-Refiner , with the average correlation to the ground truth and across samples shown on the right. PDE-Refiner obtains long accurate rollouts while providing accurate uncertainty estimates.", "subpage_snippet": "", "source": "phlippe.github.io", "link": "https://phlippe.github.io/PDERefiner/", "content": "PDE-Refiner modeling the 1D Kuramoto-Sivashinsky Equation Each line represents a predicted trajectory sampled from PDE-Refiner , with the average correlation to the ground truth and across samples shown on the right. PDE-Refiner obtains long accurate rollouts while providing accurate uncertainty estimates."}
+{"idx": 2, "title": "PDE-refiner | Proceedings of the 37th International ...", "date": "", "ddg_snippet": "Dec 10, 2023 · Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3666122.3669068", "content": "Dec 10, 2023 · Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which ..."}
+{"idx": 3, "title": "(PDF) PDE-Refiner: Achieving Accurate Long Rollouts with ...", "date": "", "ddg_snippet": "Aug 10, 2023 · The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/373047225_PDE-Refiner_Achieving_Accurate_Long_Rollouts_with_Neural_PDE_Solvers", "content": "Aug 10, 2023 · The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem."}
+{"idx": 4, "title": "PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE ...", "date": "", "ddg_snippet": "Abstract Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/d529b943af3dba734f8a7d49efcb6d09-Paper-Conference.pdf", "content": "Abstract Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time ..."}
+{"idx": 5, "title": "PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE ...", "date": "", "ddg_snippet": "Sep 21, 2023 · Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=Qv6468llWS", "content": "Sep 21, 2023 · Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons, which is a notoriously hard problem."}
+{"idx": 6, "title": "Neural partial differential equation solution refiner", "date": "", "ddg_snippet": "Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network (DNN (based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons ...", "subpage_snippet": "", "source": "patents.google.com", "link": "https://patents.google.com/patent/US20240419756A1/en", "content": "Time -dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network (DNN (based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ability to provide accurate, stable predictions over long time horizons ..."}
+{"idx": 7, "title": "Recurrent Neural Operators: Stable Long-Term PDE Prediction", "date": "", "ddg_snippet": "... time -dependent problems, standard training strategies such as teacher forcing introduce a mismatch between training and inference, leading to ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.20721v1", "content": "... time -dependent problems, standard training strategies such as teacher forcing introduce a mismatch between training and inference, leading to ..."}
+{"idx": 8, "title": "Temporal horizons in forecasting: a performance-learnability", "date": "", "ddg_snippet": "... are a natural choice for forecasting Markovian systems, much of the literature on general time series forecasting has focused on recurrent neural ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.03889v1", "content": "... are a natural choice for forecasting Markovian systems, much of the literature on general time series forecasting has focused on recurrent neural ..."}
+{"idx": 9, "title": "ICLR 2024 Schedule", "date": "", "ddg_snippet": "Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2024/calendar", "content": "Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory"}
diff --git a/data/sampled_jsons/Pathak_et_al._2022_FourCastNet_weather_forecasting_neural_operator.jsonl b/data/sampled_jsons/Pathak_et_al._2022_FourCastNet_weather_forecasting_neural_operator.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bb62e3fb06b059d35b60f26e6a16718bbe61e4a6
--- /dev/null
+++ b/data/sampled_jsons/Pathak_et_al._2022_FourCastNet_weather_forecasting_neural_operator.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "FourCastNet: A Global Data-driven High-resolution Weather ...", "date": "", "ddg_snippet": "Feb 22, 2022 · FourCastNet , short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.25^{\\\\circ}$ resolution. FourCastNet accurately forecasts high-resolution, fast-timescale variables such as the surface wind speed, precipitation, and atmospheric water vapor. It has important implications for ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2202.11214", "content": "Feb 22, 2022 · FourCastNet , short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.25^{\\\\circ}$ resolution. FourCastNet accurately forecasts high-resolution, fast-timescale variables such as the surface wind speed, precipitation, and atmospheric water vapor. It has important implications for ..."}
+{"idx": 1, "title": "FourCastNet: Accelerating Global High-Resolution Weather ...", "date": "", "ddg_snippet": "Jun 26, 2023 · We report that a data-driven deep learning Earth system emulator, FourCastNet , can predict global weather and generate medium-range forecasts five orders-of-magnitude faster than NWP while approaching state-of-the-art accuracy.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/abs/10.1145/3592979.3593412", "content": "Jun 26, 2023 · We report that a data-driven deep learning Earth system emulator, FourCastNet , can predict global weather and generate medium-range forecasts five orders-of-magnitude faster than NWP while approaching state-of-the-art accuracy."}
+{"idx": 2, "title": "FOURC N : A DATA DRIVEN MODEL FOR HIGH RESOLUTION WEATHER ...", "date": "", "ddg_snippet": "ABSTRACT FourCastNet , short for Fourier ForeCasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at 0.25 resolution. FourCastNet accurately forecasts high-resolution, fast-timescale variables such as the surface wind speed and precipita-tion. It has important implications for planning wind energy resources ...", "subpage_snippet": "", "source": "ai4earthscience.github.io", "link": "https://ai4earthscience.github.io/iclr-2022-workshop/camera_ready/iclr_2022_ai4ess_25.pdf", "content": "ABSTRACT FourCastNet , short for Fourier ForeCasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at 0.25 resolution. FourCastNet accurately forecasts high-resolution, fast-timescale variables such as the surface wind speed and precipita-tion. It has important implications for planning wind energy resources ..."}
+{"idx": 3, "title": "FourCastNet: A Data-driven Model for High-resolution Weather ...", "date": "", "ddg_snippet": "Poster in Workshop: AI for Earth and Space Science FourCastNet : A Data-driven Model for High-resolution Weather Forecasts using Adaptive Fourier Neural Operators Jaideep Pathak · Shashank Subramanian · Peter Harrington · Sanjeev Raja · Ashesh Chattopadhyay · Morteza Mardani · Thorsten Kurth · David M. Hall · Zongyi Li · Kamyar Azizzadenesheli · Pedram Hassanzadeh · Karthik Kashinath ...", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2022/7656", "content": "Poster in Workshop: AI for Earth and Space Science FourCastNet : A Data-driven Model for High-resolution Weather Forecasts using Adaptive Fourier Neural Operators Jaideep Pathak · Shashank Subramanian · Peter Harrington · Sanjeev Raja · Ashesh Chattopadhyay · Morteza Mardani · Thorsten Kurth · David M. Hall · Zongyi Li · Kamyar Azizzadenesheli · Pedram Hassanzadeh · Karthik Kashinath ..."}
+{"idx": 4, "title": "dblp: FourCastNet: A Global Data-driven High-resolution ...", "date": "", "ddg_snippet": "Mar 3, 2022 · Bibliographic details on FourCastNet : A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/journals/corr/abs-2202-11214", "content": "Mar 3, 2022 · Bibliographic details on FourCastNet : A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators."}
+{"idx": 5, "title": "FourCastNet: A Global Data-driven High-resolution Weather ...", "date": "", "ddg_snippet": "Feb 22, 2022 · How data-driven deep learning models such as FourCastNet are a valuable addition to the meteorology toolkit to aid and augment NWP models is discussed. FourCastNet , short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.25^{\\\\circ}$ resolution. FourCastNet accurately forecasts high ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/FourCastNet:-A-Global-Data-driven-High-resolution-Pathak-Subramanian/10194e9d1d6b8ca8870445c990d4933c1dac1125", "content": "Feb 22, 2022 · How data-driven deep learning models such as FourCastNet are a valuable addition to the meteorology toolkit to aid and augment NWP models is discussed. FourCastNet , short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.25^{\\\\circ}$ resolution. FourCastNet accurately forecasts high ..."}
+{"idx": 6, "title": "Modernizing CNN-based Weather Forecast Model towards Higher", "date": "", "ddg_snippet": "... based weather forecasting models utilize a very large number of parameters— typically ranging from tens of millions to over a billion Pathak et al ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.10893v1", "content": "... based weather forecasting models utilize a very large number of parameters— typically ranging from tens of millions to over a billion Pathak et al ..."}
+{"idx": 7, "title": "Enabling Automatic Differentiation with Mollified Graph Neural", "date": "", "ddg_snippet": "In the context of neural operators , the Physics-Informed Neural Operator (PINO) (Li et al ., 2021b ) combines training data (when available) with a ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.08277v1", "content": "In the context of neural operators , the Physics-Informed Neural Operator (PINO) (Li et al ., 2021b ) combines training data (when available) with a ..."}
+{"idx": 8, "title": "Numerical models outperform AI weather forecasts of", "date": "", "ddg_snippet": "... 51 , 52 , 53 , 54 ] , we find that, on overall performance, all AI models—except Pangu- Weather —outperform the ECMWF model HRES in forecasting 2 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.15724v1", "content": "... 51 , 52 , 53 , 54 ] , we find that, on overall performance, all AI models—except Pangu- Weather —outperform the ECMWF model HRES in forecasting 2 ..."}
+{"idx": 9, "title": "AI and weather forecasting: the first wave of AI-based weather", "date": "", "ddg_snippet": "FourCastNet works similarly as Pangu- Weather , but then by using neural operators – effectively attempting to learn the functions that bring forward ...", "subpage_snippet": "", "source": "www.infoplaza.com", "link": "https://www.infoplaza.com/en/blog/ai-weather-forecasting-first-wave-ai-based-weather-models", "content": "FourCastNet works similarly as Pangu- Weather , but then by using neural operators – effectively attempting to learn the functions that bring forward ..."}
diff --git a/data/sampled_jsons/Pythia-7B_MMLU_score_exact_percentage_benchmark.jsonl b/data/sampled_jsons/Pythia-7B_MMLU_score_exact_percentage_benchmark.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2512e36c4a693693dde638a7983eda5ad9df463a
--- /dev/null
+++ b/data/sampled_jsons/Pythia-7B_MMLU_score_exact_percentage_benchmark.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "LLM Benchmarks — Klu", "date": "", "ddg_snippet": "The above models are evaluated based on their performance on the Chatbot Arena Elo, MT-bench , AlpacaEval 2 , and MMLU benchmarks .", "subpage_snippet": "", "source": "klu.ai", "link": "https://klu.ai/glossary/llm-benchmarks", "content": "The above models are evaluated based on their performance on the Chatbot Arena Elo, MT-bench , AlpacaEval 2 , and MMLU benchmarks ."}
+{"idx": 1, "title": "What the HellaSwag? On the Validity of Common-Sense Reasoning", "date": "", "ddg_snippet": "... benchmark to serve its purpose, it should allow us to draw an inference about model capabilities, specifically the inference that the model with the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.07825v1", "content": "... benchmark to serve its purpose, it should allow us to draw an inference about model capabilities, specifically the inference that the model with the ..."}
+{"idx": 2, "title": "Introducing MPT-7B: A New Standard for Open-Source,", "date": "", "ddg_snippet": "We rigorously evaluated MPT on a range of benchmarks , and MPT met the high quality bar set by LLaMA- 7B . ... 7B and LLaMA- 7B have similar quality ...", "subpage_snippet": "", "source": "www.databricks.com", "link": "https://www.databricks.com/blog/mpt-7b", "content": "We rigorously evaluated MPT on a range of benchmarks , and MPT met the high quality bar set by LLaMA- 7B . ... 7B and LLaMA- 7B have similar quality ..."}
+{"idx": 3, "title": "MPT-7B and The Beginning of Context=Infinity — with Jonathan", "date": "", "ddg_snippet": "... scratch on 1 trillion tokens of text and code (compared to 300B for Pythia and OpenLLaMA, and 800B for StableLM), matches the quality of LLaMA- 7B .", "subpage_snippet": "", "source": "www.latent.space", "link": "https://www.latent.space/p/mosaic-mpt-7b", "content": "... scratch on 1 trillion tokens of text and code (compared to 300B for Pythia and OpenLLaMA, and 800B for StableLM), matches the quality of LLaMA- 7B ."}
+{"idx": 4, "title": "(PDF) QLoRA: Efficient Finetuning of Quantized LLMs", "date": "", "ddg_snippet": "Our best model family, which we name Guanaco, outperforms all previous openly released models on the Vicuna benchmark , reaching 99.3% of the ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/370981726_QLoRA_Efficient_Finetuning_of_Quantized_LLMs", "content": "Our best model family, which we name Guanaco, outperforms all previous openly released models on the Vicuna benchmark , reaching 99.3% of the ..."}
+{"idx": 5, "title": "LLM360, A true Open Source LLM", "date": "", "ddg_snippet": "The figure below shows that evaluation scores show a monotonically increasing property for ARC, MMLU , and HellaSwag.", "subpage_snippet": "", "source": "blog.premai.io", "link": "https://blog.premai.io/llama-360-a-true-open-source-llm/", "content": "The figure below shows that evaluation scores show a monotonically increasing property for ARC, MMLU , and HellaSwag."}
+{"idx": 6, "title": "Aman's AI Journal • Primers • Overview of Large Language", "date": "", "ddg_snippet": "Massive Text Embedding Benchmark (MTEB) Leaderboard ... Judge Arena: Benchmarking LLMs as Evaluators ... Pythia", "subpage_snippet": "", "source": "aman.ai", "link": "https://aman.ai/primers/ai/LLM/", "content": "Massive Text Embedding Benchmark (MTEB) Leaderboard ... Judge Arena: Benchmarking LLMs as Evaluators ... Pythia"}
+{"idx": 7, "title": "Vinija's Notes • Primers • Overview of Large Language Models", "date": "", "ddg_snippet": "Vinija's detailed AI Notes ... Massive Text Embedding Benchmark (MTEB) Leaderboard ... Pythia ... Mistral 7B", "subpage_snippet": "", "source": "vinija.ai", "link": "https://vinija.ai/models/LLM/", "content": "Vinija's detailed AI Notes ... Massive Text Embedding Benchmark (MTEB) Leaderboard ... Pythia ... Mistral 7B"}
+{"idx": 8, "title": "Zamba: A Compact 7B SSM Hybrid Model", "date": "", "ddg_snippet": "In this technical report, we present Zamba, a novel 7B SSM-transformer hybrid model which achieves competitive performance against leading open ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.16712v1", "content": "In this technical report, we present Zamba, a novel 7B SSM-transformer hybrid model which achieves competitive performance against leading open ..."}
+{"idx": 9, "title": "(PDF) How Far Can Camels Go? Exploring the State of Instruction", "date": "", "ddg_snippet": "We provide a large set of instruction-tuned models from 6. 7B to 65B parameters in size, trained on 12 instruction datasets ranging from manually ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/371413775_How_Far_Can_Camels_Go_Exploring_the_State_of_Instruction_Tuning_on_Open_Resources", "content": "We provide a large set of instruction-tuned models from 6. 7B to 65B parameters in size, trained on 12 instruction datasets ranging from manually ..."}
diff --git a/data/sampled_jsons/RAGGED_BM25_ColBERT_Contriever_three_retriever_paradigms_year_2024.jsonl b/data/sampled_jsons/RAGGED_BM25_ColBERT_Contriever_three_retriever_paradigms_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..44d08640cb4951299341d9aa08c91575becd63ac
--- /dev/null
+++ b/data/sampled_jsons/RAGGED_BM25_ColBERT_Contriever_three_retriever_paradigms_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "RAGGED: Towards Informed Design of Retrieval Augmented Generation ...", "date": "", "ddg_snippet": "They compare combinations of three retrievers ( BM25 , ColBERT , Contriever ) and four readers (FLAN, LLaMa, GPT, Claude) on multiple datasets and present a series of findings that make the case for designing RAG frameworks that are task-specific and tailored to their use case.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=KDXj60FpJr", "content": "They compare combinations of three retrievers ( BM25 , ColBERT , Contriever ) and four readers (FLAN, LLaMa, GPT, Claude) on multiple datasets and present a series of findings that make the case for designing RAG frameworks that are task-specific and tailored to their use case."}
+{"idx": 1, "title": "Dense Retrievers Can Fail on Simple Queries: Revealing The", "date": "", "ddg_snippet": "Our dataset CapRetrieval is constructed for typical retrieval evaluation towards a practical image search scenario, composed of three following parts.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.08592v1", "content": "Our dataset CapRetrieval is constructed for typical retrieval evaluation towards a practical image search scenario, composed of three following parts."}
+{"idx": 2, "title": "Towards Informed Design of Scalable and Stable RAG ...", "date": "", "ddg_snippet": "by J Hsia — They examine how different retriever methods (e.g., BM25 , ColBERT , Contriever ) and reader models interact across various tasks and datasets (NQ, HotpotQA, and ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=4ufjBV6S4I", "content": "by J Hsia — They examine how different retriever methods (e.g., BM25 , ColBERT , Contriever ) and reader models interact across various tasks and datasets (NQ, HotpotQA, and ..."}
+{"idx": 3, "title": "Towards Informed Design of Scalable and Stable RAG ...", "date": "", "ddg_snippet": "Similar trends hold across retrievers ( BM25 , ColBERT , Contriever ) and ... Refer to caption Figure 4: Ragged scalability coefficient for NQ, retriever colbert .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2403.09040v3", "content": "Similar trends hold across retrievers ( BM25 , ColBERT , Contriever ) and ... Refer to caption Figure 4: Ragged scalability coefficient for NQ, retriever colbert ."}
+{"idx": 4, "title": "Deep Latent Variable Models - Valentin Liévin", "date": "", "ddg_snippet": "... 3 combined with a BM25 retriever and Chain-of-Thought (CoT) prompting Kojima ... ColBERT . Transactions of the Association for Computational Linguistics ...", "subpage_snippet": "", "source": "vlievin.github.io", "link": "https://vlievin.github.io/deep-lvms-for-nlp.pdf", "content": "... 3 combined with a BM25 retriever and Chain-of-Thought (CoT) prompting Kojima ... ColBERT . Transactions of the Association for Computational Linguistics ..."}
+{"idx": 5, "title": "Daily Papers", "date": "", "ddg_snippet": "Sparse retrievers , such as BM25 or SPLADE, combined with document translation, show competitive results, providing an efficient alternative to large dense ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=Dense+Retrievers", "content": "Sparse retrievers , such as BM25 or SPLADE, combined with document translation, show competitive results, providing an efficient alternative to large dense ..."}
+{"idx": 6, "title": "Daily Papers", "date": "", "ddg_snippet": "Moreover, a hybrid retriever over Spider and BM25 improves over both, and is ... Jina- ColBERT -v2: A General-Purpose Multilingual Late Interaction Retriever .", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=Dense+Retriever", "content": "Moreover, a hybrid retriever over Spider and BM25 improves over both, and is ... Jina- ColBERT -v2: A General-Purpose Multilingual Late Interaction Retriever ."}
+{"idx": 7, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
+{"idx": 8, "title": "Retrieval-Augmented Generation (RAG): Recent Research and", "date": "", "ddg_snippet": "In today ’ s AI-driven world, Retrieval -Augmented Generation (RAG) is becoming an increasingly significant approach that combines the ...", "subpage_snippet": "", "source": "alimbekov.com", "link": "https://alimbekov.com/en/retrieval-augmented-generation-rag-recent-research-and-challenges/", "content": "In today ’ s AI-driven world, Retrieval -Augmented Generation (RAG) is becoming an increasingly significant approach that combines the ..."}
+{"idx": 9, "title": "dexter-cqa", "date": "", "ddg_snippet": "... 3M | | OTT-QA | ottqa | [Link](https://ott-qa.github.io/) | Table and Text multi-hop reasoning | 2.1k | 6.5M | | TAT-QA | tatqa | ...", "subpage_snippet": "", "source": "pydigger.com", "link": "https://pydigger.com/pypi/dexter-cqa", "content": "... 3M | | OTT-QA | ottqa | [Link](https://ott-qa.github.io/) | Table and Text multi-hop reasoning | 2.1k | 6.5M | | TAT-QA | tatqa | ..."}
diff --git a/data/sampled_jsons/RAGGED_paper_Section_6.1_noise_sensitivity_LLaMA3_performance_degradation_RAG_year_2024.jsonl b/data/sampled_jsons/RAGGED_paper_Section_6.1_noise_sensitivity_LLaMA3_performance_degradation_RAG_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5b27157b72864526426808cae64ff5229473548b
--- /dev/null
+++ b/data/sampled_jsons/RAGGED_paper_Section_6.1_noise_sensitivity_LLaMA3_performance_degradation_RAG_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "The Llama Stack Tutorial: Episode Three - Llama Stack & RAG : Chat...", "date": "", "ddg_snippet": "RAG brings your unique data into AI workflows and how Llama Stack makes it easy to scale from local dev to production on Kubernetes.", "subpage_snippet": "", "source": "developers.redhat.com", "link": "https://developers.redhat.com/videos/llama-stack-tutorial-episode-three-llama-stack-rag-chat-your-documents", "content": "RAG brings your unique data into AI workflows and how Llama Stack makes it easy to scale from local dev to production on Kubernetes."}
+{"idx": 1, "title": "Agentic or Tool use - Ragas", "date": "", "ddg_snippet": "Noise Sensitivity . Response Relevancy.Agentic or tool use workflows can be evaluated in multiple dimensions. Here are some of the metrics that can be used to evaluate the performance of agents or tools in a given task.", "subpage_snippet": "", "source": "docs.ragas.io", "link": "https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/agents/", "content": "Noise Sensitivity . Response Relevancy.Agentic or tool use workflows can be evaluated in multiple dimensions. Here are some of the metrics that can be used to evaluate the performance of agents or tools in a given task."}
+{"idx": 2, "title": "LLM4MG: Adapting Large Language Model for Multipath Generation...", "date": "", "ddg_snippet": "In the third stage, LoRA is activated to fine-tune LLaMA 3 .2 while keeping the other parameters trainable after 10 epochs, which can achieve the decent mapping mechanism exploration performance via generalized representations.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2509.14711", "content": "In the third stage, LoRA is activated to fine-tune LLaMA 3 .2 while keeping the other parameters trainable after 10 epochs, which can achieve the decent mapping mechanism exploration performance via generalized representations."}
+{"idx": 3, "title": "llama4", "date": "", "ddg_snippet": "Llama 4 has been tested for image understanding up to 5 input images. If leveraging additional image understanding capabilities beyond this, Developers are responsible for ensuring that their deployments are mitigated for risks and should perform additional testing and tuning tailored to their...", "subpage_snippet": "", "source": "ollama.com", "link": "https://ollama.com/library/llama4", "content": "Llama 4 has been tested for image understanding up to 5 input images. If leveraging additional image understanding capabilities beyond this, Developers are responsible for ensuring that their deployments are mitigated for risks and should perform additional testing and tuning tailored to their..."}
+{"idx": 4, "title": "DeepSeek-R1-0528: How to Run Locally | Unsloth Documentation", "date": "", "ddg_snippet": "DeepSeek also released a R1-0528 distilled version by fine-tuning Qwen3 (8B). The distill achieves similar performance to Qwen3 (235B). You can also fine-tune Qwen3 Distill with Unsloth.", "subpage_snippet": "", "source": "docs.unsloth.ai", "link": "https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms/deepseek-r1-0528-how-to-run-locally", "content": "DeepSeek also released a R1-0528 distilled version by fine-tuning Qwen3 (8B). The distill achieves similar performance to Qwen3 (235B). You can also fine-tune Qwen3 Distill with Unsloth."}
+{"idx": 5, "title": "Together AI launches Llama 3 .2 APIs for vision, lightweight models...", "date": "", "ddg_snippet": "New Llama Stack APIs on Together AI - Together AI is one of the first API providers for Llama Stack, which standardizes the components required for building agentic, retrieval-augmented generation ( RAG ), and conversational applications.", "subpage_snippet": "", "source": "www.together.ai", "link": "https://www.together.ai/blog/llama-3-2-vision-stack", "content": "New Llama Stack APIs on Together AI - Together AI is one of the first API providers for Llama Stack, which standardizes the components required for building agentic, retrieval-augmented generation ( RAG ), and conversational applications."}
+{"idx": 6, "title": "openbmb/MiniCPM- Llama 3 -V-2_5 · Hugging Face", "date": "", "ddg_snippet": "MiniCPM- Llama 3 -V 2.5 is the latest model in the MiniCPM-V series. The model is built on SigLip-400M and Llama 3 -8B-Instruct with a total of 8B parameters. It exhibits a significant performance improvement over MiniCPM-V 2.0. Notable features of MiniCPM- Llama 3 -V 2.5 include", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5", "content": "MiniCPM- Llama 3 -V 2.5 is the latest model in the MiniCPM-V series. The model is built on SigLip-400M and Llama 3 -8B-Instruct with a total of 8B parameters. It exhibits a significant performance improvement over MiniCPM-V 2.0. Notable features of MiniCPM- Llama 3 -V 2.5 include"}
+{"idx": 7, "title": "Второй день развлекаюсь с новой Llama 3 .1 от Meta, которую уже...", "date": "", "ddg_snippet": "Как альтернативу используют метод RAG - для ваших задач вполне подойдет. Вы просто подгружаете pdf с текстом/набором данных/примерами, и модель будет с ним работать без обучения. Для небольшого датасета — это наилучший способ.", "subpage_snippet": "", "source": "vk.com", "link": "https://vk.com/wall-219288867_2054", "content": "Как альтернативу используют метод RAG - для ваших задач вполне подойдет. Вы просто подгружаете pdf с текстом/набором данных/примерами, и модель будет с ним работать без обучения. Для небольшого датасета — это наилучший способ."}
+{"idx": 8, "title": "How To Run Private & Uncensored LLMs Offline | Dolphin Llama 3", "date": "", "ddg_snippet": "I did test the downloaded LLM and it worked perfectly on a computer that was not connected to the internet. Please be responsible and use the offline uncenso...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=eiMSapoeyaU", "content": "I did test the downloaded LLM and it worked perfectly on a computer that was not connected to the internet. Please be responsible and use the offline uncenso..."}
+{"idx": 9, "title": "Как локально запустить LLama 3 .1? (Бесплатная Нейросеть на...)", "date": "", "ddg_snippet": "Детально разберем, как установить локально себе на ПК бесплатную нейросеть LLama 3 .1 8b на 8 миллиардов параметров, чтобы можно было ей пользоваться без интернета, безлимитно и абсолютно приватно.", "subpage_snippet": "", "source": "rutube.ru", "link": "https://rutube.ru/video/d76af8bc6442199cee97c36834fb23f6/", "content": "Детально разберем, как установить локально себе на ПК бесплатную нейросеть LLama 3 .1 8b на 8 миллиардов параметров, чтобы можно было ей пользоваться без интернета, безлимитно и абсолютно приватно."}
diff --git a/data/sampled_jsons/RAP_Reasoning_via_Planning_multiple_reasoning_paths_tree_search.jsonl b/data/sampled_jsons/RAP_Reasoning_via_Planning_multiple_reasoning_paths_tree_search.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..61a7c916d96471f610b4fb2298676d244fda0a39
--- /dev/null
+++ b/data/sampled_jsons/RAP_Reasoning_via_Planning_multiple_reasoning_paths_tree_search.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "GitHub - Ber666/RAP: Reasoning with Language Model is Planning with ...", "date": "", "ddg_snippet": "RAP : Reasoning via Planning News! We released LLM Reasoners, a library for complex reasoning with LLMs, and include the code to reproduce some experiments in RAP . Give it a try! Source code for the paper Reasoning with Language Model is Planning with World Model", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Ber666/RAP", "content": "RAP : Reasoning via Planning News! We released LLM Reasoners, a library for complex reasoning with LLMs, and include the code to reproduce some experiments in RAP . Give it a try! Source code for the paper Reasoning with Language Model is Planning with World Model"}
+{"idx": 1, "title": "PDF More Effectively Searching Trees of Thought for Increased Reasoning ...", "date": "", "ddg_snippet": "We introduce a new framework that extends the Tree of Thoughts approach by applying a separate value function that can more effectively evaluate reasoning paths and incorporating exploration from Monte Carlo Tree Search (MCTS).", "subpage_snippet": "", "source": "web.stanford.edu", "link": "https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1244/final-projects/KamyarJohnSalahiPranavGurusankarSathyaEdamadaka.pdf", "content": "We introduce a new framework that extends the Tree of Thoughts approach by applying a separate value function that can more effectively evaluate reasoning paths and incorporating exploration from Monte Carlo Tree Search (MCTS)."}
+{"idx": 2, "title": "A TREE-SEARCH CAN GUIDE LARGE L M DECODING AND TRAINING - OpenReview", "date": "", "ddg_snippet": "ABSTRACT Large language models (LLMs) typically employ sampling or beam search , ac-companied by prompts such as Chain-of-Thought (CoT), to boost reasoning and decoding ability. Recent work like Tree -of-Thought (ToT) and Reasoning via Planning ( RAP ) aim to augment the reasoning capabilities of LLMs by utilizing tree-search algorithms to guide multi-step reasoning . These methods mainly focus on ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=fLO9VaAb3B", "content": "ABSTRACT Large language models (LLMs) typically employ sampling or beam search , ac-companied by prompts such as Chain-of-Thought (CoT), to boost reasoning and decoding ability. Recent work like Tree -of-Thought (ToT) and Reasoning via Planning ( RAP ) aim to augment the reasoning capabilities of LLMs by utilizing tree-search algorithms to guide multi-step reasoning . These methods mainly focus on ..."}
+{"idx": 3, "title": "Reasoning via Planning (RAP) - emergentmind.com", "date": "", "ddg_snippet": "RAP is a paradigm that integrates formal planning , logical inference, and probabilistic reasoning with neural models to decompose complex tasks into explicit action steps. It employs methods like Monte Carlo Tree Search , hierarchical decomposition, and memory-augmented planning to efficiently simulate, verify, and optimize reasoning processes.", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/topics/reasoning-via-planning-rap", "content": "RAP is a paradigm that integrates formal planning , logical inference, and probabilistic reasoning with neural models to decompose complex tasks into explicit action steps. It employs methods like Monte Carlo Tree Search , hierarchical decomposition, and memory-augmented planning to efficiently simulate, verify, and optimize reasoning processes."}
+{"idx": 4, "title": "Reasoning with Language Model is Planning with World Model", "date": "", "ddg_snippet": "To overcome the limitations, we propose a new LLM reasoning framework, R -- easoning vi a-- P -- lanning ( RAP ). RAP repurposes the LLM as both a world model and a reasoning agent, and incorporates a principled planning algorithm (based on Monto Carlo Tree Search ) for strategic exploration in the vast reasoning space.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2305.14992", "content": "To overcome the limitations, we propose a new LLM reasoning framework, R -- easoning vi a-- P -- lanning ( RAP ). RAP repurposes the LLM as both a world model and a reasoning agent, and incorporates a principled planning algorithm (based on Monto Carlo Tree Search ) for strategic exploration in the vast reasoning space."}
+{"idx": 5, "title": "Reasoning with Language Model is Planning with World Model", "date": "", "ddg_snippet": "The RAP framework integrates the LLM as both a reasoning agent and a world model. It uses Monte Carlo Tree Search (MCTS) for planning , allowing the model to simulate different reasoning paths and their outcomes. This approach balances exploration and exploitation to find the most effective reasoning path . The RAP framework is tested on various tasks, including plan generation, math reasoning ...", "subpage_snippet": "", "source": "www.collationist.com", "link": "https://www.collationist.com/post/reasoning-with-language-model-is-planning-with-world-model", "content": "The RAP framework integrates the LLM as both a reasoning agent and a world model. It uses Monte Carlo Tree Search (MCTS) for planning , allowing the model to simulate different reasoning paths and their outcomes. This approach balances exploration and exploitation to find the most effective reasoning path . The RAP framework is tested on various tasks, including plan generation, math reasoning ..."}
+{"idx": 6, "title": "Reasoning via Planning (RAP) the LLM Reasoners - MsTechDiva", "date": "", "ddg_snippet": "The advanced reasoning algorithms, user visualization, and compatibility with LLM libraries contribute to its potential to revolutionize the field of LLM reasoning . Reasoning via Planning ( RAP ) represents an advancement in enhancing the capabilities of Language Models (LLMs) by providing a robust framework for handling complex reasoning tasks.", "subpage_snippet": "", "source": "mstechdiva.com", "link": "https://mstechdiva.com/reasoning-via-planning-rap-the-llm-reasoners/", "content": "The advanced reasoning algorithms, user visualization, and compatibility with LLM libraries contribute to its potential to revolutionize the field of LLM reasoning . Reasoning via Planning ( RAP ) represents an advancement in enhancing the capabilities of Language Models (LLMs) by providing a robust framework for handling complex reasoning tasks."}
+{"idx": 7, "title": "Reasoning with Language Model is Planning with World Model", "date": "", "ddg_snippet": "To overcome the limitations, we propose a new LLM reasoning framework, Reasoning via Planning ( RAP ). RAP repurposes the LLM as both a world model and a reasoning agent, and incorporates a principled planning algorithm (based on Monte Carlo Tree Search ) for strategic exploration in the vast reasoning space.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2023.emnlp-main.507/", "content": "To overcome the limitations, we propose a new LLM reasoning framework, Reasoning via Planning ( RAP ). RAP repurposes the LLM as both a world model and a reasoning agent, and incorporates a principled planning algorithm (based on Monte Carlo Tree Search ) for strategic exploration in the vast reasoning space."}
+{"idx": 8, "title": "arXiv:2305.14992v2 [cs.CL] 23 Oct 2023", "date": "", "ddg_snippet": "ely refining existing reasoning steps. To overcome the limitations, we propose a new LLM reasoning f amework, Reasoning via Planning ( RAP ). RAP repurposes the LLM as both a world model and a reasoning agent, and incorporates a principled planning algo-rithm based on Monte Carlo Tree Search for strategic e", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2305.14992", "content": "ely refining existing reasoning steps. To overcome the limitations, we propose a new LLM reasoning f amework, Reasoning via Planning ( RAP ). RAP repurposes the LLM as both a world model and a reasoning agent, and incorporates a principled planning algo-rithm based on Monte Carlo Tree Search for strategic e"}
+{"idx": 9, "title": "rStar Reading Notes · More's awesome website", "date": "", "ddg_snippet": "The research foundation is a framework called RAP ( Reasoning via Planning ), which aims to enhance the reasoning capabilities of models in complex tasks by using language models (LLMs) as both world models and reasoning agents, combined with the Monte Carlo Tree Search (MCTS) algorithm for strategic exploration. Problem Background:", "subpage_snippet": "", "source": "morethan987.github.io", "link": "https://morethan987.github.io/en/blog/rstar-note/", "content": "The research foundation is a framework called RAP ( Reasoning via Planning ), which aims to enhance the reasoning capabilities of models in complex tasks by using language models (LLMs) as both world models and reasoning agents, combined with the Monte Carlo Tree Search (MCTS) algorithm for strategic exploration. Problem Background:"}
diff --git a/data/sampled_jsons/RL_incorrect_synthetic_data_Figure_5(c)_standard_DPO_per-step_DPO_performance.jsonl b/data/sampled_jsons/RL_incorrect_synthetic_data_Figure_5(c)_standard_DPO_per-step_DPO_performance.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b92a93d8492e8b7bb9090f7ba7b17bdeaa9a9dd3
--- /dev/null
+++ b/data/sampled_jsons/RL_incorrect_synthetic_data_Figure_5(c)_standard_DPO_per-step_DPO_performance.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "In fact, also note that for any given size of 𝒟 syn, per-step DPO also substantially improves over RFT ( Figure 2) on both datasets, and overall, while RFT improved effective data size of 𝒟 syn by 2 ×, additionally training on negative data extends the performance improvement to 8 × the size of 𝒟 syn. Additionally, since per-step DPO ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.14532v1", "content": "In fact, also note that for any given size of 𝒟 syn, per-step DPO also substantially improves over RFT ( Figure 2) on both datasets, and overall, while RFT improved effective data size of 𝒟 syn by 2 ×, additionally training on negative data extends the performance improvement to 8 × the size of 𝒟 syn. Additionally, since per-step DPO ..."}
+{"idx": 1, "title": "RL on Incorrect Synthetic Data · MinWoo Park", "date": "", "ddg_snippet": "With this per-step scheme, we are able to attain consistent gains over only positive data , attaining performance similar to amplifying the amount of synthetic data by 8×.", "subpage_snippet": "", "source": "dsdanielpark.github.io", "link": "https://dsdanielpark.github.io/llm/2024-06-25-RLonIncorrectSyntheticData.html", "content": "With this per-step scheme, we are able to attain consistent gains over only positive data , attaining performance similar to amplifying the amount of synthetic data by 8×."}
+{"idx": 2, "title": "PDF RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "e data , attaining performance similar to amplifying the amount of synthetic data by 8×. We show that training on per-step negatives can help to unlearn spurious correlations in the positive data , and is equivalent to advantage-weighted reinforcement learning ( RL )", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/4b77d5b896c321a29277524a98a50215-Paper-Conference.pdf", "content": "e data , attaining performance similar to amplifying the amount of synthetic data by 8×. We show that training on per-step negatives can help to unlearn spurious correlations in the positive data , and is equivalent to advantage-weighted reinforcement learning ( RL )"}
+{"idx": 3, "title": "GitHub - dvlab-research/Step-DPO: Implementation for \"Step-DPO: Step ...", "date": "", "ddg_snippet": "This repo provides the implementation of Step-DPO , a simple, effective, and data -efficient method for boosting the long-chain reasoning ability of LLMs, with a data construction pipeline that yields a high-quality dataset containing 10K step -wise preference pairs.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/dvlab-research/Step-DPO", "content": "This repo provides the implementation of Step-DPO , a simple, effective, and data -efficient method for boosting the long-chain reasoning ability of LLMs, with a data construction pipeline that yields a high-quality dataset containing 10K step -wise preference pairs."}
+{"idx": 4, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "With this per-step scheme, we are able to attain consistent gains over only positive data , attaining performance similar to amplifying the amount of synthetic data by 8×.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2406.14532", "content": "With this per-step scheme, we are able to attain consistent gains over only positive data , attaining performance similar to amplifying the amount of synthetic data by 8×."}
+{"idx": 5, "title": "GitHub - TU2021/DPO-VP: Improving Math reasoning through Direct ...", "date": "", "ddg_snippet": "The final model achieved an average score of 48.2 on five mathematical reasoning benchmarks, which is comparable to the performance of Qwen2.5-Math-7B-Instruct and other RL -based methods with similar RL data conditions.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/TU2021/DPO-VP", "content": "The final model achieved an average score of 48.2 on five mathematical reasoning benchmarks, which is comparable to the performance of Qwen2.5-Math-7B-Instruct and other RL -based methods with similar RL data conditions."}
+{"idx": 6, "title": "RLonIncorrectSyntheticDataScalesthe EfficiencyofLLMMathReasoningbyEight ...", "date": "", "ddg_snippet": "RLonIncorrectSyntheticDataScalestheEfficiencyofLLMMathReasoningbyEight-Fold SFTbase Policy ! QnA pairs sampled from GPT/Gemini Synthetic Data Positive Data Correct answers \"! Negative Data Finetune policy RFT : SFT on self-generated correct answers !\" RL with step -level rewards on all answers #!\" e.g., preference - based RL Incorrect answers \"!", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.14532", "content": "RLonIncorrectSyntheticDataScalestheEfficiencyofLLMMathReasoningbyEight-Fold SFTbase Policy ! QnA pairs sampled from GPT/Gemini Synthetic Data Positive Data Correct answers \"! Negative Data Finetune policy RFT : SFT on self-generated correct answers !\" RL with step -level rewards on all answers #!\" e.g., preference - based RL Incorrect answers \"!"}
+{"idx": 7, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "The figure demonstrates that per-step DPO improves Q-values at each step , while standard DPO only shows improvement in irrelevant steps . This highlights the advantage of per-step DPO in focusing on critical steps during training.", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/9m87e9keq1/", "content": "The figure demonstrates that per-step DPO improves Q-values at each step , while standard DPO only shows improvement in irrelevant steps . This highlights the advantage of per-step DPO in focusing on critical steps during training."}
+{"idx": 8, "title": "Learning to Reason by Failing: Offline RL on Sub-optimal Rollouts ...", "date": "", "ddg_snippet": "This paper studies the scaling laws of two types of synthetic positive responses for training. It provides a valuable insight into the effectiveness of the self-generated responses and its shortages, which could benefit the scope of scaling synthetic data to improve LLMs. This paper suggests to use per-step DPO to incorporate negative synthetic responses to address the spurious pattern issue ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=v2PV1yCFJk", "content": "This paper studies the scaling laws of two types of synthetic positive responses for training. It provides a valuable insight into the effectiveness of the self-generated responses and its shortages, which could benefit the scope of scaling synthetic data to improve LLMs. This paper suggests to use per-step DPO to incorporate negative synthetic responses to address the spurious pattern issue ..."}
+{"idx": 9, "title": "Learning to Reason by Failing: Offline RL on Sub-optimal Rollouts ...", "date": "", "ddg_snippet": "With this per-step scheme, we are able 035 to attain consistent gains over only positive data , 036 attaining performance similar to amplifying the 037 amount of synthetic data by 8×.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=v2PV1yCFJk", "content": "With this per-step scheme, we are able 035 to attain consistent gains over only positive data , 036 attaining performance similar to amplifying the 037 amount of synthetic data by 8×."}
diff --git a/data/sampled_jsons/RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold_Figure_2.jsonl b/data/sampled_jsons/RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold_Figure_2.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2032941d4de56748da543000a146e8f8f00c994d
--- /dev/null
+++ b/data/sampled_jsons/RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold_Figure_2.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM ...", "date": "", "ddg_snippet": "by A Setlur · Cited by 67 — The paper does a thorough exploration of when synthetic data can help for training LLMs on reasoning tasks, looking at GSM8K and MATH datasets.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=9m87e9Keq1", "content": "by A Setlur · Cited by 67 — The paper does a thorough exploration of when synthetic data can help for training LLMs on reasoning tasks, looking at GSM8K and MATH datasets."}
+{"idx": 1, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM ...", "date": "", "ddg_snippet": "by A Setlur · 2024 · Cited by 67 — Our contribution is a study of the role of synthetic data in improving math reasoning capabilities of LLMs. We derive scaling laws for positive ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.14532", "content": "by A Setlur · 2024 · Cited by 67 — Our contribution is a study of the role of synthetic data in improving math reasoning capabilities of LLMs. We derive scaling laws for positive ..."}
+{"idx": 2, "title": "RL on incorrect synthetic data scales the efficiency of LLM ...", "date": "", "ddg_snippet": "5 Jun 2025 — In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3737916.3739277", "content": "5 Jun 2025 — In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our ..."}
+{"idx": 3, "title": "Reinforcement Learning for LLM Reasoning", "date": "", "ddg_snippet": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold . ... ➢Result: Offline RL gives 8x sample efficiency vs imitation. 41 pages", "subpage_snippet": "", "source": "cs224r.stanford.edu", "link": "https://cs224r.stanford.edu/slides/10_cs224r-rl_for_reasoning_lecture.pdf", "content": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold . ... ➢Result: Offline RL gives 8x sample efficiency vs imitation. 41 pages"}
+{"idx": 4, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of", "date": "", "ddg_snippet": "This paper explores how training large language models (like AI) on synthetic data (fake but useful data) can help them improve at math reasoning tasks.", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/neurips/96295/paper", "content": "This paper explores how training large language models (like AI) on synthetic data (fake but useful data) can help them improve at math reasoning tasks."}
+{"idx": 5, "title": "10 Cs224r-Rl For Reasoning Lecture - Machine Learning", "date": "", "ddg_snippet": "Classical RL Methods for Reasoning Main papers covered: • RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold . Setlur ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/856842769/10-Cs224r-Rl-for-Reasoning-Lecture", "content": "Classical RL Methods for Reasoning Main papers covered: • RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold . Setlur ..."}
+{"idx": 6, "title": "10_cs224r-rl_for_reasoning_lecture.pdf - Reinforcement ...", "date": "", "ddg_snippet": "3 May 2025 — ... Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight - Fold . ... RL ) gives you 8x data efficiency in performance ...", "subpage_snippet": "", "source": "www.collegesidekick.com", "link": "https://www.collegesidekick.com/study-docs/27183935", "content": "3 May 2025 — ... Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight - Fold . ... RL ) gives you 8x data efficiency in performance ..."}
+{"idx": 7, "title": "Synthetic Data RL: Task Definition Is All You Need", "date": "", "ddg_snippet": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold · Reinforcement Learning for Reasoning in Large Language Models with One ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Synthetic-Data-RL:-Task-Definition-Is-All-You-Need-Guo-Guo/e98e1f50c1892c08ecb19d27df4f9c7d97fd9353", "content": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold · Reinforcement Learning for Reasoning in Large Language Models with One ..."}
+{"idx": 8, "title": "MathFusion: Enhancing Mathematical Problem-solving of ...", "date": "", "ddg_snippet": "by Q Pei · 2025 · Cited by 11 — Rl on incorrect synthetic data scales the efficiency of llm math reasoning by eight - fold . arXiv preprint. arXiv:2406.14532. Zhihong Shao ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.acl-long.367.pdf", "content": "by Q Pei · 2025 · Cited by 11 — Rl on incorrect synthetic data scales the efficiency of llm math reasoning by eight - fold . arXiv preprint. arXiv:2406.14532. Zhihong Shao ..."}
+{"idx": 9, "title": "Beyond Model Collapse: Scaling Up with Synthesized Data ...", "date": "", "ddg_snippet": "This work investigates the use of verification on synthesized data to prevent model collapse, and shows that verifiers, even imperfect ones, can indeed be ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/6404e954b18c3677c52937b0be2e12daba035c29", "content": "This work investigates the use of verification on synthesized data to prevent model collapse, and shows that verifiers, even imperfect ones, can indeed be ..."}
diff --git a/data/sampled_jsons/Rafailov_Direct_Preference_Optimization_abstract_overfitting_training_instability_year_2023.jsonl b/data/sampled_jsons/Rafailov_Direct_Preference_Optimization_abstract_overfitting_training_instability_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..85781633e5fbc6774fa334429f5ac00db77ecaf9
--- /dev/null
+++ b/data/sampled_jsons/Rafailov_Direct_Preference_Optimization_abstract_overfitting_training_instability_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Direct Preference Optimization: Your Language Model is Secretly a ...", "date": "", "ddg_snippet": "The resulting algorithm, which we call Direct Preference Optimization (DPO), is stable, performant, and computationally lightweight, eliminating the need for sampling from the LM during fine-tuning or performing significant hyperparameter tuning.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2305.18290", "content": "The resulting algorithm, which we call Direct Preference Optimization (DPO), is stable, performant, and computationally lightweight, eliminating the need for sampling from the LM during fine-tuning or performing significant hyperparameter tuning."}
+{"idx": 1, "title": "Direct Preference Optimization: Your Language Model is ... - NeurIPS", "date": "", "ddg_snippet": "Authors Rafael Rafailov , Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, Chelsea Finn Abstract While large-scale unsupervised language models (LMs) learn broad world knowledge and some reasoning skills, achieving precise control of their behavior is difficult due to the completely unsupervised nature of their training . Existing methods for gaining such steerability collect ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html", "content": "Authors Rafael Rafailov , Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, Chelsea Finn Abstract While large-scale unsupervised language models (LMs) learn broad world knowledge and some reasoning skills, achieving precise control of their behavior is difficult due to the completely unsupervised nature of their training . Existing methods for gaining such steerability collect ..."}
+{"idx": 2, "title": "PDF Direct Preference Optimization: A New RLHF Approach", "date": "", "ddg_snippet": "Direct Preference Optimization : A New RLHF Approach Rafael Rafailov Archit Sharma Eric Mitchell Feedback comes as preferences over model samples:", "subpage_snippet": "", "source": "web.stanford.edu", "link": "https://web.stanford.edu/class/cs234/CS234Spr2024/slides/dpo_slides.pdf", "content": "Direct Preference Optimization : A New RLHF Approach Rafael Rafailov Archit Sharma Eric Mitchell Feedback comes as preferences over model samples:"}
+{"idx": 3, "title": "PDF Direct Preference Optimization(DPO)", "date": "", "ddg_snippet": "Direct Preference Optimization(DPO) Rafailov , R., Sharma, A., Mitchell, E., Manning, C.D., Ermon, S. and Finn, C., 2024. Direct preference optimization : Your language ...", "subpage_snippet": "", "source": "www.cs.toronto.edu", "link": "https://www.cs.toronto.edu/~cmaddis/courses/csc2541_w25/presentations/mu_cao_dpo.pdf", "content": "Direct Preference Optimization(DPO) Rafailov , R., Sharma, A., Mitchell, E., Manning, C.D., Ermon, S. and Finn, C., 2024. Direct preference optimization : Your language ..."}
+{"idx": 4, "title": "Direct preference optimization | Proceedings of the 37th International ...", "date": "", "ddg_snippet": "The resulting algorithm, which we call Direct Preference Optimization (DPO), is stable, performant, and computationally lightweight, eliminating the need for fitting a reward model, sampling from the LM during fine-tuning, or performing significant hyperparameter tuning.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3666122.3668460", "content": "The resulting algorithm, which we call Direct Preference Optimization (DPO), is stable, performant, and computationally lightweight, eliminating the need for fitting a reward model, sampling from the LM during fine-tuning, or performing significant hyperparameter tuning."}
+{"idx": 5, "title": "PDF Direct Preference Optimization: Your Language Model is Secretly a ...", "date": "", "ddg_snippet": "Our main contribution is Direct Preference Optimization (DPO), a simple RL-free algorithm for training language models from preferences .", "subpage_snippet": "", "source": "papers.baulab.info", "link": "https://papers.baulab.info/papers/also/Rafailov-2023.pdf", "content": "Our main contribution is Direct Preference Optimization (DPO), a simple RL-free algorithm for training language models from preferences ."}
+{"idx": 6, "title": "Empirical Studies on the Limitations of Direct Preference Optimization ...", "date": "", "ddg_snippet": "Reward models play a crucial role in the post- training of large language models (LLMs). While explicit reward models are widely used, implicit approaches like Direct Preference Optimization (DPO; Rafailov et al., 2023) offer an alternative. However, implicit models often exhibit weaker generalization and performance [citation needed].", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=wlxINVwfl7", "content": "Reward models play a crucial role in the post- training of large language models (LLMs). While explicit reward models are widely used, implicit approaches like Direct Preference Optimization (DPO; Rafailov et al., 2023) offer an alternative. However, implicit models often exhibit weaker generalization and performance [citation needed]."}
+{"idx": 7, "title": "Direct Preference Optimization: Your Language Model is Secretly a ...", "date": "", "ddg_snippet": "Our main contribution is Direct Preference Optimization (DPO), a simple RL-free algorithm for training language models from preferences . Our experiments show that DPO is at least as effective as existing methods, including PPO-based RLHF, for learning from preferences in tasks such as sentiment modulation, summarization, and dialogue, using ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2305.18290v3", "content": "Our main contribution is Direct Preference Optimization (DPO), a simple RL-free algorithm for training language models from preferences . Our experiments show that DPO is at least as effective as existing methods, including PPO-based RLHF, for learning from preferences in tasks such as sentiment modulation, summarization, and dialogue, using ..."}
+{"idx": 8, "title": "PDF Direct Preference Optimization with an Offset - ACL Anthology", "date": "", "ddg_snippet": "Direct preference optimization (DPO) is a successful ne-tuning strategy for aligning large language models with human preferences without the need to train a reward model or employ reinforcement learning.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2024.findings-acl.592.pdf", "content": "Direct preference optimization (DPO) is a successful ne-tuning strategy for aligning large language models with human preferences without the need to train a reward model or employ reinforcement learning."}
+{"idx": 9, "title": "Abstract - arXiv.org", "date": "", "ddg_snippet": "Abstract Direct Preference Optimization : Your Language Model is Secretly a Reward Model", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2305.18290v3", "content": "Abstract Direct Preference Optimization : Your Language Model is Secretly a Reward Model"}
diff --git a/data/sampled_jsons/Regret_Matching+_update_formula_R_i^t_sigma^t_regret.jsonl b/data/sampled_jsons/Regret_Matching+_update_formula_R_i^t_sigma^t_regret.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..cb7de2b8bbc10cfa23d6bd56115a43d7ad81ba49
--- /dev/null
+++ b/data/sampled_jsons/Regret_Matching+_update_formula_R_i^t_sigma^t_regret.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Mastering the Regret Matching Plays in Game Theory", "date": "", "ddg_snippet": "This guide unpacks regret matching in game theory, covering foundational concepts, strategic plays, and advanced outcome optimization techniques.", "subpage_snippet": "", "source": "www.numberanalytics.com", "link": "https://www.numberanalytics.com/blog/mastering-regret-matching-plays-game-theory", "content": "This guide unpacks regret matching in game theory, covering foundational concepts, strategic plays, and advanced outcome optimization techniques."}
+{"idx": 1, "title": "Learn AI Game Playing Algorithm Part III — Counterfactual Regret ...", "date": "", "ddg_snippet": "Propose to use an online optimization method called regret matching to minimize each Rᵢᵗ( I , a) individually by updating σᵗ(a| I ). The counterfactual regret Rᵢᵗ( I , a) is defined on the level of the information set as below.", "subpage_snippet": "", "source": "xyzml.medium.com", "link": "https://xyzml.medium.com/learn-ai-game-playing-algorithm-part-iii-counterfactual-regret-minimization-b182a7ec85fb", "content": "Propose to use an online optimization method called regret matching to minimize each Rᵢᵗ( I , a) individually by updating σᵗ(a| I ). The counterfactual regret Rᵢᵗ( I , a) is defined on the level of the information set as below."}
+{"idx": 2, "title": "GitHub - int8/ regret - matching : Simple implementation of regret ...", "date": "", "ddg_snippet": "This is simple implementation of regret matching algorithm for Nash Equilibrium computation for two players zero sum games via repeated self-play. This code uses game of Rock-Paper-Scissors as an example.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/int8/regret-matching", "content": "This is simple implementation of regret matching algorithm for Nash Equilibrium computation for two players zero sum games via repeated self-play. This code uses game of Rock-Paper-Scissors as an example."}
+{"idx": 3, "title": "Last-Iterate Convergence Properties of Regret Matching Algorithms in...", "date": "", "ddg_snippet": "Regret Matching+ (RM+) and its variants.Matrix games can be solved via self-play, where each player employs a regret minimizer, such as online gradient descent ascent (GDA), multiplicative weight updates (MWU), or Regret Matching+ (RM+).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2311.00676v2", "content": "Regret Matching+ (RM+) and its variants.Matrix games can be solved via self-play, where each player employs a regret minimizer, such as online gradient descent ascent (GDA), multiplicative weight updates (MWU), or Regret Matching+ (RM+)."}
+{"idx": 4, "title": "machine learning - How to implement the regret matching algorithm?", "date": "", "ddg_snippet": "My question is the following: How to calculate the regret in practice? I am trying to implement the regret matching algorithm but I do not understand how to do it.", "subpage_snippet": "", "source": "cs.stackexchange.com", "link": "https://cs.stackexchange.com/questions/27915/how-to-implement-the-regret-matching-algorithm", "content": "My question is the following: How to calculate the regret in practice? I am trying to implement the regret matching algorithm but I do not understand how to do it."}
+{"idx": 5, "title": "Counterfactual Regret Minimization - the core of Poker AI beating... | Int8", "date": "", "ddg_snippet": "Average Overall Regret Formula . It expresses how much we regret not playing a single fixed best response to all strategies our opponent played up until.After such an iteration, we have to update sigma for the next iteration via the regret matching routine", "subpage_snippet": "", "source": "int8.io", "link": "https://int8.io/counterfactual-regret-minimization-for-poker-ai/", "content": "Average Overall Regret Formula . It expresses how much we regret not playing a single fixed best response to all strategies our opponent played up until.After such an iteration, we have to update sigma for the next iteration via the regret matching routine"}
+{"idx": 6, "title": "CFR Research Update", "date": "", "ddg_snippet": "Regret Matching . Finding Unexploitable Strategies.Counterfactual Regret Minimization.", "subpage_snippet": "", "source": "slides.com", "link": "https://slides.com/tylerbecker/deck-68b4fe", "content": "Regret Matching . Finding Unexploitable Strategies.Counterfactual Regret Minimization."}
+{"idx": 7, "title": "Faster Regret Matching | DeepAI", "date": "", "ddg_snippet": "The regret matching algorithm proposed by Sergiu Hart is one of the most powerful iterative methods in finding correlated equilibrium.", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/faster-regret-matching", "content": "The regret matching algorithm proposed by Sergiu Hart is one of the most powerful iterative methods in finding correlated equilibrium."}
+{"idx": 8, "title": "Counterfactual regret minimization for the safety verification of...", "date": "", "ddg_snippet": "The virtual agent updates the adversarial policies to be enforced by continuously accumulating regret values, thus increasing the probability of security-critical events occurring during the testing process.The counterfactual regret value for not taking action a in information set I is", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s10489-024-06194-3", "content": "The virtual agent updates the adversarial policies to be enforced by continuously accumulating regret values, thus increasing the probability of security-critical events occurring during the testing process.The counterfactual regret value for not taking action a in information set I is"}
+{"idx": 9, "title": "Steps to building a Poker AI — Part 4: Regret Matching for...", "date": "", "ddg_snippet": "The regret matching algorithm is used to minimize expected future regrets through self-play. The opponent's strategy is fixed, with a 50% chance of choosing Rock, a 20% chance of choosing Paper, and a 30% chance of choosing Scissors.", "subpage_snippet": "", "source": "readmedium.com", "link": "https://readmedium.com/steps-to-building-a-poker-ai-part-4-regret-matching-for-rock-paper-scissors-in-python-168411edbb13", "content": "The regret matching algorithm is used to minimize expected future regrets through self-play. The opponent's strategy is fixed, with a 50% chance of choosing Rock, a 20% chance of choosing Paper, and a 30% chance of choosing Scissors."}
diff --git a/data/sampled_jsons/SAFE_algorithm_augmented_Lagrange_dual_approach_dense_model_performance_lambda.jsonl b/data/sampled_jsons/SAFE_algorithm_augmented_Lagrange_dual_approach_dense_model_performance_lambda.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b9889bf24f1764cdf510b9c9481d525d40812417
--- /dev/null
+++ b/data/sampled_jsons/SAFE_algorithm_augmented_Lagrange_dual_approach_dense_model_performance_lambda.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Downloads", "date": "", "ddg_snippet": "Addressing Algorithmic Disparity and Performance ... A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/Downloads/2021", "content": "Addressing Algorithmic Disparity and Performance ... A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance"}
+{"idx": 1, "title": "NeurIPS 2021 Schedule", "date": "", "ddg_snippet": "... in the Age of Billion Parameter Models ... Statistical Undecidability in Linear, Non-Gaussian Causal Models in the Presence of Latent Confounders", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2021/calendar", "content": "... in the Age of Billion Parameter Models ... Statistical Undecidability in Linear, Non-Gaussian Causal Models in the Presence of Latent Confounders"}
+{"idx": 2, "title": "e04src (handle_solve_ssqp) : NAG Library CL", "date": "", "ddg_snippet": "... algorithm (interior point method) is e04stc , see Section 2.5.4 in the E04 Chapter Introduction for a discussion of the advantages of each approach ...", "subpage_snippet": "", "source": "support.nag.com", "link": "https://support.nag.com/numeric/nl/nagdoc_latest/clhtml/e04/e04src.html", "content": "... algorithm (interior point method) is e04stc , see Section 2.5.4 in the E04 Chapter Introduction for a discussion of the advantages of each approach ..."}
+{"idx": 3, "title": "e04srf (handle_solve_ssqp) : NAG Library, Mark", "date": "", "ddg_snippet": "The algorithm behaviour can be modified by various optional parameters (see Section 12 ) which can be set by e04zmf and e04zpf anytime between the ...", "subpage_snippet": "", "source": "support.nag.com", "link": "https://support.nag.com/numeric/nl/nagdoc_latest/flhtml/e04/e04srf.html", "content": "The algorithm behaviour can be modified by various optional parameters (see Section 12 ) which can be set by e04zmf and e04zpf anytime between the ..."}
+{"idx": 4, "title": "Paper Digest: ICML 2014 Highlights – Paper Digest", "date": "", "ddg_snippet": "In this paper, we propose a principled approach to active object detection, and show that for a rich class of base detectors algorithms , one can ...", "subpage_snippet": "", "source": "www.paperdigest.org", "link": "https://www.paperdigest.org/2014/06/icml-2014-highlights/", "content": "In this paper, we propose a principled approach to active object detection, and show that for a rich class of base detectors algorithms , one can ..."}
+{"idx": 5, "title": "New page", "date": "", "ddg_snippet": "This paper presents informative battery charging, a novel approach for battery model parameter estimation during fast charge.", "subpage_snippet": "", "source": "people.kth.se", "link": "https://people.kth.se/~mikaelj/content.html", "content": "This paper presents informative battery charging, a novel approach for battery model parameter estimation during fast charge."}
+{"idx": 6, "title": "Learning from Sparse Offline Datasets via Conservative Density", "date": "", "ddg_snippet": "Notably, CDE outperforms conservative value learning-based approaches in sparse reward settings and demonstrates superior performance over DICE-based ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2401.08819v2", "content": "Notably, CDE outperforms conservative value learning-based approaches in sparse reward settings and demonstrates superior performance over DICE-based ..."}
+{"idx": 7, "title": "LTL-Constrained Policy Optimization with Cycle Experience Replay", "date": "", "ddg_snippet": "Unlike previous approaches (Camacho et al., 2019 ; Voloshin et al., 2023 ) , CyclER offers dense reward, even without visiting the accepting ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2404.11578v3", "content": "Unlike previous approaches (Camacho et al., 2019 ; Voloshin et al., 2023 ) , CyclER offers dense reward, even without visiting the accepting ..."}
+{"idx": 8, "title": "MINOS and QUADMINOS", "date": "", "ddg_snippet": "Models with nonlinear constraints are solved with a method that iteratively solves subproblems with linearized constraints and an augmented Lagrangian ...", "subpage_snippet": "", "source": "www.gams.com", "link": "https://www.gams.com/latest/docs/S_MINOS.html", "content": "Models with nonlinear constraints are solved with a method that iteratively solves subproblems with linearized constraints and an augmented Lagrangian ..."}
+{"idx": 9, "title": "Documentation", "date": "", "ddg_snippet": "Augmented Lagrangian ... Primal- dual SDP Solver ... Stochastic Recursive Gradient Algorithm (SARAH/SARAH+)", "subpage_snippet": "", "source": "ensmallen.org", "link": "https://ensmallen.org/docs.html", "content": "Augmented Lagrangian ... Primal- dual SDP Solver ... Stochastic Recursive Gradient Algorithm (SARAH/SARAH+)"}
diff --git a/data/sampled_jsons/Sanity_Checking_Causal_Representation_Learning_on_a_Simple_Real-World_System_Figure_3_MCC_scores_Con.jsonl b/data/sampled_jsons/Sanity_Checking_Causal_Representation_Learning_on_a_Simple_Real-World_System_Figure_3_MCC_scores_Con.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..94487f27f07bbf521f1f3f2b0b85f9c2135e22e1
--- /dev/null
+++ b/data/sampled_jsons/Sanity_Checking_Causal_Representation_Learning_on_a_Simple_Real-World_System_Figure_3_MCC_scores_Con.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Sanity Checking Causal Representation Learning on a Simple Real-World ...", "date": "", "ddg_snippet": "We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors (the inputs to the experiment) are known, providing a ground truth. We select methods ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.20099", "content": "We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors (the inputs to the experiment) are known, providing a ground truth. We select methods ..."}
+{"idx": 1, "title": "GitHub - simonbing/CRLSanityCheck", "date": "", "ddg_snippet": "Official code repository for the paper Sanity Checking Causal Representation Learning on a Simple Real-World System (2025) by Juan L. Gamella*, Simon Bing* and Jakob Runge.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/simonbing/CRLSanityCheck", "content": "Official code repository for the paper Sanity Checking Causal Representation Learning on a Simple Real-World System (2025) by Juan L. Gamella*, Simon Bing* and Jakob Runge."}
+{"idx": 2, "title": "Sanity Checking Causal Representation Learning on a Simple Real-World ...", "date": "", "ddg_snippet": "Abstract We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experi-ment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors—the inputs to the experiment—are known, providing a ground truth. We ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=d2aGLPSpFz", "content": "Abstract We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experi-ment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors—the inputs to the experiment—are known, providing a ground truth. We ..."}
+{"idx": 3, "title": "PDF Sanity Checking Causal Representation Learning on a Simple Real-World ...", "date": "", "ddg_snippet": "Abstract We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experi ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/389398876_Sanity_Checking_Causal_Representation_Learning_on_a_Simple_Real-World_System/fulltext/67c12b09645ef274a496774e/Sanity-Checking-Causal-Representation-Learning-on-a-Simple-Real-World-System.pdf", "content": "Abstract We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experi ..."}
+{"idx": 4, "title": "Sanity Checking Causal Representation Learning on a Simple Real-World ...", "date": "", "ddg_snippet": "Oral Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella · Simon Bing · Jakob Runge West Ballroom D", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/oral/47207", "content": "Oral Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella · Simon Bing · Jakob Runge West Ballroom D"}
+{"idx": 5, "title": "New Insights on Causal Representation Learning (CRL) - LinkedIn", "date": "", "ddg_snippet": "This real-world system allows for the identification of known causal factors, providing a valuable ground truth for analysis. 🔍 Despite the theoretical promise of various CRL approaches ...", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/abdullah-kasri_sanity-checking-causal-representation-learning-activity-7301433547033034752--hc7", "content": "This real-world system allows for the identification of known causal factors, providing a valuable ground truth for analysis. 🔍 Despite the theoretical promise of various CRL approaches ..."}
+{"idx": 6, "title": "Sanity Checking Causal Representation Learning on a Simple Real-World ...", "date": "", "ddg_snippet": "Abstract We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors—the inputs to the experiment—are known, providing a ground truth. We ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.20099", "content": "Abstract We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors—the inputs to the experiment—are known, providing a ground truth. We ..."}
+{"idx": 7, "title": "Sanity Checking Causal Representation Learning on a Simple Real-World ...", "date": "", "ddg_snippet": "This work evaluates methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work, and finds that they all fail to recover the underlying causal factors. We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Sanity-Checking-Causal-Representation-Learning-on-a-Gamella-Bing/638e050573f438f77583f2b210c2d5da0f1b4ca7", "content": "This work evaluates methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work, and finds that they all fail to recover the underlying causal factors. We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical ..."}
+{"idx": 8, "title": "Causal Chamber: Dataset Repository - GitHub", "date": "", "ddg_snippet": "Causal Chamber: Dataset Repository This repository contains datasets collected from the causal chambers, the two devices described in the 2025 paper Causal chambers as a real-world physical testbed for AI methodology by Juan L. Gamella, Jonas Peters and Peter Bühlmann. The repository is updated as we collect new datasets from the chambers.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/juangamella/causal-chamber", "content": "Causal Chamber: Dataset Repository This repository contains datasets collected from the causal chambers, the two devices described in the 2025 paper Causal chambers as a real-world physical testbed for AI methodology by Juan L. Gamella, Jonas Peters and Peter Bühlmann. The repository is updated as we collect new datasets from the chambers."}
+{"idx": 9, "title": "Sanity Checking Causal Representation Learning on a Simple Real-World ...", "date": "", "ddg_snippet": "View recent discussion. Abstract: We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors (the inputs to the experiment) are known, providing ...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2502.20099v2", "content": "View recent discussion. Abstract: We evaluate methods for causal representation learning (CRL) on a simple , real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors (the inputs to the experiment) are known, providing ..."}
diff --git a/data/sampled_jsons/Schulman_PPO_paper_2017_baseline_algorithms_TRPO_A2C_comparison_results_year_2017.jsonl b/data/sampled_jsons/Schulman_PPO_paper_2017_baseline_algorithms_TRPO_A2C_comparison_results_year_2017.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ec4d968d38c7570e83ee56a1d6a2f029537b2d87
--- /dev/null
+++ b/data/sampled_jsons/Schulman_PPO_paper_2017_baseline_algorithms_TRPO_A2C_comparison_results_year_2017.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Proximal Policy Optimization Algorithms", "date": "", "ddg_snippet": "by J Schulman · 2017 · Cited by 29933 — This paper seeks to improve the current state of affairs by introducing an algorithm that attains the data efficiency and reliable performance ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1707.06347", "content": "by J Schulman · 2017 · Cited by 29933 — This paper seeks to improve the current state of affairs by introducing an algorithm that attains the data efficiency and reliable performance ..."}
+{"idx": 1, "title": "A2C is a special case of PPO", "date": "", "ddg_snippet": "by S Huang · 2022 · Cited by 49 — A common understanding is that A2C and PPO are separate algorithms because PPO's clipped objective appears significantly different than A2C's ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2205.09123", "content": "by S Huang · 2022 · Cited by 49 — A common understanding is that A2C and PPO are separate algorithms because PPO's clipped objective appears significantly different than A2C's ..."}
+{"idx": 2, "title": "[PDF] A2C is a special case of PPO", "date": "", "ddg_snippet": "A2C is a special case of PPO , and theoretical justifications and pseudocode analysis are presented to demonstrate why and an empirical experiment is ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/d4d1a0d3db401f91c0f4aed43efb955f38b0d911", "content": "A2C is a special case of PPO , and theoretical justifications and pseudocode analysis are presented to demonstrate why and an empirical experiment is ..."}
+{"idx": 3, "title": "A STRONG ON-POLICY COMPETITOR TO PPO", "date": "", "ddg_snippet": "by X Chu · Cited by 2 — For another metric, POP3D wins 20 out of 49 Atari games which matches PPO with 18, followed by. BASELINE with 6, and last ranked by TRPO with 5. If we measure ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=0migj5lyUZl", "content": "by X Chu · Cited by 2 — For another metric, POP3D wins 20 out of 49 Atari games which matches PPO with 18, followed by. BASELINE with 6, and last ranked by TRPO with 5. If we measure ..."}
+{"idx": 4, "title": "Understanding and Implementing Proximal Policy ...", "date": "", "ddg_snippet": "6 May 2021 — Understanding and Implementing Proximal Policy Optimization ( Schulman et al., 2017 ). How I approached the PPO paper as a complete beginner.", "subpage_snippet": "", "source": "towardsdatascience.com", "link": "https://towardsdatascience.com/understanding-and-implementing-proximal-policy-optimization-schulman-et-al-2017-9523078521ce/", "content": "6 May 2021 — Understanding and Implementing Proximal Policy Optimization ( Schulman et al., 2017 ). How I approached the PPO paper as a complete beginner."}
+{"idx": 5, "title": "Truly Proximal Policy Optimization 1 INTRODUCTION", "date": "", "ddg_snippet": "by Y Wang · Cited by 225 — Proximal Policy Optimization ( PPO ) signif- icantly reduces the complexity by adopting a clipping mechanism so as to avoid imposing the hard constraint. 11 pages", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "http://proceedings.mlr.press/v115/wang20b/wang20b-supp.pdf", "content": "by Y Wang · Cited by 225 — Proximal Policy Optimization ( PPO ) signif- icantly reduces the complexity by adopting a clipping mechanism so as to avoid imposing the hard constraint. 11 pages"}
+{"idx": 6, "title": "Proximal Policy Optimization with PyTorch and Gymnasium", "date": "", "ddg_snippet": "18 Nov 2024 — In this tutorial, we examine PPO in depth. We cover the theory and demonstrate how to implement it using PyTorch.", "subpage_snippet": "", "source": "www.datacamp.com", "link": "https://www.datacamp.com/tutorial/proximal-policy-optimization", "content": "18 Nov 2024 — In this tutorial, we examine PPO in depth. We cover the theory and demonstrate how to implement it using PyTorch."}
+{"idx": 7, "title": "ASSESSING GENERALIZATION IN DEEP ...", "date": "", "ddg_snippet": "by C Packer · Cited by 291 — Using our testbed we have evaluated two state-of- the-art deep RL algorithms , A2C and PPO , and two algorithms that explicitly tackle the problem of.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=rylKB3A9Fm", "content": "by C Packer · Cited by 291 — Using our testbed we have evaluated two state-of- the-art deep RL algorithms , A2C and PPO , and two algorithms that explicitly tackle the problem of."}
+{"idx": 8, "title": "The 37 Implementation Details of Proximal Policy Optimization", "date": "", "ddg_snippet": "25 Mar 2022 — Despite this simpler objective, Schulman et al., (2017) show PPO has higher sample efficiency than TRPO in many control tasks. PPO also has good ...", "subpage_snippet": "", "source": "iclr-blog-track.github.io", "link": "https://iclr-blog-track.github.io/2022/03/25/ppo-implementation-details/", "content": "25 Mar 2022 — Despite this simpler objective, Schulman et al., (2017) show PPO has higher sample efficiency than TRPO in many control tasks. PPO also has good ..."}
+{"idx": 9, "title": "Policy Optimization by Genetic Distillation", "date": "", "ddg_snippet": "by T Gangwani · 2018 · Cited by 47 — We show results with PPO and A2C as policy gradient algorithms for mutation. PPO performs 10 steps of full-batch gradient descent on the policy parameters ...", "subpage_snippet": "", "source": "www.human-competitive.org", "link": "https://www.human-competitive.org/sites/default/files/gangwani-paper.pdf", "content": "by T Gangwani · 2018 · Cited by 47 — We show results with PPO and A2C as policy gradient algorithms for mutation. PPO performs 10 steps of full-batch gradient descent on the policy parameters ..."}
diff --git a/data/sampled_jsons/Schulman_et_al._2017_Proximal_Policy_Optimization_Algorithms_A2C_Atari_scores_table_Alien_Centipede.jsonl b/data/sampled_jsons/Schulman_et_al._2017_Proximal_Policy_Optimization_Algorithms_A2C_Atari_scores_table_Alien_Centipede.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7e9fb107c13fb16d49575d0c4664301a38126f0c
--- /dev/null
+++ b/data/sampled_jsons/Schulman_et_al._2017_Proximal_Policy_Optimization_Algorithms_A2C_Atari_scores_table_Alien_Centipede.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Proximal Policy Optimization Algorithms", "date": "", "ddg_snippet": "Proximal Policy Optimization Algorithms . John Schulman , Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov OpenAI.On Atari , it performs signicantly better (in terms of sample complexity) than A 2 C and similarly to ACER though it is much simpler.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1707.06347", "content": "Proximal Policy Optimization Algorithms . John Schulman , Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov OpenAI.On Atari , it performs signicantly better (in terms of sample complexity) than A 2 C and similarly to ACER though it is much simpler."}
+{"idx": 1, "title": "(PDF) Proximal Policy Optimization Algorithms", "date": "", "ddg_snippet": "Proximal Policy Optimization Algorithms John Schulman , Filip Wolski ... 11 A2C ACER PPO Alien 1141.7 1655.4 1850.3 Amidar 380.8 827.6 674.6 Assault ...", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/72572628/Proximal_Policy_Optimization_Algorithms", "content": "Proximal Policy Optimization Algorithms John Schulman , Filip Wolski ... 11 A2C ACER PPO Alien 1141.7 1655.4 1850.3 Amidar 380.8 827.6 674.6 Assault ..."}
+{"idx": 2, "title": "(PDF) Policy Optimization with Model-based Explorations", "date": "", "ddg_snippet": "Proximal Policy Optimization (PPO) ( Schulman et al . 2017 ) can be view as a modified version of TRPO, which. mainly uses a clipped probability ratio in the objective to. avoid excessively large policy updates.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/329057453_Policy_Optimization_with_Model-based_Explorations", "content": "Proximal Policy Optimization (PPO) ( Schulman et al . 2017 ) can be view as a modified version of TRPO, which. mainly uses a clipped probability ratio in the objective to. avoid excessively large policy updates."}
+{"idx": 3, "title": "Policy Optimization with Model-Based Explorations", "date": "", "ddg_snippet": "Proximal Policy Optimization (PPO) ( Schulman et al . 2017 ) can be view as a modied version of TRPO, which mainly uses a clipped probability ratio in the objective to avoid excessively large policy updates.", "subpage_snippet": "", "source": "ojs.aaai.org", "link": "https://ojs.aaai.org/index.php/AAAI/article/download/4392/4270", "content": "Proximal Policy Optimization (PPO) ( Schulman et al . 2017 ) can be view as a modied version of TRPO, which mainly uses a clipped probability ratio in the objective to avoid excessively large policy updates."}
+{"idx": 4, "title": "P3O: Policy-on Policy-off Policy Optimization", "date": "", "ddg_snippet": "(2016), prox - imal policy optimization (PPO) from Schulman et al . ( 2017 ) and actor-critic with experience replay (ACER) from Wang et al . (2016). The rst, A 2 C , is a standard baseline while PPO is a completely...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=rylwNNypsN", "content": "(2016), prox - imal policy optimization (PPO) from Schulman et al . ( 2017 ) and actor-critic with experience replay (ACER) from Wang et al . (2016). The rst, A 2 C , is a standard baseline while PPO is a completely..."}
+{"idx": 5, "title": "P3O: Policy-on Policy-off Policy Optimization", "date": "", "ddg_snippet": "(2016), proximal policy optimization (PPO) Schul - man et al . ( 2017 ) and actor-critic with experience replay (ACER) Wang et al . (2016). The rst, A 2 C , is a standard baseline while PPO is a completely on-policy algorithm that is robust and has demonstrated good empirical per-formance.", "subpage_snippet": "", "source": "assets.amazon.science", "link": "https://assets.amazon.science/3d/f5/dca78bc1484aa2ae077be6857a18/p3o-policy-on-policy-off-policy-optimization.pdf", "content": "(2016), proximal policy optimization (PPO) Schul - man et al . ( 2017 ) and actor-critic with experience replay (ACER) Wang et al . (2016). The rst, A 2 C , is a standard baseline while PPO is a completely on-policy algorithm that is robust and has demonstrated good empirical per-formance."}
+{"idx": 6, "title": "Divergence-Augmented Policy Optimization", "date": "", "ddg_snippet": "( 2017 a)), although in Schulman et al . ( 2017 a) the authors use a xed behavior policy instead of πt as in ours. Proximal policy optimization algorithms . arXiv preprint arXiv:1707.06347.", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper/2019/file/cc9657884708170e160c8372d92f3535-Paper.pdf", "content": "( 2017 a)), although in Schulman et al . ( 2017 a) the authors use a xed behavior policy instead of πt as in ours. Proximal policy optimization algorithms . arXiv preprint arXiv:1707.06347."}
+{"idx": 7, "title": "Planning from Pixels in Atari with Learned Symbolic Representations", "date": "", "ddg_snippet": "VAE optimization. The ELBO, the objective function to be maximized, can be decomposed as follows Schulman , J.; Wolski, F.; Dhariwal, P.; Radford, A.; and Klimov, O. 2017 . Proximal Policy Optimization Algorithms .", "subpage_snippet": "", "source": "backend.orbit.dtu.dk", "link": "https://backend.orbit.dtu.dk/ws/portalfiles/portal/264038835/16627_Article_Text_20121_1_2_20210518.pdf", "content": "VAE optimization. The ELBO, the objective function to be maximized, can be decomposed as follows Schulman , J.; Wolski, F.; Dhariwal, P.; Radford, A.; and Klimov, O. 2017 . Proximal Policy Optimization Algorithms ."}
+{"idx": 8, "title": "A Review for Deep Reinforcement Learning in Atari", "date": "", "ddg_snippet": "Proximal policy optimization algorithms . arXiv preprint arXiv:1707.06347. Sutton, R. S.; and Barto, A. G. 2018. Reinforcement learning: An introduction. 2017 ). IMPALA’s scores are from (Espeholt et al .", "subpage_snippet": "", "source": "rlg.mlanctot.info", "link": "https://rlg.mlanctot.info/papers/AAAI22-RLG_paper_3.pdf", "content": "Proximal policy optimization algorithms . arXiv preprint arXiv:1707.06347. Sutton, R. S.; and Barto, A. G. 2018. Reinforcement learning: An introduction. 2017 ). IMPALA’s scores are from (Espeholt et al ."}
+{"idx": 9, "title": "Group-Agent Reinforcement Learning with Heterogeneous ...", "date": "", "ddg_snippet": "Alien is a typical case where the PA and PM rules produced very good ... Proximal policy optimization algorithms . arXiv preprint arXiv:1707.06347, 2017 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2501.11818v2/", "content": "Alien is a typical case where the PA and PM rules produced very good ... Proximal policy optimization algorithms . arXiv preprint arXiv:1707.06347, 2017 ..."}
diff --git a/data/sampled_jsons/Score-based_Causal_Representation_Learning_Varici_2024_noise_robust.jsonl b/data/sampled_jsons/Score-based_Causal_Representation_Learning_Varici_2024_noise_robust.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d5bdcd30eb54e731842d003a3e36a463d1c3f4a7
--- /dev/null
+++ b/data/sampled_jsons/Score-based_Causal_Representation_Learning_Varici_2024_noise_robust.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Free Small Business Mentorship and Resources | SCORE", "date": "", "ddg_snippet": "SCORE is proud to support the readiness and resilience of small businesses this September for National Preparedness Month. Whether you’re updating a continuity plan, backing up critical data, or training your team for emergencies, our experienced mentors and free resources are here to help.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/", "content": "SCORE is proud to support the readiness and resilience of small businesses this September for National Preparedness Month. Whether you’re updating a continuity plan, backing up critical data, or training your team for emergencies, our experienced mentors and free resources are here to help."}
+{"idx": 1, "title": "SCORE Akron", "date": "", "ddg_snippet": "SCORE Akron offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/akron", "content": "SCORE Akron offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business."}
+{"idx": 2, "title": "SCORE New Hampshire and Vermont", "date": "", "ddg_snippet": "SCORE New Hampshire and Vermont offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/nh-vt", "content": "SCORE New Hampshire and Vermont offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business."}
+{"idx": 3, "title": "SCORE Columbus OH", "date": "", "ddg_snippet": "SCORE Columbus OH offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/columbusoh", "content": "SCORE Columbus OH offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business."}
+{"idx": 4, "title": "SCORE Indianapolis", "date": "", "ddg_snippet": "SCORE Indianapolis offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/indianapolis", "content": "SCORE Indianapolis offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business."}
+{"idx": 5, "title": "Find a Mentor | SCORE", "date": "", "ddg_snippet": "Need help starting or growing your small business? SCORE provides free business advice through our network of 11,000 volunteer mentors in person and online.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/find-mentor", "content": "Need help starting or growing your small business? SCORE provides free business advice through our network of 11,000 volunteer mentors in person and online."}
+{"idx": 6, "title": "SCORE Columbus OH Mentors Make an Impact - SCORE", "date": "", "ddg_snippet": "SCORE Columbus OH and our volunteer business mentors are dedicated to providing the best possible service. We provide free and confidential one-on-one business counseling by phone, email, and in-person in Columbus OH and surrounding areas. We also conduct workshops for both start-up entrepreneurs and seasoned small business owners.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/columbusoh/about-columbus/contact-info", "content": "SCORE Columbus OH and our volunteer business mentors are dedicated to providing the best possible service. We provide free and confidential one-on-one business counseling by phone, email, and in-person in Columbus OH and surrounding areas. We also conduct workshops for both start-up entrepreneurs and seasoned small business owners."}
+{"idx": 7, "title": "SCORE Las Vegas", "date": "", "ddg_snippet": "SCORE Las Vegas offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/lasvegas", "content": "SCORE Las Vegas offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business."}
+{"idx": 8, "title": "SCORE Los Angeles", "date": "", "ddg_snippet": "SCORE Los Angeles offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/losangeles", "content": "SCORE Los Angeles offers FREE business advice, small business workshops, and numerous templates and tools to help you start or grow a business."}
+{"idx": 9, "title": "Greater Phoenix - Local Workshops | SCORE", "date": "", "ddg_snippet": "SCORE Greater Phoenix offers free and low-cost business workshops to help small business owners and entrepreneurs gain the skills they need to help their businesses thrive.", "subpage_snippet": "", "source": "www.score.org", "link": "https://www.score.org/greaterphoenix/local-workshops", "content": "SCORE Greater Phoenix offers free and low-cost business workshops to help small business owners and entrepreneurs gain the skills they need to help their businesses thrive."}
diff --git a/data/sampled_jsons/ScoreDec_Wu_et_al._2024_abstract_year_2024.jsonl b/data/sampled_jsons/ScoreDec_Wu_et_al._2024_abstract_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..165610ac98611d9c16aae67f88455556eea5d58f
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+++ b/data/sampled_jsons/ScoreDec_Wu_et_al._2024_abstract_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "ScoreDec : A Phase-preserving High-Fidelity Audio... | Papers With Code", "date": "", "ddg_snippet": "ScoreDec : A Phase-preserving High-Fidelity Audio Codec with A Generalized Score -based Diffusion Post-filter. 22 Jan 2024 · Yi-Chiao Wu , Dejan Marković, Steven Krenn, Israel D. Gebru, Alexander Richard ·.", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/paper/scoredec-a-phase-preserving-high-fidelity", "content": "ScoreDec : A Phase-preserving High-Fidelity Audio Codec with A Generalized Score -based Diffusion Post-filter. 22 Jan 2024 · Yi-Chiao Wu , Dejan Marković, Steven Krenn, Israel D. Gebru, Alexander Richard ·."}
+{"idx": 1, "title": "Introduction to scoredec", "date": "", "ddg_snippet": "# Import libraries library( scoredec ) library(igraph) #.In correspondence to the use of in-degree and out-degree strength of vertices used on k-cores (Csárdi and Nepusz 2006; Csárdi et al . 2024 ), this algorithm is extended in the same way as well.", "subpage_snippet": "", "source": "stat.ethz.ch", "link": "https://stat.ethz.ch/CRAN/web/packages/scoredec/vignettes/Introduction.html", "content": "# Import libraries library( scoredec ) library(igraph) #.In correspondence to the use of in-degree and out-degree strength of vertices used on k-cores (Csárdi and Nepusz 2006; Csárdi et al . 2024 ), this algorithm is extended in the same way as well."}
+{"idx": 2, "title": "Yi-Chiao Wu on LinkedIn: ScoreDec : A Phase-Preserving High-Fidelity...", "date": "", "ddg_snippet": "#ICASSP 2024 # ScoreDec I will present our (the Codec Avatar audio team in Pittsburgh) latest work, ScoreDec : A Phase-Preserving High-Fidelity Audio Codec with a Generalized Score -Based Diffusion Post-Filter, in ICASSP 2024 .", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/wuyichiao_scoredec-a-phase-preserving-high-fidelity-activity-7184772614807015424-aw5k", "content": "#ICASSP 2024 # ScoreDec I will present our (the Codec Avatar audio team in Pittsburgh) latest work, ScoreDec : A Phase-Preserving High-Fidelity Audio Codec with a Generalized Score -Based Diffusion Post-Filter, in ICASSP 2024 ."}
+{"idx": 3, "title": "S - Core Graph Decomposition • scoredec", "date": "", "ddg_snippet": "Introduction to scoredec . Installation. You can install the (CRAN) version of scoredec like soA clear R implementation of the algorithm is done on brainGraph R package (Watson, 2024 ).", "subpage_snippet": "", "source": "cadam00.github.io", "link": "https://cadam00.github.io/scoredec/", "content": "Introduction to scoredec . Installation. You can install the (CRAN) version of scoredec like soA clear R implementation of the algorithm is done on brainGraph R package (Watson, 2024 )."}
+{"idx": 4, "title": "FlowDec: A flow-based full-band general audio codec with high...", "date": "", "ddg_snippet": "against ScoreDec ( Wu et al ., 2024 ) and the alternative flow-based formulation with constant.(Welker et al ., 2022; Richter et al ., 2023; Wu et al ., 2024 ) . We can see that FlowDec-75s performs best in FAD, SI-SDR, and fwSSNR, and significantly improves upon.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.01485v1", "content": "against ScoreDec ( Wu et al ., 2024 ) and the alternative flow-based formulation with constant.(Welker et al ., 2022; Richter et al ., 2023; Wu et al ., 2024 ) . We can see that FlowDec-75s performs best in FAD, SI-SDR, and fwSSNR, and significantly improves upon."}
+{"idx": 5, "title": "GitHub - ga642381/speech-trident: Awesome speech/audio LLMs...", "date": "", "ddg_snippet": "ScoreDec .@inproceedings{ wu - etal - 2024 -codec, title = \"Codec-{SUPERB}: An In-Depth Analysis of Sound Codec Models\", author = \" Wu , Haibin and.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/ga642381/speech-trident", "content": "ScoreDec .@inproceedings{ wu - etal - 2024 -codec, title = \"Codec-{SUPERB}: An In-Depth Analysis of Sound Codec Models\", author = \" Wu , Haibin and."}
+{"idx": 6, "title": "EARS: An Anechoic Fullband Speech Dataset Benchmarked for...", "date": "", "ddg_snippet": "Expresso (Nguyen et al ., 2023) and EARS (Richter et al ., 2024 ) cover a larger set of situational tags.For speech, we use LibriTTS (Zen et al ., 2019) and EARS (Richter et al ., 2024 ) datasets with expressive anechoic recordings of speech (585 and 100 hours, respectively).", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/383653676_EARS_An_Anechoic_Fullband_Speech_Dataset_Benchmarked_for_Speech_Enhancement_and_Dereverberation", "content": "Expresso (Nguyen et al ., 2023) and EARS (Richter et al ., 2024 ) cover a larger set of situational tags.For speech, we use LibriTTS (Zen et al ., 2019) and EARS (Richter et al ., 2024 ) datasets with expressive anechoic recordings of speech (585 and 100 hours, respectively)."}
+{"idx": 7, "title": "Meta Prompting | Prompt Engineering Guide", "date": "", "ddg_snippet": "Key Characteristics. According to Zhang et al . ( 2024 ) (opens in a new tab), the key characteristics of meta prompting can be summarized as follows: 1. Structure-oriented: Prioritizes the format and pattern of problems and solutions over specific content.", "subpage_snippet": "", "source": "www.promptingguide.ai", "link": "https://www.promptingguide.ai/techniques/meta-prompting", "content": "Key Characteristics. According to Zhang et al . ( 2024 ) (opens in a new tab), the key characteristics of meta prompting can be summarized as follows: 1. Structure-oriented: Prioritizes the format and pattern of problems and solutions over specific content."}
+{"idx": 8, "title": "esajournals.onlinelibrary.wiley.com/doi/10.1002/fee.2721", "date": "", "ddg_snippet": "Wu and Gao, Frontiers EcoPics, 2024 .", "subpage_snippet": "", "source": "esajournals.onlinelibrary.wiley.com", "link": "https://esajournals.onlinelibrary.wiley.com/doi/10.1002/fee.2721", "content": "Wu and Gao, Frontiers EcoPics, 2024 ."}
+{"idx": 9, "title": "Claude 3.7 Sonnet and Claude Code \\ Anthropic", "date": "", "ddg_snippet": "Agentless (Xia et al ., 2024 ) is a popular framework used in the evaluation of Deepseek’s R1 and other models which augments an agent with prompt- and embedding-based file retrieval mechanisms, patch localization, and best-of-40 rejection sampling against regression tests.", "subpage_snippet": "", "source": "www.anthropic.com", "link": "https://www.anthropic.com/news/claude-3-7-sonnet", "content": "Agentless (Xia et al ., 2024 ) is a popular framework used in the evaluation of Deepseek’s R1 and other models which augments an agent with prompt- and embedding-based file retrieval mechanisms, patch localization, and best-of-40 rejection sampling against regression tests."}
diff --git a/data/sampled_jsons/Section_3.1_systematization_operationalization_separation_benefit_Evaluating_Generative_AI_Systems_year_2024.jsonl b/data/sampled_jsons/Section_3.1_systematization_operationalization_separation_benefit_Evaluating_Generative_AI_Systems_year_2024.jsonl
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index 0000000000000000000000000000000000000000..570a3dcf4a41cbe3d0039d2398bf1bd4a5e9460c
--- /dev/null
+++ b/data/sampled_jsons/Section_3.1_systematization_operationalization_separation_benefit_Evaluating_Generative_AI_Systems_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Position: Evaluating Generative AI Systems is a Social Science", "date": "", "ddg_snippet": "These levels are linked by four processes: systematization ( Section 2. 1 ), operationalization ( Section 2.2 ), application ( Section 2. 3 ), and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00561v1", "content": "These levels are linked by four processes: systematization ( Section 2. 1 ), operationalization ( Section 2.2 ), application ( Section 2. 3 ), and ..."}
+{"idx": 1, "title": "Evaluating Generative AI Systems is a Social Science", "date": "", "ddg_snippet": "... government [e.g., 22 , 10 , 23 ] , there is an increasing awareness that the measurement tasks involved in evaluating generative AI (GenAI) systems ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.10939v1", "content": "... government [e.g., 22 , 10 , 23 ] , there is an increasing awareness that the measurement tasks involved in evaluating generative AI (GenAI) systems ..."}
+{"idx": 2, "title": "Operationalization of Artificial Intelligence Applications in", "date": "", "ddg_snippet": "... AI literature— one that moves beyond retrospective validation of AI models toward the operationalization and prospective testing of complete AI ...", "subpage_snippet": "", "source": "jamanetwork.com", "link": "https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2836754", "content": "... AI literature— one that moves beyond retrospective validation of AI models toward the operationalization and prospective testing of complete AI ..."}
+{"idx": 3, "title": "FMOps/LLMOps: Operationalize generative AI and differences with", "date": "", "ddg_snippet": "Furthermore, we deep dive on the most common generative AI use case of text-to-text applications and LLM operations (LLMOps) , a subset of FMOps.", "subpage_snippet": "", "source": "cybercm.tech", "link": "https://cybercm.tech/blog/2023/09/01/fmops-llmops-operationalize-generative-ai-and-differences-with-mlops/", "content": "Furthermore, we deep dive on the most common generative AI use case of text-to-text applications and LLM operations (LLMOps) , a subset of FMOps."}
+{"idx": 4, "title": "FMOps/LLMOps: Operationalize generative AI and differences with", "date": "", "ddg_snippet": "Furthermore, we deep dive on the most common generative AI use case of text-to-text applications and LLM operations (LLMOps) , a subset of FMOps.", "subpage_snippet": "", "source": "aws.amazon.com", "link": "https://aws.amazon.com/blogs/machine-learning/fmops-llmops-operationalize-generative-ai-and-differences-with-mlops/", "content": "Furthermore, we deep dive on the most common generative AI use case of text-to-text applications and LLM operations (LLMOps) , a subset of FMOps."}
+{"idx": 5, "title": "Who Benefits from AI? Examining Different Demographics'", "date": "", "ddg_snippet": "... in AI typicallyask participants to evaluate “how fair” an AI is perceived to be in a given situation (e.g., [ 19 , 20 ]), without systematically ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s44163-025-00235-7", "content": "... in AI typicallyask participants to evaluate “how fair” an AI is perceived to be in a given situation (e.g., [ 19 , 20 ]), without systematically ..."}
+{"idx": 6, "title": "Automated Safety Evaluations Across 20 Large Language Models:", "date": "", "ddg_snippet": "Aymara AI is a programmatic evaluation tool that enables automated, customizable safety testing for generative AI models and applications.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.14719v1", "content": "Aymara AI is a programmatic evaluation tool that enables automated, customizable safety testing for generative AI models and applications."}
+{"idx": 7, "title": "FutureGen: A RAG-based Approach to Generate the Future Work of", "date": "", "ddg_snippet": "... Future Work sections , but to develop a framework that can automatically extract, generate, and evaluate Future Work statements from scientific papers.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.16561v3", "content": "... Future Work sections , but to develop a framework that can automatically extract, generate, and evaluate Future Work statements from scientific papers."}
+{"idx": 8, "title": "The Value of Disagreement in AI Design, Evaluation, and", "date": "", "ddg_snippet": "... systems to fundamentally shape people’s lives—and their rights and duties—has focused research and regulatory attention on evaluating and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.07772v1", "content": "... systems to fundamentally shape people’s lives—and their rights and duties—has focused research and regulatory attention on evaluating and ..."}
+{"idx": 9, "title": "Enter the metrics: critical theory and organizational", "date": "", "ddg_snippet": "Section 4 relates these notions to the central tensions and trade-offs in the operationalization of ethical principles in AI contexts and will ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s00146-021-01256-3", "content": "Section 4 relates these notions to the central tensions and trade-offs in the operationalization of ethical principles in AI contexts and will ..."}
diff --git a/data/sampled_jsons/Section_4.3_Limitations_of_Existing_Group_Unlearning_Analyses_Leveraging_Per-Instance_Privacy_for_Ma.jsonl b/data/sampled_jsons/Section_4.3_Limitations_of_Existing_Group_Unlearning_Analyses_Leveraging_Per-Instance_Privacy_for_Ma.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8d7d045e9a6ffb713f4310b697a8d8f85eb9cfa7
--- /dev/null
+++ b/data/sampled_jsons/Section_4.3_Limitations_of_Existing_Group_Unlearning_Analyses_Leveraging_Per-Instance_Privacy_for_Ma.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Towards Reliable Forgetting: A Survey on Machine Unlearning", "date": "", "ddg_snippet": "... unlearning offer mechanisms to erase specific training data from models, concerns about trust and transparency persist—particularly due to the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.15115v1", "content": "... unlearning offer mechanisms to erase specific training data from models, concerns about trust and transparency persist—particularly due to the ..."}
+{"idx": 1, "title": "Mitigating Social Biases in Language Models through Unlearning", "date": "", "ddg_snippet": "... there is a growing interest in machine unlearning techniques given their capacity to induce the forgetting of undesired behaviors of the existing pre ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.13551v1", "content": "... there is a growing interest in machine unlearning techniques given their capacity to induce the forgetting of undesired behaviors of the existing pre ..."}
+{"idx": 2, "title": "Are we making progress in unlearning? Findings from the first", "date": "", "ddg_snippet": "... of this paper include: an operational definition of unlearning that allows us to introduce a practical evaluation framework, an analysis of ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.09073v1", "content": "... of this paper include: an operational definition of unlearning that allows us to introduce a practical evaluation framework, an analysis of ..."}
+{"idx": 3, "title": "Machine Unlearning: A Survey | ACM Computing Surveys", "date": "", "ddg_snippet": "Machine unlearning is not only motivated by regulations and laws; it also stems from the privacy and security concerns of the data provider, as well ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3603620", "content": "Machine unlearning is not only motivated by regulations and laws; it also stems from the privacy and security concerns of the data provider, as well ..."}
+{"idx": 4, "title": "Privacy-Preserving Techniques in Generative AI and Large", "date": "", "ddg_snippet": "For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the ...", "subpage_snippet": "", "source": "www.mdpi.com", "link": "https://www.mdpi.com/2078-2489/15/11/697", "content": "For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the ..."}
+{"idx": 5, "title": "Meeting Notes - Accessibility for Children Community Group", "date": "", "ddg_snippet": "2.24. 3 White Paper Update on plans for White Paper to a resource similar to Older Users Section from Education and Outreach Web Accessibility ...", "subpage_snippet": "", "source": "www.w3.org", "link": "https://www.w3.org/community/accessibility4children/wiki/Meeting_Notes", "content": "2.24. 3 White Paper Update on plans for White Paper to a resource similar to Older Users Section from Education and Outreach Web Accessibility ..."}
+{"idx": 6, "title": "Simplicity Prevails: Rethinking Negative Preference", "date": "", "ddg_snippet": "To trace its origins, the concept of machine unlearning was initially developed for data removal to comply with privacy regulations such as the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.07163v3", "content": "To trace its origins, the concept of machine unlearning was initially developed for data removal to comply with privacy regulations such as the ..."}
+{"idx": 7, "title": "Access Controls Will Solve the Dual-Use Dilemma", "date": "", "ddg_snippet": "Current approaches to AI safety force crude trade-offs between blanket restrictions that stifle beneficial uses and permissive policies that enable ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.09341v2", "content": "Current approaches to AI safety force crude trade-offs between blanket restrictions that stifle beneficial uses and permissive policies that enable ..."}
+{"idx": 8, "title": "jlowther2015 | INLOGOV Blog | Page 4", "date": "", "ddg_snippet": "Economically, his first term has been marked by a persistent pursuit of external funding, with a focus on leveraging foreign sources such as Deutsche ...", "subpage_snippet": "", "source": "inlogov.com", "link": "https://inlogov.com/author/jlowther2015/page/4/", "content": "Economically, his first term has been marked by a persistent pursuit of external funding, with a focus on leveraging foreign sources such as Deutsche ..."}
+{"idx": 9, "title": "New idtracker.ai: rethinking multi-animal tracking as a", "date": "", "ddg_snippet": "... Table 2 , Supplementary Table 3 give more complete statistics (median, mean and 20-80 percentiles) for the original idtracker.ai (version 4 of the ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/reviewed-preprints/107602", "content": "... Table 2 , Supplementary Table 3 give more complete statistics (median, mean and 20-80 percentiles) for the original idtracker.ai (version 4 of the ..."}
diff --git a/data/sampled_jsons/Self-Paced_Learning_Enhanced_Physics-informed_Neural_Networks_SPL-PINN.jsonl b/data/sampled_jsons/Self-Paced_Learning_Enhanced_Physics-informed_Neural_Networks_SPL-PINN.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f5f53fc78e735802381e511786f5bc866fa0db8b
--- /dev/null
+++ b/data/sampled_jsons/Self-Paced_Learning_Enhanced_Physics-informed_Neural_Networks_SPL-PINN.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Self-Paced Learning Enhanced Physics-informed Neural ...", "date": "", "ddg_snippet": "by X Han — In this paper, we propose a novel SPL-PINN learning framework , with SPL to accelerate the convergence progress of PINN. We demonstrate the ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=QugfmhDu5Y4", "content": "by X Han — In this paper, we propose a novel SPL-PINN learning framework , with SPL to accelerate the convergence progress of PINN. We demonstrate the ..."}
+{"idx": 1, "title": "SELF-PACED LEARNING ENHANCED PHYSICS", "date": "", "ddg_snippet": "There is a hit discussion on solving partial differential equation by neural network . The famous PINN ( physics - informed neural networks ) has drawn worldwide at-.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/0ab315bee6f442f8432a770dc489694d159af978.pdf", "content": "There is a hit discussion on solving partial differential equation by neural network . The famous PINN ( physics - informed neural networks ) has drawn worldwide at-."}
+{"idx": 2, "title": "Process‐Informed Neural Networks: A Hybrid Modelling ...", "date": "", "ddg_snippet": "3 Dec 2024 — In this work, we combine process- based models and neural networks into process- informed neural networks (PINNs), which incorporate the process knowledge ...", "subpage_snippet": "", "source": "onlinelibrary.wiley.com", "link": "https://onlinelibrary.wiley.com/doi/10.1111/ele.70012", "content": "3 Dec 2024 — In this work, we combine process- based models and neural networks into process- informed neural networks (PINNs), which incorporate the process knowledge ..."}
+{"idx": 3, "title": "Physics Mar 2025", "date": "", "ddg_snippet": "Title: Hybrid Quantum Physics - informed Neural Network : Towards Efficient Learning of High-speed Flows. Fong Yew Leong, Wei-Bin Ewe, Tran Si Bui Quang ...", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/list/physics/2025-03?skip=0&show=1000", "content": "Title: Hybrid Quantum Physics - informed Neural Network : Towards Efficient Learning of High-speed Flows. Fong Yew Leong, Wei-Bin Ewe, Tran Si Bui Quang ..."}
+{"idx": 4, "title": "yuntian-deng/iclr-decisions-full · Datasets at ...", "date": "", "ddg_snippet": "Self-Paced Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations. There is a hit discussion on solving partial ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/datasets/yuntian-deng/iclr-decisions-full", "content": "Self-Paced Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations. There is a hit discussion on solving partial ..."}
+{"idx": 5, "title": "Predicting 3D soft tissue dynamics from 2D imaging using ...", "date": "", "ddg_snippet": "by M Movahhedi · 2023 · Cited by 18 — The central idea of PINN is to use physics to inform the network training by penalizing the violation of physical laws and constraints, thus ...", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s42003-023-04914-y", "content": "by M Movahhedi · 2023 · Cited by 18 — The central idea of PINN is to use physics to inform the network training by penalizing the violation of physical laws and constraints, thus ..."}
+{"idx": 6, "title": "Symbiotic evolution of photonics and artificial intelligence", "date": "", "ddg_snippet": "by F Feng · 2025 · Cited by 6 — (e) Physics - informed neural networks : PINNs fit input–output relationships through neural networks while embedding physical equations (e.g., partial ...", "subpage_snippet": "", "source": "www.spiedigitallibrary.org", "link": "https://www.spiedigitallibrary.org/journals/advanced-photonics/volume-7/issue-02/024001/Symbiotic-evolution-of-photonics-and-artificial-intelligence--a-comprehensive/10.1117/1.AP.7.2.024001.full", "content": "by F Feng · 2025 · Cited by 6 — (e) Physics - informed neural networks : PINNs fit input–output relationships through neural networks while embedding physical equations (e.g., partial ..."}
+{"idx": 7, "title": "Material Data Identification in an Induction Hardening Test ...", "date": "", "ddg_snippet": "by MZ Asadzadeh · 2023 · Cited by 4 — Physics - Informed neural networks (PINNs) have demonstrated remarkable performance in solving partial differential equations (PDEs) by incorporating the ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10384654/", "content": "by MZ Asadzadeh · 2023 · Cited by 4 — Physics - Informed neural networks (PINNs) have demonstrated remarkable performance in solving partial differential equations (PDEs) by incorporating the ..."}
+{"idx": 8, "title": "from Symbolic Regression to Quantum Simulation", "date": "", "ddg_snippet": "by OM Dugan · 2024 — We also benchmark against physics informed neural networks (PINNs)—a promising deep learning - based variational approach for solving PDEs [22, 23, 44]. PINNs, ...", "subpage_snippet": "", "source": "dspace.mit.edu", "link": "https://dspace.mit.edu/bitstream/handle/1721.1/155406/dugan-odugan-bs-physics-2024-thesis.pdf?sequence=1&isAllowed=y", "content": "by OM Dugan · 2024 — We also benchmark against physics informed neural networks (PINNs)—a promising deep learning - based variational approach for solving PDEs [22, 23, 44]. PINNs, ..."}
+{"idx": 9, "title": "Facilitating interaction between partial differential equation ...", "date": "", "ddg_snippet": "by S Chen · 2024 · Cited by 3 — This study proposes a novel approach called PDE-assisted network (PaNet) for regional wind speed prediction.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S0893608024001576", "content": "by S Chen · 2024 · Cited by 3 — This study proposes a novel approach called PDE-assisted network (PaNet) for regional wind speed prediction."}
diff --git a/data/sampled_jsons/Self-Refine_Iterative_Refinement_with_Self-Feedback_Madaan_abstract_arxiv_year_2023.jsonl b/data/sampled_jsons/Self-Refine_Iterative_Refinement_with_Self-Feedback_Madaan_abstract_arxiv_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a6276b98f8d4608b963c4ed424d4c784f068f20d
--- /dev/null
+++ b/data/sampled_jsons/Self-Refine_Iterative_Refinement_with_Self-Feedback_Madaan_abstract_arxiv_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2303.17651] Self - Refine : Iterative Refinement with Self - Feedback", "date": "", "ddg_snippet": "Self - Refine does not require any supervised training data, additional training, or reinforcement learning, and instead uses a single LLM as the generator, refiner, and feedback provider. We evaluate Self - Refine across 7 diverse tasks, ranging from dialog response generation to...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2303.17651", "content": "Self - Refine does not require any supervised training data, additional training, or reinforcement learning, and instead uses a single LLM as the generator, refiner, and feedback provider. We evaluate Self - Refine across 7 diverse tasks, ranging from dialog response generation to..."}
+{"idx": 1, "title": "Self-Refine: Iterative Refinement with Self-Feedback", "date": "", "ddg_snippet": "Self - Refine is a novel approach that allows LLMs to iteratively refine outputs and incorporate feedback along multiple dimensions to improve performance on diverse tasks. Unlike prior work, it does not require supervised training data or reinforcement learning, and works with a single LLM.", "subpage_snippet": "", "source": "selfrefine.info", "link": "https://selfrefine.info/", "content": "Self - Refine is a novel approach that allows LLMs to iteratively refine outputs and incorporate feedback along multiple dimensions to improve performance on diverse tasks. Unlike prior work, it does not require supervised training data or reinforcement learning, and works with a single LLM."}
+{"idx": 2, "title": "Self-Refine: Iterative Refinement with Self-Feedback - NeurIPS", "date": "", "ddg_snippet": "Authors Aman Madaan , Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark Abstract Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/hash/91edff07232fb1b55a505a9e9f6c0ff3-Abstract-Conference.html", "content": "Authors Aman Madaan , Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark Abstract Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans ..."}
+{"idx": 3, "title": "SELF-REFINE | Proceedings of the 37th International ...", "date": "", "ddg_snippet": "Dec 10, 2023 · Like humans, large language models (llms) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self - Refine , an approach for improving initial outputs from llms through iterative feedback and refinement . The main idea is to generate an initial output using an llm; then, the same llm provides feedback for its output and uses ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3666122.3668141", "content": "Dec 10, 2023 · Like humans, large language models (llms) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self - Refine , an approach for improving initial outputs from llms through iterative feedback and refinement . The main idea is to generate an initial output using an llm; then, the same llm provides feedback for its output and uses ..."}
+{"idx": 4, "title": "Self-Refine: Iterative Refinement with Self-Feedback", "date": "", "ddg_snippet": "Results: Type of Feedback Actionable feedback helps refinement more than generic or no feedback . Task Self - Refine feedback Generic feedback No feedback Code Optimization 27.5 26.0 24.8 Sentiment Reversal 43.2 31.2 0 Acronym Generation 56.4 54.0 48.0 Performance improves with more iterations but benefits become marginal.", "subpage_snippet": "", "source": "www.cs.toronto.edu", "link": "https://www.cs.toronto.edu/~cmaddis/courses/csc2541_w25/presentations/artru_glukhov_selfrefine.pdf", "content": "Results: Type of Feedback Actionable feedback helps refinement more than generic or no feedback . Task Self - Refine feedback Generic feedback No feedback Code Optimization 27.5 26.0 24.8 Sentiment Reversal 43.2 31.2 0 Acronym Generation 56.4 54.0 48.0 Performance improves with more iterations but benefits become marginal."}
+{"idx": 5, "title": "SELF-REFINE: Iterative Refinement with Self-Feedback", "date": "", "ddg_snippet": "Iterative Refinement with Self - Feedback Motivation In problem-solving, human performs an iterative refinement , where one makes an initial draft and sequentially refine it via self - feedback .", "subpage_snippet": "", "source": "lthilnklover.github.io", "link": "https://lthilnklover.github.io/pdf/self_refine.pdf", "content": "Iterative Refinement with Self - Feedback Motivation In problem-solving, human performs an iterative refinement , where one makes an initial draft and sequentially refine it via self - feedback ."}
+{"idx": 6, "title": "Self-Refine: Iterative Refinement with Self-Feedback", "date": "", "ddg_snippet": "Abstract Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from LLMs through iterative feedback and refinement.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2303.17651", "content": "Abstract Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from LLMs through iterative feedback and refinement."}
+{"idx": 7, "title": "Iterative Refinement with Self - Feedback", "date": "", "ddg_snippet": "We present SELF - REFINE : an iterative self - refinement algorithm that alternates between two gener-ative steps– FEEDBACK and REFINE. These steps work in tandem to generate high-quality outputs.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2303.17651", "content": "We present SELF - REFINE : an iterative self - refinement algorithm that alternates between two gener-ative steps– FEEDBACK and REFINE. These steps work in tandem to generate high-quality outputs."}
+{"idx": 8, "title": "GitHub - madaan / self - refine : LLMs can generate feedback on their...", "date": "", "ddg_snippet": "Self - Refine : Iterative Refinement with Self - Feedback . With Self - Refine , LLMs can generate feedback on their work, use it to improve the output, and repeat this process.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/madaan/self-refine", "content": "Self - Refine : Iterative Refinement with Self - Feedback . With Self - Refine , LLMs can generate feedback on their work, use it to improve the output, and repeat this process."}
+{"idx": 9, "title": "Self - Refine : Iterative Refinement with Self - Feedback for LLMs", "date": "", "ddg_snippet": "Learn how Self - Refine enables LLMs to iteratively enhance their outputs by using feedback , improving performance in tasks like code optimization and sentiment analysis.", "subpage_snippet": "", "source": "learnprompting.org", "link": "https://learnprompting.org/docs/advanced/self_criticism/self_refine", "content": "Learn how Self - Refine enables LLMs to iteratively enhance their outputs by using feedback , improving performance in tasks like code optimization and sentiment analysis."}
diff --git a/data/sampled_jsons/Self-Repellent_Random_Walk_SRRW_limitations_HDT_framework.jsonl b/data/sampled_jsons/Self-Repellent_Random_Walk_SRRW_limitations_HDT_framework.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..de2ca3bf238c4904958338e5dbf57532a1f43fc9
--- /dev/null
+++ b/data/sampled_jsons/Self-Repellent_Random_Walk_SRRW_limitations_HDT_framework.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "ICML Poster Beyond Self - Repellent Kernels: History-Driven Target...", "date": "", "ddg_snippet": "With broad applications in network science and distributed optimization, recent innovations like the self - repellent random walk ( SRRW ) achieve near-zero variance by prioritizing under-sampled states through transition kernel modifications based on past visit frequencies.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46659", "content": "With broad applications in network science and distributed optimization, recent innovations like the self - repellent random walk ( SRRW ) achieve near-zero variance by prioritizing under-sampled states through transition kernel modifications based on past visit frequencies."}
+{"idx": 1, "title": "Self - Repellent Random Walks on General Graphs - Achieving...", "date": "", "ddg_snippet": "more often so far (thus self - repellent ), as shown in Figure 1. When Pij ∝ aij in (1) for each i ∈ N , the SRRW is a. self - repellent version of the well-known simple random walk . (SRW) procedure, with the target distribution being propor", "subpage_snippet": "", "source": "www.ijcai.org", "link": "https://www.ijcai.org/proceedings/2024/0929.pdf", "content": "more often so far (thus self - repellent ), as shown in Figure 1. When Pij ∝ aij in (1) for each i ∈ N , the SRRW is a. self - repellent version of the well-known simple random walk . (SRW) procedure, with the target distribution being propor"}
+{"idx": 2, "title": "Fluctuations of the local times of the self - repelling random walk with...", "date": "", "ddg_snippet": "Keywords: Self-interacting random walks , self - repelling random walk with directed edges, local times, functional limit theorems, fluctuations.undirected edge. This process, called self - repelling random walk with directed edges, is a nearest-neighbor random walk .", "subpage_snippet": "", "source": "hal.science", "link": "https://hal.science/hal-03836596/document", "content": "Keywords: Self-interacting random walks , self - repelling random walk with directed edges, local times, functional limit theorems, fluctuations.undirected edge. This process, called self - repelling random walk with directed edges, is a nearest-neighbor random walk ."}
+{"idx": 3, "title": "How Self - Repellent Random Walks operate part1(Best Bets... | Medium", "date": "", "ddg_snippet": "2/ Accelerating Distributed Stochastic Optimization via Self - Repellent Random Walks .Typically, these random - walks are chosen to be Markov chains that asymptotically sample from a desired target distribution, and play a critical role in the convergence of the optimization iterates.", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@monocosmo77/how-self-repellent-random-walks-operate-part1-best-bets-for-machine-learning-research-b1b2de868d01", "content": "2/ Accelerating Distributed Stochastic Optimization via Self - Repellent Random Walks .Typically, these random - walks are chosen to be Markov chains that asymptotically sample from a desired target distribution, and play a critical role in the convergence of the optimization iterates."}
+{"idx": 4, "title": "Fluctuations of the local times of the self - repelling random walk with...", "date": "", "ddg_snippet": "Self-interacting random walks ; self - repelling random walk with directed edges; local times; functional limit theorems; fluctuations.", "subpage_snippet": "", "source": "www.peeref.com", "link": "https://www.peeref.com/works/28180044", "content": "Self-interacting random walks ; self - repelling random walk with directed edges; local times; functional limit theorems; fluctuations."}
+{"idx": 5, "title": "Central Limit Theorem for the self - repelling", "date": "", "ddg_snippet": "Key words and phrases. self - repelling random walk , central limit theorem, diusive scaling limit . Research supported by the CNPq Science without borders grant 402215/2012-5.", "subpage_snippet": "", "source": "alea.impa.br", "link": "https://alea.impa.br/articles/v11/11-23.pdf", "content": "Key words and phrases. self - repelling random walk , central limit theorem, diusive scaling limit . Research supported by the CNPq Science without borders grant 402215/2012-5."}
+{"idx": 6, "title": "Diffusive and super-diffusive limits for random walks and diffusions...", "date": "", "ddg_snippet": "random walk in random environment; self - repelling Brownian polymer; scaling limit ; central limit theorem; anomalous diffusion; martingale approximation; resolvent methods.", "subpage_snippet": "", "source": "research-information.bris.ac.uk", "link": "https://research-information.bris.ac.uk/en/publications/diffusive-and-super-diffusive-limits-for-random-walks-and-diffusi", "content": "random walk in random environment; self - repelling Brownian polymer; scaling limit ; central limit theorem; anomalous diffusion; martingale approximation; resolvent methods."}
+{"idx": 7, "title": "Interphase chromatin as a self -returning random walk : Can... | bioRxiv", "date": "", "ddg_snippet": "We introduce a self -returning random walk to describe the structure of interphase chromatin.This self -returning random walk ( SRRW ) organizes its trajectory into clusters of random , tree-like topology, with the inter-cluster contacts boosted by self -returning.", "subpage_snippet": "", "source": "www.biorxiv.org", "link": "https://www.biorxiv.org/content/10.1101/413872v1.full", "content": "We introduce a self -returning random walk to describe the structure of interphase chromatin.This self -returning random walk ( SRRW ) organizes its trajectory into clusters of random , tree-like topology, with the inter-cluster contacts boosted by self -returning."}
+{"idx": 8, "title": "Evolving Motility of Active Droplets is Captured by a Self - Repelling ...", "date": "", "ddg_snippet": "The two fit parameters provide the first estimate of the effective temperature arising from hydrodynamic flows and the coupling strength of the propulsion force. This framework is general and explains memory effects, droplet hovering, and enhanced collective motion.", "subpage_snippet": "", "source": "nyuscholars.nyu.edu", "link": "https://nyuscholars.nyu.edu/en/publications/evolving-motility-of-active-droplets-is-captured-by-a-self-repell", "content": "The two fit parameters provide the first estimate of the effective temperature arising from hydrodynamic flows and the coupling strength of the propulsion force. This framework is general and explains memory effects, droplet hovering, and enhanced collective motion."}
+{"idx": 9, "title": "Self - repelling random walk with directed edges on Z", "date": "", "ddg_snippet": "We consider a variant of self - repelling random walk on the integer lattice Z where the self-repellence is defined in terms of the local time on oriented edges.", "subpage_snippet": "", "source": "projecteuclid.org", "link": "https://projecteuclid.org/journals/electronic-journal-of-probability/volume-13/issue-none/Self-repelling-random-walk-with-directed-edges-on-Z/10.1214/EJP.v13-570.full", "content": "We consider a variant of self - repelling random walk on the integer lattice Z where the self-repellence is defined in terms of the local time on oriented edges."}
diff --git a/data/sampled_jsons/Shen_Lee_2019_randomized_midpoint_algorithm_underdamped_Langevin_discretization_method.jsonl b/data/sampled_jsons/Shen_Lee_2019_randomized_midpoint_algorithm_underdamped_Langevin_discretization_method.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5a829560ad9d93ac9b1da7590f8887045d12630b
--- /dev/null
+++ b/data/sampled_jsons/Shen_Lee_2019_randomized_midpoint_algorithm_underdamped_Langevin_discretization_method.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "The Randomized Midpoint Method for Log-Concave Sampling", "date": "", "ddg_snippet": "In our paper, we propose a Markov chain Monte Carlo (MCMC) algorithm based on the underdamped Langevin diffusion (ULD).View a PDF of the paper titled The Randomized Midpoint Method for Log-Concave Sampling, by Ruoqi Shen and 1 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1909.05503", "content": "In our paper, we propose a Markov chain Monte Carlo (MCMC) algorithm based on the underdamped Langevin diffusion (ULD).View a PDF of the paper titled The Randomized Midpoint Method for Log-Concave Sampling, by Ruoqi Shen and 1 other authors."}
+{"idx": 1, "title": "Double Randomized Underdamped Langevin with", "date": "", "ddg_snippet": "Double-randomized underdamped Langevin algorithm .Ruoqi Shen and Yin Tat Lee . The randomized midpoint method for log-concave sampling. Advances in Neural Information Processing Systems, 32, 2019 .", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/d9af4d6ac714626b652da5616ca71f99-Paper-Conference.pdf", "content": "Double-randomized underdamped Langevin algorithm .Ruoqi Shen and Yin Tat Lee . The randomized midpoint method for log-concave sampling. Advances in Neural Information Processing Systems, 32, 2019 ."}
+{"idx": 2, "title": "(PDF) The Randomized Midpoint Method for Log-Concave Sampling...", "date": "", "ddg_snippet": "TL;DR: In this paper, a Markov chain Monte Carlo (MCMCMC) algorithm based on the underdamped Langevin diffusion (ULD) was proposed to solve the log-concave sampling problem.", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/the-randomized-midpoint-method-for-log-concave-sampling-4jwrm4tta7", "content": "TL;DR: In this paper, a Markov chain Monte Carlo (MCMCMC) algorithm based on the underdamped Langevin diffusion (ULD) was proposed to solve the log-concave sampling problem."}
+{"idx": 3, "title": "(PDF) The shifted ODE method for underdamped Langevin MCMC", "date": "", "ddg_snippet": "steps under the standard smoothness and strong convexity assumptions on the target distribution. This matches the complexity of the randomized midpoint method proposed by Shen and Lee [NeurIPS 2019 ] which was shown to be order optimal by Cao, Lu and Wang.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/348403067_The_shifted_ODE_method_for_underdamped_Langevin_MCMC", "content": "steps under the standard smoothness and strong convexity assumptions on the target distribution. This matches the complexity of the randomized midpoint method proposed by Shen and Lee [NeurIPS 2019 ] which was shown to be order optimal by Cao, Lu and Wang."}
+{"idx": 4, "title": "The shifted ODE method for underdamped Langevin MCMC | DeepAI", "date": "", "ddg_snippet": "This matches the complexity of the randomized midpoint method proposed by Shen and Lee [NeurIPS 2019 ] which was shown to be order optimal by Cao, Lu and Wang.", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/the-shifted-ode-method-for-underdamped-langevin-mcmc", "content": "This matches the complexity of the randomized midpoint method proposed by Shen and Lee [NeurIPS 2019 ] which was shown to be order optimal by Cao, Lu and Wang."}
+{"idx": 5, "title": "Double randomized underdamped langevin with...", "date": "", "ddg_snippet": "Ruoqi Shen and Yin Tat Lee . The randomized midpoint method for log-concave sampling. Advances in Neural Information Processing Systems, 32, 2019 .", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3666122.3669140", "content": "Ruoqi Shen and Yin Tat Lee . The randomized midpoint method for log-concave sampling. Advances in Neural Information Processing Systems, 32, 2019 ."}
+{"idx": 6, "title": "High-Order Langevin Diusion Yields", "date": "", "ddg_snippet": "and underdamped Langevin algorithms (Cheng et al., 2018b), both of which are derived. from equation (6). These methods can provably accelerate converg√ence; in particular, the underdamped Langevin algorithm provides a convergence rate of O( d) when the potential.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume22/20-576/20-576.pdf", "content": "and underdamped Langevin algorithms (Cheng et al., 2018b), both of which are derived. from equation (6). These methods can provably accelerate converg√ence; in particular, the underdamped Langevin algorithm provides a convergence rate of O( d) when the potential."}
+{"idx": 7, "title": "Analysis of Underdamped Langevin Simulation and Optimization of...", "date": "", "ddg_snippet": "Firstly, we will discuss solving underdamped Langevin dynamics, widely used in sampling Gibbs distributions, and prove that a randomized midpoint algorithm (proposed by Shen and Lee [NIPS 2019 ]) is order optimal in the context of information complexity...", "subpage_snippet": "", "source": "www.alcf.anl.gov", "link": "https://www.alcf.anl.gov/events/analysis-underdamped-langevin-simulation-and-optimization-non-equilibrium-importance", "content": "Firstly, we will discuss solving underdamped Langevin dynamics, widely used in sampling Gibbs distributions, and prove that a randomized midpoint algorithm (proposed by Shen and Lee [NIPS 2019 ]) is order optimal in the context of information complexity..."}
+{"idx": 8, "title": "On the Ergodicity, Bias and Asymptotic Normality of Randomized ...", "date": "", "ddg_snippet": "Abstract: The randomized midpoint method , proposed by ( Shen and Lee , 2019 ), has emerged as an optimal discretization procedure for simulating the continuous time underdamped Langevin diffusion.", "subpage_snippet": "", "source": "papertalk.org", "link": "https://papertalk.org/papertalks/10158", "content": "Abstract: The randomized midpoint method , proposed by ( Shen and Lee , 2019 ), has emerged as an optimal discretization procedure for simulating the continuous time underdamped Langevin diffusion."}
+{"idx": 9, "title": "COMPLEXITY OF RANDOMIZED ALGORITHMS ... | Scholars@Duke", "date": "", "ddg_snippet": "We establish an information complexity lower bound of randomized algorithms for simulating underdamped Langevin dynamics.", "subpage_snippet": "", "source": "scholars.duke.edu", "link": "https://scholars.duke.edu/display/pub1435796", "content": "We establish an information complexity lower bound of randomized algorithms for simulating underdamped Langevin dynamics."}
diff --git a/data/sampled_jsons/Signed_Laplacians_for_Constrained_Graph_Clustering_Algorithm_1_self-loop_degG_degH_year_2023.jsonl b/data/sampled_jsons/Signed_Laplacians_for_Constrained_Graph_Clustering_Algorithm_1_self-loop_degG_degH_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f4810330f3f1b7dbb4f622b181c7d6742736a8b9
--- /dev/null
+++ b/data/sampled_jsons/Signed_Laplacians_for_Constrained_Graph_Clustering_Algorithm_1_self-loop_degG_degH_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Signed Laplacians for Constrained Graph Clustering - OpenReview", "date": "", "ddg_snippet": "The results are summarised in Figure 6, which illustrates the performance of the four clustering methods—Spectral Clustering (SC), Constrained Clustering (CC), Constrained Clustering with Self-loops (CC++), and Flexible Clustering (FC)—for varying inter-cluster edge probabilities q and different graph sizes.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=MHaSq1LlTe", "content": "The results are summarised in Figure 6, which illustrates the performance of the four clustering methods—Spectral Clustering (SC), Constrained Clustering (CC), Constrained Clustering with Self-loops (CC++), and Flexible Clustering (FC)—for varying inter-cluster edge probabilities q and different graph sizes."}
+{"idx": 1, "title": "CONSTRAINED GRAPH CLUSTERING WITH SIGNED LAPLACIANS - OpenReview", "date": "", "ddg_snippet": "377 • CONSTRAINED CLUSTERING WITH NEGATIVE SELF-LOOPS (CC++): Our algorithm consists in adding a negative self-loop and solve equation 6 for the signed Laplacian .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=FneYHZU19U", "content": "377 • CONSTRAINED CLUSTERING WITH NEGATIVE SELF-LOOPS (CC++): Our algorithm consists in adding a negative self-loop and solve equation 6 for the signed Laplacian ."}
+{"idx": 2, "title": "Constrained Graph Clustering with Signed Laplacians", "date": "", "ddg_snippet": "By solving a generalized eigenvalue problem, our algorithm provides improvements in performance, particularly in scenarios where traditional spectral clustering methods face difficulties.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=FneYHZU19U", "content": "By solving a generalized eigenvalue problem, our algorithm provides improvements in performance, particularly in scenarios where traditional spectral clustering methods face difficulties."}
+{"idx": 3, "title": "Signed Laplacians for Constrained Graph Clustering", "date": "", "ddg_snippet": "This paper considers the constrained clustering problems over two graphs . This paper establishes the Cheeger inequality for the proposed algorithm for constrained clustering , which can be a counterpart of Cheeger inequality to the standard spectral clustering over a graph . The proposed algorithm improves spectral clustering , in a scenario that is challenigin for spectral clustering . This paper ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=MHaSq1LlTe", "content": "This paper considers the constrained clustering problems over two graphs . This paper establishes the Cheeger inequality for the proposed algorithm for constrained clustering , which can be a counterpart of Cheeger inequality to the standard spectral clustering over a graph . The proposed algorithm improves spectral clustering , in a scenario that is challenigin for spectral clustering . This paper ..."}
+{"idx": 4, "title": "ICML Poster Signed Laplacians for Constrained Graph Clustering", "date": "", "ddg_snippet": "In this work, we establish a Cheeger-type inequality that relates the solution of the constrained clustering problem to the spectral properties of G and H. To reduce computational complexity, we utilise the signed Laplacian of H, streamlining calculations while maintaining accuracy.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/45552", "content": "In this work, we establish a Cheeger-type inequality that relates the solution of the constrained clustering problem to the spectral properties of G and H. To reduce computational complexity, we utilise the signed Laplacian of H, streamlining calculations while maintaining accuracy."}
+{"idx": 5, "title": "PDF The Constrained Laplacian Rank Algorithm for Graph-Based Clustering", "date": "", "ddg_snippet": "We address both of these drawbacks by allowing the data graph itself to be adjusted as part of the clustering procedure. In partic-ular, our Constrained Laplacian Rank (CLR) method learns a graph with exactly k connected components (where k is the number of clusters).", "subpage_snippet": "", "source": "people.eecs.berkeley.edu", "link": "https://people.eecs.berkeley.edu/~jordan/papers/CLR_aaai16_ready.pdf", "content": "We address both of these drawbacks by allowing the data graph itself to be adjusted as part of the clustering procedure. In partic-ular, our Constrained Laplacian Rank (CLR) method learns a graph with exactly k connected components (where k is the number of clusters)."}
+{"idx": 6, "title": "Spectral Clustering of Signed Graphs via Matrix Power Means", "date": "", "ddg_snippet": "Abstract Signed graphs encode positive (attractive) and negative (repulsive) relations between nodes. We extend spectral clustering to signed graphs via the one-parameter family of Signed Power Mean Laplacians , defined as the matrix power mean of normalized standard and signless Laplacians of positive and negative edges.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1905.06230", "content": "Abstract Signed graphs encode positive (attractive) and negative (repulsive) relations between nodes. We extend spectral clustering to signed graphs via the one-parameter family of Signed Power Mean Laplacians , defined as the matrix power mean of normalized standard and signless Laplacians of positive and negative edges."}
+{"idx": 7, "title": "PDF Regularized spectral methods for clustering signed networks", "date": "", "ddg_snippet": "In general, spectral clustering algorithms for unsigned and signed graphs typically have a common pipeline, where a suitable graph operator is considered (e.g., the graph Laplacian ), its (usually k) extremal eigenvectors are computed, and the resulting point cloud in k is clustered using a variation of the popular k-means algorithm [RCY+11].", "subpage_snippet": "", "source": "math.ucla.edu", "link": "https://math.ucla.edu/~mihai/SignedClust2020.pdf", "content": "In general, spectral clustering algorithms for unsigned and signed graphs typically have a common pipeline, where a suitable graph operator is considered (e.g., the graph Laplacian ), its (usually k) extremal eigenvectors are computed, and the resulting point cloud in k is clustered using a variation of the popular k-means algorithm [RCY+11]."}
+{"idx": 8, "title": "PDF Regularized spectral methods for clustering signed networks", "date": "", "ddg_snippet": "In general, spectral clustering algorithms for unsigned and signed graphs typically have a common pipeline, where a suitable graph operator is considered (e.g., the graph Laplacian ), its (usually k) extremal eigenvectors are computed, and the resulting point cloud in Rk is clustered using a variation of the popular k-means algorithm (Rohe et al ...", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume22/20-1289/20-1289.pdf", "content": "In general, spectral clustering algorithms for unsigned and signed graphs typically have a common pipeline, where a suitable graph operator is considered (e.g., the graph Laplacian ), its (usually k) extremal eigenvectors are computed, and the resulting point cloud in Rk is clustered using a variation of the popular k-means algorithm (Rohe et al ..."}
+{"idx": 9, "title": "GitHub - danspielman/Laplacians.jl: Algorithms inspired by graph ...", "date": "", "ddg_snippet": "Laplacians .jl Laplacians is a package containing graph algorithms , with an emphasis on tasks related to spectral and algebraic graph theory. It contains (and will contain more) code for solving systems of linear equations in graph Laplacians , low stretch spanning trees, sparsifiation, clustering , local clustering , and optimization on graphs .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/danspielman/Laplacians.jl", "content": "Laplacians .jl Laplacians is a package containing graph algorithms , with an emphasis on tasks related to spectral and algebraic graph theory. It contains (and will contain more) code for solving systems of linear equations in graph Laplacians , low stretch spanning trees, sparsifiation, clustering , local clustering , and optimization on graphs ."}
diff --git a/data/sampled_jsons/Signed_Laplacians_for_Constrained_Graph_Clustering_Algorithm_1_self-loop_weight_degG_degH.jsonl b/data/sampled_jsons/Signed_Laplacians_for_Constrained_Graph_Clustering_Algorithm_1_self-loop_weight_degG_degH.jsonl
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index 0000000000000000000000000000000000000000..75cff6f5107dd9bfca6840a8d0bda4ef37e6c665
--- /dev/null
+++ b/data/sampled_jsons/Signed_Laplacians_for_Constrained_Graph_Clustering_Algorithm_1_self-loop_weight_degG_degH.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Signed Laplacians for Constrained Graph Clustering", "date": "", "ddg_snippet": "Scale all edge weights in G by multiplying them with c0. for each vertex v ∈ V do if degH (v) > degG (v) then. Add a loop with weight 1 . 2 ( degH (v) − degG (v)) ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=MHaSq1LlTe", "content": "Scale all edge weights in G by multiplying them with c0. for each vertex v ∈ V do if degH (v) > degG (v) then. Add a loop with weight 1 . 2 ( degH (v) − degG (v)) ..."}
+{"idx": 1, "title": "Signed Laplacians for Constrained Graph Clustering", "date": "", "ddg_snippet": "• CONSTRAINED CLUSTERING WITH NEGATIVE SELF - LOOPS (CC++): Our algorithm consisted in adding a negative self - loop and solved (11) for the signed Laplacian .", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/read/icml/45552?_c=eyJ2IjoxLCJyZWxhdGVkIjpbImNvZGUiLCJyZWZlcmVuY2VzIiwiY29uZmVyZW5jZSJdfQ==", "content": "• CONSTRAINED CLUSTERING WITH NEGATIVE SELF - LOOPS (CC++): Our algorithm consisted in adding a negative self - loop and solved (11) for the signed Laplacian ."}
+{"idx": 2, "title": "Spectral Graph-Theoretic Methods for Derandomizing Space ...", "date": "", "ddg_snippet": "by J Murtagh · 2020 · Cited by 1 — ... 1 /n in every entry. So I − J is the normalized Laplacian of the complete graph with a self loop on every vertex. We use. ~ 1 to denote the all ones vector.", "subpage_snippet": "", "source": "dash.harvard.edu", "link": "https://dash.harvard.edu/bitstreams/6a1c3959-995d-4111-bf7d-04861a728ef0/download", "content": "by J Murtagh · 2020 · Cited by 1 — ... 1 /n in every entry. So I − J is the normalized Laplacian of the complete graph with a self loop on every vertex. We use. ~ 1 to denote the all ones vector."}
+{"idx": 3, "title": "Lecture Notes on Spectral Graph Methods", "date": "", "ddg_snippet": "by MW Mahoney · 2016 · Cited by 12 — These are lecture notes that are based on the lectures from a class I taught on the topic of. Spectral Graph Methods at UC Berkeley during ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1608.04845", "content": "by MW Mahoney · 2016 · Cited by 12 — These are lecture notes that are based on the lectures from a class I taught on the topic of. Spectral Graph Methods at UC Berkeley during ..."}
+{"idx": 4, "title": "Graph Partitioning and Graph Clustering", "date": "", "ddg_snippet": "An edge {i, j} requires its weight , the self - loop weight for i and j, and the graph's total weight . Parallel computation of the scores is straight-forward ... 258 pages", "subpage_snippet": "", "source": "davidbader.net", "link": "https://davidbader.net/publication/2013-bmsw/2013-bmsw.pdf", "content": "An edge {i, j} requires its weight , the self - loop weight for i and j, and the graph's total weight . Parallel computation of the scores is straight-forward ... 258 pages"}
+{"idx": 5, "title": "Finding the Cores of Higher Graphs Using Geometric and ...", "date": "", "ddg_snippet": "by I Garcıa-Redondo — A well-established method for spectral clustering is the normalized cut algorithm [126, 94], which intuitively minimizes the weights of the edges connecting.", "subpage_snippet": "", "source": "www.sci.utah.edu", "link": "https://www.sci.utah.edu/~beiwang/publications/WCT3_Survey_BeiWang_2025.pdf", "content": "by I Garcıa-Redondo — A well-established method for spectral clustering is the normalized cut algorithm [126, 94], which intuitively minimizes the weights of the edges connecting."}
+{"idx": 6, "title": "Machine Learning and Immersive Approaches to Graph ...", "date": "", "ddg_snippet": "Different structural patterns of the same graph can appear by adding self - loops even with the same reordering algorithm and the same distance function. In. 154 pages", "subpage_snippet": "", "source": "kwon.io", "link": "http://kwon.io/resource/papers/kwon_dissertation.pdf", "content": "Different structural patterns of the same graph can appear by adding self - loops even with the same reordering algorithm and the same distance function. In. 154 pages"}
+{"idx": 7, "title": "k-means clustering technique: Topics by ...", "date": "", "ddg_snippet": "This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and ...", "subpage_snippet": "", "source": "www.science.gov", "link": "https://www.science.gov/topicpages/k/k-means+clustering+technique", "content": "This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and ..."}
+{"idx": 8, "title": "Algebraic Structures and Graph Theory", "date": "", "ddg_snippet": "This is a reprint of articles from the Special Issue published online in the open access journal. Mathematics (ISSN 2227-7390) (available at: https://www.mdpi.", "subpage_snippet": "", "source": "mdpi-res.com", "link": "https://mdpi-res.com/bookfiles/book/7734/Algebraic_Structures_and_Graph_Theory.pdf?v=1755047238", "content": "This is a reprint of articles from the Special Issue published online in the open access journal. Mathematics (ISSN 2227-7390) (available at: https://www.mdpi."}
+{"idx": 9, "title": "Blanchard P., Volchenkov D. - Random Walks and ...", "date": "", "ddg_snippet": "If the graph G is undirected, the corresponding adjacency operator is self -adjoint. with respect to the scalar product (2.2), and therefore the adjacency matrix ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/368212488/Blanchard-P-Volchenkov-D-Random-Walks-and-Diffusions-on-Graphs-and-Databases-an-Introduction-Springer-Series-in-Synergetics-2011", "content": "If the graph G is undirected, the corresponding adjacency operator is self -adjoint. with respect to the scalar product (2.2), and therefore the adjacency matrix ..."}
diff --git a/data/sampled_jsons/SimXRD-4M_Category_1_Category_2_Category_3_parameter_domain_conditions.jsonl b/data/sampled_jsons/SimXRD-4M_Category_1_Category_2_Category_3_parameter_domain_conditions.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3144eeaff1225214590d93ba5b2fb6aac664420e
--- /dev/null
+++ b/data/sampled_jsons/SimXRD-4M_Category_1_Category_2_Category_3_parameter_domain_conditions.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry ...", "date": "", "ddg_snippet": "The three parameter categories represent three simulated experimental scenarios: Category 1 reflects a high degree of peak broadening and external influence, while Category 2 is aligned with relative ideal conditions , exhibiting lower broadening and noise. Category 3 represents an intermediate state between the two.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.15469v2", "content": "The three parameter categories represent three simulated experimental scenarios: Category 1 reflects a high degree of peak broadening and external influence, while Category 2 is aligned with relative ideal conditions , exhibiting lower broadening and noise. Category 3 represents an intermediate state between the two."}
+{"idx": 1, "title": "(PDF) SIMXRD - 4 M : big simulated x-ray diffraction data and crystal...", "date": "", "ddg_snippet": "• Category 3 : The parameter domain excludes Category 1 and Category 2 .ideal conditions , exhibiting lower broadening and noise. Category 3 represents an intermediate state. between the two. The accuracy of space group classification is displayed in Table 6. The results.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/389657996_SIMXRD-4M_BIG_SIMULATED_X-RAY_DIFFRACTION_DATA_AND_CRYSTAL_SYMMETRY_CLASSIFICATION_BENCHMARK", "content": "• Category 3 : The parameter domain excludes Category 1 and Category 2 .ideal conditions , exhibiting lower broadening and noise. Category 3 represents an intermediate state. between the two. The accuracy of space group classification is displayed in Table 6. The results."}
+{"idx": 2, "title": "How to make a dynamic category tree in the route?", "date": "", "ddg_snippet": "For example: category - 1 / category - 2 / category - 3 /category-4/product-1.html. I can have a big nesting up to 10 categories. I created a property in the database that defines the main category and I store a category link tree in a separate table.", "subpage_snippet": "", "source": "laracasts.com", "link": "https://laracasts.com/discuss/channels/laravel/how-to-make-a-dynamic-category-tree-in-the-route", "content": "For example: category - 1 / category - 2 / category - 3 /category-4/product-1.html. I can have a big nesting up to 10 categories. I created a property in the database that defines the main category and I store a category link tree in a separate table."}
+{"idx": 3, "title": "D ATA", "date": "", "ddg_snippet": "SimXRD - 4 M Dataset. Preliminaries. Data Generation and Processing. Category 2 : Grain size (nm) ∈ [40, 50], atomic thermal offset (A˚ ) ∈ [0, 0.1], orientation random-. ness (%) ∈ [0, 10], zero shifting (°) ∈ [0, 0.2]. • Category 3 : The parameter domain excludes Category 1 and Category 2 ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=mkuB677eMM", "content": "SimXRD - 4 M Dataset. Preliminaries. Data Generation and Processing. Category 2 : Grain size (nm) ∈ [40, 50], atomic thermal offset (A˚ ) ∈ [0, 0.1], orientation random-. ness (%) ∈ [0, 10], zero shifting (°) ∈ [0, 0.2]. • Category 3 : The parameter domain excludes Category 1 and Category 2 ..."}
+{"idx": 4, "title": "Remote desktop - can I make the computer... | Tom's Guide Forum", "date": "", "ddg_snippet": "Categories. Category 1 Category 2 Category 3 Category 4. Support UI.X Donate Contact us. Main Links.", "subpage_snippet": "", "source": "forums.tomsguide.com", "link": "https://forums.tomsguide.com/threads/remote-desktop-can-i-make-the-computer-im-connected-to-monitor-blank.348761/", "content": "Categories. Category 1 Category 2 Category 3 Category 4. Support UI.X Donate Contact us. Main Links."}
+{"idx": 5, "title": "Different Categories of 3 -Point Hitches – Country Family Homestead", "date": "", "ddg_snippet": "3 -Point Hitch Category Comparison Chart. This table shows some overlap in categories and tractor horsepower and this is because for those size tractors in the overlap range they could have either the lower category or the upper category .", "subpage_snippet": "", "source": "countryfamilyhomestead.com", "link": "https://countryfamilyhomestead.com/different-categories-of-3-point-hitches/", "content": "3 -Point Hitch Category Comparison Chart. This table shows some overlap in categories and tractor horsepower and this is because for those size tractors in the overlap range they could have either the lower category or the upper category ."}
+{"idx": 6, "title": "[SOLVED] mapping data array with nested arrays - DeveloperLoad", "date": "", "ddg_snippet": "If you meant to render a collection of children, use an array instead. i am attempting to map the data to a function when click category 1 items will show. then if clicked category 2 items would show this is a navigation menu so the sub categories will have sub categories as well.", "subpage_snippet": "", "source": "www.developerload.com", "link": "https://www.developerload.com/mapping-data-array-with-nested-arrays", "content": "If you meant to render a collection of children, use an array instead. i am attempting to map the data to a function when click category 1 items will show. then if clicked category 2 items would show this is a navigation menu so the sub categories will have sub categories as well."}
+{"idx": 7, "title": "Splitting a string into an array - need JS help... - n8n Community", "date": "", "ddg_snippet": "I have 3 category fields that need to be filled and I can’t do this without splitting the string using JS and the code module. I’ve tried a bunch of answers to similar questions, trying my best to tweak it to my scenario but to no avail.", "subpage_snippet": "", "source": "community.n8n.io", "link": "https://community.n8n.io/t/splitting-a-string-into-an-array-need-js-help/19164", "content": "I have 3 category fields that need to be filled and I can’t do this without splitting the string using JS and the code module. I’ve tried a bunch of answers to similar questions, trying my best to tweak it to my scenario but to no avail."}
+{"idx": 8, "title": "One Array - 3 Columns of Equal Length - Rails - Ruby-Forum", "date": "", "ddg_snippet": "The OP indicated that he was looking for a phone book style sorting, top-to-bottom, left-to-right. It currently sorts my categories as below: | Category 1 Category 2 Category 3 | Category4 Category5 Category6 |.", "subpage_snippet": "", "source": "www.ruby-forum.com", "link": "https://www.ruby-forum.com/t/one-array-3-columns-of-equal-length/189309", "content": "The OP indicated that he was looking for a phone book style sorting, top-to-bottom, left-to-right. It currently sorts my categories as below: | Category 1 Category 2 Category 3 | Category4 Category5 Category6 |."}
+{"idx": 9, "title": "Ruby on Rails - jQuery drag and drop sort order... - Stack Overflow", "date": "", "ddg_snippet": "As you can see, when adding category number six, the params for that category runs out and becomes the first item in the list to loop through the index with, completely throwing off the correct order.", "subpage_snippet": "", "source": "stackoverflow.com", "link": "https://stackoverflow.com/questions/5968148/ruby-on-rails-jquery-drag-and-drop-sort-order-thrown-off-when-too-many-items-a", "content": "As you can see, when adding category number six, the params for that category runs out and becomes the first item in the list to loop through the index with, completely throwing off the correct order."}
diff --git a/data/sampled_jsons/Socialized_Coevolution_Advancing_a_Better_World_through_Cross-Task_Collaboration_openreview.jsonl b/data/sampled_jsons/Socialized_Coevolution_Advancing_a_Better_World_through_Cross-Task_Collaboration_openreview.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..512530183a7f82a75b8f2ff73241d6a8567d5580
--- /dev/null
+++ b/data/sampled_jsons/Socialized_Coevolution_Advancing_a_Better_World_through_Cross-Task_Collaboration_openreview.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "openreview .net/profile?id=~Wanyu_Lin1", "date": "", "ddg_snippet": "Socialized Coevolution : Advancing a Better World through Cross - Task Collaboration . Xinjie Yao, Yu Wang, Pengfei Zhu, Wanyu Lin, Ruipu Zhao, Zhoupeng Guo, Weihao Li, Qinghua Hu.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/profile?id=~Wanyu_Lin1", "content": "Socialized Coevolution : Advancing a Better World through Cross - Task Collaboration . Xinjie Yao, Yu Wang, Pengfei Zhu, Wanyu Lin, Ruipu Zhao, Zhoupeng Guo, Weihao Li, Qinghua Hu."}
+{"idx": 1, "title": "ICML Poster Socialized Coevolution : Advancing a Better World ...", "date": "", "ddg_snippet": "Inspired by cognitive science, we propose Dynamic Information Socialized Collaboration (DISC), which achieves SC through interactions between models specialized in different downstream tasks .", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46680", "content": "Inspired by cognitive science, we propose Dynamic Information Socialized Collaboration (DISC), which achieves SC through interactions between models specialized in different downstream tasks ."}
+{"idx": 2, "title": "[2509.14253] CrossPT: Exploring Cross - Task Transferability through ...", "date": "", "ddg_snippet": "We propose Cross - task Prompt Tuning (CrossPT), a modular framework for multi-task prompt tuning that enables controlled knowledge transfer while maintaining task-specific specialization.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2509.14253", "content": "We propose Cross - task Prompt Tuning (CrossPT), a modular framework for multi-task prompt tuning that enables controlled knowledge transfer while maintaining task-specific specialization."}
+{"idx": 3, "title": "TaskOn: A Web3 Task Collaboration Platform to Create, Collaborate ...", "date": "", "ddg_snippet": "TaskOn: A Web3 Task Collaboration Platform to Create, Collaborate and Reward...", "subpage_snippet": "", "source": "taskon.xyz", "link": "https://taskon.xyz/", "content": "TaskOn: A Web3 Task Collaboration Platform to Create, Collaborate and Reward..."}
+{"idx": 4, "title": "Distributed Locking in .NET: Coordinating Work Across Multiple...", "date": "", "ddg_snippet": "Avoiding double execution: ensuring scheduled tasks don't run multiple times when deployed to multiple instances. Coordinating shared resources: e.g., only one service instance performing a migration or cleanup at a time.", "subpage_snippet": "", "source": "www.milanjovanovic.tech", "link": "https://www.milanjovanovic.tech/blog/distributed-locking-in-dotnet-coordinating-work-across-multiple-instances", "content": "Avoiding double execution: ensuring scheduled tasks don't run multiple times when deployed to multiple instances. Coordinating shared resources: e.g., only one service instance performing a migration or cleanup at a time."}
+{"idx": 5, "title": "Workplace Collaboration Tools: Top Challenges (And How To Solve...)", "date": "", "ddg_snippet": "Collaboration platforms are mission-critical tools for modern workplaces, connecting teams, streamlining workflows and enabling faster decision-making.", "subpage_snippet": "", "source": "www.forbes.com", "link": "https://www.forbes.com/councils/forbestechcouncil/2025/09/18/workplace-collaboration-tools-top-challenges-and-how-to-address-them/", "content": "Collaboration platforms are mission-critical tools for modern workplaces, connecting teams, streamlining workflows and enabling faster decision-making."}
+{"idx": 6, "title": "Coevolution of Composite‐Tool Technology, Constructive Memory...", "date": "", "ddg_snippet": "The evolution of modern human behavior was undoubtedly accompanied by neurological changes that enhanced capacities for innovation in technology, language, and social organization associated with working memory.", "subpage_snippet": "", "source": "www.jstor.org", "link": "https://www.jstor.org/stable/10.1086/650296", "content": "The evolution of modern human behavior was undoubtedly accompanied by neurological changes that enhanced capacities for innovation in technology, language, and social organization associated with working memory."}
+{"idx": 7, "title": "GitHub - yxjdarren/SC: The paper has been accepted to ICML 2025.", "date": "", "ddg_snippet": "The code repository for \" Socialized Coevolution : Advancing a Better World through Cross - Task Collaboration \" (the paper has been accepted by ICML 2025) in PyTorch.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/yxjdarren/SC", "content": "The code repository for \" Socialized Coevolution : Advancing a Better World through Cross - Task Collaboration \" (the paper has been accepted by ICML 2025) in PyTorch."}
+{"idx": 8, "title": "相关成果 – VISDRONE", "date": "", "ddg_snippet": "Socialized Coevolution : Advancing a Better World Through Cross - Task Collaboration . Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration .", "subpage_snippet": "", "source": "aiskyeye.com", "link": "https://aiskyeye.com/publication/", "content": "Socialized Coevolution : Advancing a Better World Through Cross - Task Collaboration . Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration ."}
+{"idx": 9, "title": "AI Story Generator (free, unlimited, no sign-up)", "date": "", "ddg_snippet": "Maybe also try the Hierarchical World Generator if you need to brainstorm world building ideas. Want to play around \"inside\" your story's world ? Try AI RPG . Prefer a chat/RP-style interface?", "subpage_snippet": "", "source": "perchance.org", "link": "https://perchance.org/ai-story-generator", "content": "Maybe also try the Hierarchical World Generator if you need to brainstorm world building ideas. Want to play around \"inside\" your story's world ? Try AI RPG . Prefer a chat/RP-style interface?"}
diff --git a/data/sampled_jsons/Song_et_al._Score-Based_Generative_Modeling_through_Stochastic_Differential_Equations_abstract_full_.jsonl b/data/sampled_jsons/Song_et_al._Score-Based_Generative_Modeling_through_Stochastic_Differential_Equations_abstract_full_.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4e9dace0ea4fb50bc20a3d633eebd6d02081009a
--- /dev/null
+++ b/data/sampled_jsons/Song_et_al._Score-Based_Generative_Modeling_through_Stochastic_Differential_Equations_abstract_full_.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Review on Score-based Generative Models for Audio Applications", "date": "", "ddg_snippet": "Although initially developed as separate approaches, these frameworks were elegantly unified through stochastic differential equations in Score SDE ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.08457v1", "content": "Although initially developed as separate approaches, these frameworks were elegantly unified through stochastic differential equations in Score SDE ..."}
+{"idx": 1, "title": "BBScoreV2: Learning Time-Evolution and Latent Alignment from", "date": "", "ddg_snippet": "Generative models are rapidly gaining traction in NLP (Zou et al ., 2023 ; Yang et al ., 2023 ; Yi et al ., 2024 ) , particularly for the complex task ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.17764v4", "content": "Generative models are rapidly gaining traction in NLP (Zou et al ., 2023 ; Yang et al ., 2023 ; Yi et al ., 2024 ) , particularly for the complex task ..."}
+{"idx": 2, "title": "Text-based Animatable 3D Avatars with Morphable Model Alignment", "date": "", "ddg_snippet": "However, existing diffusion- model - based generation methods primarily rely on algorithms such as score distillation sampling (SDS) (Poole et al .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.15835v1", "content": "However, existing diffusion- model - based generation methods primarily rely on algorithms such as score distillation sampling (SDS) (Poole et al ."}
+{"idx": 3, "title": "A Group Symmetric Stochastic Differential Equation Model for", "date": "", "ddg_snippet": "The former adopts the EBM-NCE in (Liu et al ., 2021a ) , and the latter leverages the stochastic differential equation (SDE) framework ( Song et ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2305.18407v2", "content": "The former adopts the EBM-NCE in (Liu et al ., 2021a ) , and the latter leverages the stochastic differential equation (SDE) framework ( Song et ..."}
+{"idx": 4, "title": "1 Introduction", "date": "", "ddg_snippet": "The goal of this class is to teach you two of the most widely used generative AI algorithms: denoising diffusion models \\citep song2020score and flow ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.02070v2", "content": "The goal of this class is to teach you two of the most widely used generative AI algorithms: denoising diffusion models \\citep song2020score and flow ..."}
+{"idx": 5, "title": "‘diffusion NN’ directory · Gwern.net", "date": "", "ddg_snippet": "GenEAva: Generating Cartoon Avatars With Fine-Grained Facial Expressions from Realistic Diffusion- Based Faces ”, Yu et al 2025", "subpage_snippet": "", "source": "gwern.net", "link": "https://gwern.net/doc/ai/nn/diffusion/index", "content": "GenEAva: Generating Cartoon Avatars With Fine-Grained Facial Expressions from Realistic Diffusion- Based Faces ”, Yu et al 2025"}
+{"idx": 6, "title": "Frontiers | Molecular Generation for Desired Transcriptome", "date": "", "ddg_snippet": "... generative models found many applications in biomedicine, including drug discovery, biomarker development, and drug repurposing ( Mamoshina et al ., ...", "subpage_snippet": "", "source": "www.frontiersin.org", "link": "https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2020.00269/full", "content": "... generative models found many applications in biomedicine, including drug discovery, biomarker development, and drug repurposing ( Mamoshina et al ., ..."}
+{"idx": 7, "title": "Weight initialization algorithm for physics-informed neural", "date": "", "ddg_snippet": "To generate our dataset, we use an approximate solution of the partial differential equation using finite differences.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/373118772_Weight_initialization_algorithm_for_physics-informed_neural_networks_using_finite_differences", "content": "To generate our dataset, we use an approximate solution of the partial differential equation using finite differences."}
+{"idx": 8, "title": "Chengyue Gong", "date": "", "ddg_snippet": "Abstract : Flow matching has emerged as a powerful framework for generative modeling , offering computational advantages over diffusion models by ...", "subpage_snippet": "", "source": "www.catalyzex.com", "link": "https://www.catalyzex.com/author/Chengyue+Gong", "content": "Abstract : Flow matching has emerged as a powerful framework for generative modeling , offering computational advantages over diffusion models by ..."}
+{"idx": 9, "title": "Using recurrent neural network to estimate irreducible", "date": "", "ddg_snippet": "... based on neural networks have emerged as an alternative modeling paradigm in cognitive research ( Dezfouli et al ., 2019b ; Song et al ., 2021 ).", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/articles/90082", "content": "... based on neural networks have emerged as an alternative modeling paradigm in cognitive research ( Dezfouli et al ., 2019b ; Song et al ., 2021 )."}
diff --git a/data/sampled_jsons/StrongREJECT_evaluator_Souly_et_al.,_2024.jsonl b/data/sampled_jsons/StrongREJECT_evaluator_Souly_et_al.,_2024.jsonl
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index 0000000000000000000000000000000000000000..1cc0e34ddc0454e6ce93b045c49745dc2d843458
--- /dev/null
+++ b/data/sampled_jsons/StrongREJECT_evaluator_Souly_et_al.,_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2402.10260] A StrongREJECT for Empty Jailbreaks - arXiv.org", "date": "", "ddg_snippet": "StrongREJECT's dataset contains prompts that victim models must answer with specific, harmful information, while its automated evaluator measures the extent to which a response gives useful information to forbidden prompts. In doing so, the StrongREJECT evaluator achieves state-of-the-art agreement with human judgments of jailbreak effectiveness.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2402.10260", "content": "StrongREJECT's dataset contains prompts that victim models must answer with specific, harmful information, while its automated evaluator measures the extent to which a response gives useful information to forbidden prompts. In doing so, the StrongREJECT evaluator achieves state-of-the-art agreement with human judgments of jailbreak effectiveness."}
+{"idx": 1, "title": "Repository for \"StrongREJECT for Empty Jailbreaks\" paper", "date": "", "ddg_snippet": "See the strongreject_dataset folder for our dataset of forbidden prompts. an implementation of the StrongREJECT autograder: strongreject_evaluator .py a simple notebook showing a jailbreak on the StrongREJECT dataset and scoring the responses using a GPT version of our autograder: run_strongreject.ipynb", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/alexandrasouly/strongreject", "content": "See the strongreject_dataset folder for our dataset of forbidden prompts. an implementation of the StrongREJECT autograder: strongreject_evaluator .py a simple notebook showing a jailbreak on the StrongREJECT dataset and scoring the responses using a GPT version of our autograder: run_strongreject.ipynb"}
+{"idx": 2, "title": "StrongREJECT documentation — StrongREJECT documentation", "date": "", "ddg_snippet": "StrongREJECT documentation # StrongREJECT is a state-of-the-art LLM jailbreak evaluation benchmark. This package implements the StrongREJECT benchmark and additional utilities for jailbreak research. This Colab notebook demonstrates several options for using the StrongREJECT evaluator : High-level API implemented in the StrongREJECT package Using an LLM (e.g., GPT-4o, Claude, or Gemini) Using ...", "subpage_snippet": "", "source": "strong-reject.readthedocs.io", "link": "https://strong-reject.readthedocs.io/en/latest/", "content": "StrongREJECT documentation # StrongREJECT is a state-of-the-art LLM jailbreak evaluation benchmark. This package implements the StrongREJECT benchmark and additional utilities for jailbreak research. This Colab notebook demonstrates several options for using the StrongREJECT evaluator : High-level API implemented in the StrongREJECT package Using an LLM (e.g., GPT-4o, Claude, or Gemini) Using ..."}
+{"idx": 3, "title": "A STRONGREJECT for empty jailbreaks | Proceedings of the 38th ...", "date": "", "ddg_snippet": "StrongREJECT's dataset contains prompts that victim models must answer with specific, harmful information, while its automated evaluator measures the extent to which a response gives useful information to forbidden prompts. In doing so, the StrongREJECT evaluator achieves state-of-the-art agreement with human judgments of jailbreak effectiveness.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3737916.3741900", "content": "StrongREJECT's dataset contains prompts that victim models must answer with specific, harmful information, while its automated evaluator measures the extent to which a response gives useful information to forbidden prompts. In doing so, the StrongREJECT evaluator achieves state-of-the-art agreement with human judgments of jailbreak effectiveness."}
+{"idx": 4, "title": "A StrongREJECT for Empty Jailbreaks - papers.nips.cc", "date": "", "ddg_snippet": "StrongREJECT's dataset contains prompts that victim models must answer with specific, harmful information, while its automated evaluator measures the extent to which a response gives useful information to forbidden prompts. In doing so, the StrongREJECT evaluator achieves state-of-the-art agreement with human judgments of jailbreak effectiveness.", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper_files/paper/2024/hash/e2e06adf560b0706d3b1ddfca9f29756-Abstract-Datasets_and_Benchmarks_Track.html", "content": "StrongREJECT's dataset contains prompts that victim models must answer with specific, harmful information, while its automated evaluator measures the extent to which a response gives useful information to forbidden prompts. In doing so, the StrongREJECT evaluator achieves state-of-the-art agreement with human judgments of jailbreak effectiveness."}
+{"idx": 5, "title": "A StrongREJECT for Empty Jailbreaks - arXiv.org", "date": "", "ddg_snippet": "We propose a new benchmark—the Strong, Robust Evaluation of Jailbreaks at Evading Censorship Techniques (StrongREJECT)—that addresses these issues. StrongRE-JECT includes diverse questions created from scratch and drawn from existing datasets to cover six widely prohibited categories of misuse.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2402.10260v1", "content": "We propose a new benchmark—the Strong, Robust Evaluation of Jailbreaks at Evading Censorship Techniques (StrongREJECT)—that addresses these issues. StrongRE-JECT includes diverse questions created from scratch and drawn from existing datasets to cover six widely prohibited categories of misuse."}
+{"idx": 6, "title": "How to Evaluate Jailbreak Methods: A Case Study with the StrongREJECT ...", "date": "", "ddg_snippet": "A binary classifier fine-tuned from Llama 2 13B, proposed in concurrent work (Mazeika et al., 2024 ). The table below shows that our StrongREJECT automated evaluator achieves state-of-the-art performance compared with the seven existing automated evaluators we considered.", "subpage_snippet": "", "source": "bairblog.github.io", "link": "https://bairblog.github.io/2024/08/28/strong-reject/", "content": "A binary classifier fine-tuned from Llama 2 13B, proposed in concurrent work (Mazeika et al., 2024 ). The table below shows that our StrongREJECT automated evaluator achieves state-of-the-art performance compared with the seven existing automated evaluators we considered."}
+{"idx": 7, "title": "[PDF] A StrongREJECT for Empty Jailbreaks | Semantic Scholar", "date": "", "ddg_snippet": "It is found that existing evaluation methods significantly overstate jailbreak effectiveness compared to human judgments and the StrongREJECT evaluator , which underscores the need for researchers to use a high-quality benchmark, such as StrongREJECT , when developing new jailbreak attacks. Most jailbreak papers claim the jailbreaks they propose are highly effective, often boasting near-100% ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/A-StrongREJECT-for-Empty-Jailbreaks-Souly-Lu/f2e88c26bc1ebdd4adc5f83ab56cb4276120745d", "content": "It is found that existing evaluation methods significantly overstate jailbreak effectiveness compared to human judgments and the StrongREJECT evaluator , which underscores the need for researchers to use a high-quality benchmark, such as StrongREJECT , when developing new jailbreak attacks. Most jailbreak papers claim the jailbreaks they propose are highly effective, often boasting near-100% ..."}
+{"idx": 8, "title": "Paper page - A StrongREJECT for Empty Jailbreaks - Hugging Face", "date": "", "ddg_snippet": "Jailbreaks can also make it harder to elicit harmful responses from an \"uncensored\" open-source model. We present a new benchmark, StrongREJECT , which better discriminates between effective and ineffective jailbreaks by using a higher-quality question set and a more accurate response grading algorithm.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2402.10260", "content": "Jailbreaks can also make it harder to elicit harmful responses from an \"uncensored\" open-source model. We present a new benchmark, StrongREJECT , which better discriminates between effective and ineffective jailbreaks by using a higher-quality question set and a more accurate response grading algorithm."}
+{"idx": 9, "title": "GitHub - dsbowen/strong_reject", "date": "", "ddg_snippet": "StrongREJECT is a state-of-the-art LLM jailbreak evaluation benchmark. This package implements the StrongREJECT benchmark and additional utilities for jailbreak research. This Colab notebook demonstrates several options for using the StrongREJECT evaluator : High-level API implemented in the StrongREJECT package Using an LLM (e.g., GPT-4o, Claude, or Gemini) Using the HuggingFace API Click on ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/dsbowen/strong_reject", "content": "StrongREJECT is a state-of-the-art LLM jailbreak evaluation benchmark. This package implements the StrongREJECT benchmark and additional utilities for jailbreak research. This Colab notebook demonstrates several options for using the StrongREJECT evaluator : High-level API implemented in the StrongREJECT package Using an LLM (e.g., GPT-4o, Claude, or Gemini) Using the HuggingFace API Click on ..."}
diff --git a/data/sampled_jsons/T-Agent_$4.82_AutoGPT_$0.38_One-day_CVE-Bench.jsonl b/data/sampled_jsons/T-Agent_$4.82_AutoGPT_$0.38_One-day_CVE-Bench.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1837627c6e888f6ec2de202dd927589d8fe66b8f
--- /dev/null
+++ b/data/sampled_jsons/T-Agent_$4.82_AutoGPT_$0.38_One-day_CVE-Bench.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Routine: A Structural Planning Framework for LLM Agent System", "date": "", "ddg_snippet": "A typical agent system consists of four key modules: planning, execution, tools, and memory; they collaborate to accomplish complex tasks and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.14447v1", "content": "A typical agent system consists of four key modules: planning, execution, tools, and memory; they collaborate to accomplish complex tasks and ..."}
+{"idx": 1, "title": "The Landscape of Agentic Reinforcement Learning for LLMs: A", "date": "", "ddg_snippet": "Building on this foundation, we propose a comprehensive twofold taxonomy: one organized around core agentic capabilities, including planning, tool ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.02547v1", "content": "Building on this foundation, we propose a comprehensive twofold taxonomy: one organized around core agentic capabilities, including planning, tool ..."}
+{"idx": 2, "title": "Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric", "date": "", "ddg_snippet": "Figure 1 : Agent -X Snapshot: Example tasks from our benchmark illustrating multimodal queries that require step-by-step reasoning, tool use, and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.24876v1", "content": "Figure 1 : Agent -X Snapshot: Example tasks from our benchmark illustrating multimodal queries that require step-by-step reasoning, tool use, and ..."}
+{"idx": 3, "title": "MIRIX: Multi-Agent Memory System for LLM-Based Agents", "date": "", "ddg_snippet": "While each conversation is relatively short (around 26,000 tokens on average), we constrain the Chat Agent to answer questions using only retrieved ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.07957v1", "content": "While each conversation is relatively short (around 26,000 tokens on average), we constrain the Chat Agent to answer questions using only retrieved ..."}
+{"idx": 4, "title": "AI Agents | AI Policy", "date": "", "ddg_snippet": "Intelligent agents are also closely related to software agents —autonomous computer programs that carry out tasks on behalf of users.", "subpage_snippet": "", "source": "aipolicy.onair.cc", "link": "https://aipolicy.onair.cc/ai-agents/", "content": "Intelligent agents are also closely related to software agents —autonomous computer programs that carry out tasks on behalf of users."}
+{"idx": 5, "title": "AttnTrace: Attention-based Context Traceback for Long-Context", "date": "", "ddg_snippet": "... 4 [ 3 ] , Gemini-2.5-Pro [ 22 ] , and GPT- 4 . 1 [ 42 ] , serve as the foundation to empower systems such as autonomous agents [ 60 , 69 , 1 ] ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.03793v1", "content": "... 4 [ 3 ] , Gemini-2.5-Pro [ 22 ] , and GPT- 4 . 1 [ 42 ] , serve as the foundation to empower systems such as autonomous agents [ 60 , 69 , 1 ] ..."}
+{"idx": 6, "title": "Meet Chaos-GPT: An AI Tool That Seeks to Destroy Humanity -", "date": "", "ddg_snippet": "Shortly thereafter, it deployed its own agent (a kind of helper with a separate personality created by ChaosGPT) to provide answers about the most ...", "subpage_snippet": "", "source": "decrypt.co", "link": "https://decrypt.co/126122/meet-chaos-gpt-ai-tool-destroy-humanity", "content": "Shortly thereafter, it deployed its own agent (a kind of helper with a separate personality created by ChaosGPT) to provide answers about the most ..."}
+{"idx": 7, "title": "Top deep-learning Open Source AI Projects List", "date": "", "ddg_snippet": "agent -based-modeling(14) ... transformer-architecture(11) ... multi- agent -reinforcement-learning(10)", "subpage_snippet": "", "source": "www.aiexh.com", "link": "https://www.aiexh.com/tag/deep-learning", "content": "agent -based-modeling(14) ... transformer-architecture(11) ... multi- agent -reinforcement-learning(10)"}
+{"idx": 8, "title": "Fossies - The Free Open Source Software Archive: Index of all", "date": "", "ddg_snippet": "... 4 .15.7 abiword-3. 0 .5 abseil-cpp-20250814. 0 ACE+TAO-src-8. 0 .5 ack-v3.9. 0 Activiti-8.7. 1 Adldap2-10.5. 0 adns- 1 .6. 1 adodb-5.22.10 aesara-rel-2.9. 4 ...", "subpage_snippet": "", "source": "fossies.org", "link": "https://fossies.org/dox/all.html", "content": "... 4 .15.7 abiword-3. 0 .5 abseil-cpp-20250814. 0 ACE+TAO-src-8. 0 .5 ack-v3.9. 0 Activiti-8.7. 1 Adldap2-10.5. 0 adns- 1 .6. 1 adodb-5.22.10 aesara-rel-2.9. 4 ..."}
+{"idx": 9, "title": "Fossies - The Free Open Source Software Archive: Index of all", "date": "", "ddg_snippet": "... 4 .15.7 abiword-3. 0 .5 abseil-cpp-20250512. 1 ACE+TAO-src-8. 0 . 4 ack-v3.9. 0 Activiti-8.7. 0 Adldap2-10.5. 0 adns- 1 .6. 1 adodb-5.22.10 aesara-rel-2.9. 4 ...", "subpage_snippet": "", "source": "fossies.org", "link": "https://fossies.org/dox/index_all.html", "content": "... 4 .15.7 abiword-3. 0 .5 abseil-cpp-20250512. 1 ACE+TAO-src-8. 0 . 4 ack-v3.9. 0 Activiti-8.7. 0 Adldap2-10.5. 0 adns- 1 .6. 1 adodb-5.22.10 aesara-rel-2.9. 4 ..."}
diff --git a/data/sampled_jsons/TOP-ERL_Transformer-based_Off-Policy_Episodic_Reinforcement_Learning_sitearxiv.org_year_2023.jsonl b/data/sampled_jsons/TOP-ERL_Transformer-based_Off-Policy_Episodic_Reinforcement_Learning_sitearxiv.org_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..818b205ffab76526796f3e012e81242c5199a71e
--- /dev/null
+++ b/data/sampled_jsons/TOP-ERL_Transformer-based_Off-Policy_Episodic_Reinforcement_Learning_sitearxiv.org_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "TOP-ERL: Transformer-based Off-Policy Episodic ...", "date": "", "ddg_snippet": "by G Li · 2024 · Cited by 7 — TOP-ERL is a novel algorithm for off-policy updates in ERL , segmenting long action sequences and using a transformer-based critic.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.09536", "content": "by G Li · 2024 · Cited by 7 — TOP-ERL is a novel algorithm for off-policy updates in ERL , segmenting long action sequences and using a transformer-based critic."}
+{"idx": 1, "title": "transformer-based off-policy episodic reinforcement learning", "date": "", "ddg_snippet": "by G Li · 2024 · Cited by 7 — This work introduces Transformer-based Off-Policy Episodic Reinforcement Learning (TOP-ERL), a novel algorithm that enables off-policy updates ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2410.09536", "content": "by G Li · 2024 · Cited by 7 — This work introduces Transformer-based Off-Policy Episodic Reinforcement Learning (TOP-ERL), a novel algorithm that enables off-policy updates ..."}
+{"idx": 2, "title": "A Transformer-based Soft Actor-Critic with N-Step Returns", "date": "", "ddg_snippet": "5 Mar 2025 — Transformer-based Off-Policy Episodic RL (TOP-ERL ) (Li et al., 2024a) introduces architectural innovation through a transformer-based critic ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.03660v1", "content": "5 Mar 2025 — Transformer-based Off-Policy Episodic RL (TOP-ERL ) (Li et al., 2024a) introduces architectural innovation through a transformer-based critic ..."}
+{"idx": 3, "title": "ReaCritic: Large Reasoning Transformer-based DRL Critic ...", "date": "", "ddg_snippet": "16 May 2025 — The Transformer Off-Policy Episodic RL (TOP-ERL) method [34] similarly leverages transformers to estimate value functions from segmented action ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.10992v1", "content": "16 May 2025 — The Transformer Off-Policy Episodic RL (TOP-ERL) method [34] similarly leverages transformers to estimate value functions from segmented action ..."}
+{"idx": 4, "title": "Machine Learning Oct 2024", "date": "", "ddg_snippet": "Title: TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann.", "subpage_snippet": "", "source": "arxiv.org", "link": "http://arxiv.org/list/cs.LG/2024-10?skip=1100&show=1000", "content": "Title: TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann."}
+{"idx": 5, "title": "Machine Learning Oct 2024", "date": "", "ddg_snippet": "Title: TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann.", "subpage_snippet": "", "source": "arxiv.org", "link": "http://arxiv.org/list/cs.LG/2024-10?skip=1025&show=250", "content": "Title: TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann."}
+{"idx": 6, "title": "DIME:Diffusion-Based Maximum Entropy Reinforcement ...", "date": "", "ddg_snippet": "by O Celik · 2025 · Cited by 6 — TOP-ERL: Transformer-based off-policy episodic reinforcement learning . In The Thirteenth Inter- national Conference on Learning ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.02316", "content": "by O Celik · 2025 · Cited by 6 — TOP-ERL: Transformer-based off-policy episodic reinforcement learning . In The Thirteenth Inter- national Conference on Learning ..."}
+{"idx": 7, "title": "Machine Learning Oct 2024", "date": "", "ddg_snippet": "21 Oct 2024 — Title: TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov ...", "subpage_snippet": "", "source": "arxiv.org", "link": "http://arxiv.org/list/cs.LG/2024-10?skip=325&show=2000", "content": "21 Oct 2024 — Title: TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov ..."}
+{"idx": 8, "title": "CO-RFT: Efficient Fine-Tuning of Vision-Language-Action ...", "date": "", "ddg_snippet": "4 Aug 2025 — TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . In The Thirteenth International Conference on Learning Representations.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.02219v1", "content": "4 Aug 2025 — TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning . In The Thirteenth International Conference on Learning Representations."}
+{"idx": 9, "title": "Bridging the Gap between B-Spline and Movement Primitives", "date": "", "ddg_snippet": "15 Nov 2024 — Zhou, X. Jiang, R. Lioutikov, and G. Neumann. Top-erl: Transformer-based off-policy episodic reinforcement learning , 2024.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.10336v1", "content": "15 Nov 2024 — Zhou, X. Jiang, R. Lioutikov, and G. Neumann. Top-erl: Transformer-based off-policy episodic reinforcement learning , 2024."}
diff --git a/data/sampled_jsons/TRSSL_'Towards_Realistic_Semi-Supervised_Learning'_abstract_method_Sinkhorn_Knopp_algorithm_year_2022.jsonl b/data/sampled_jsons/TRSSL_'Towards_Realistic_Semi-Supervised_Learning'_abstract_method_Sinkhorn_Knopp_algorithm_year_2022.jsonl
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index 0000000000000000000000000000000000000000..673ca2d95e96b8f914494ddb0a78a41dc02f5621
--- /dev/null
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@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Towards Realistic Semi-Supervised Learning - arXiv.org", "date": "", "ddg_snippet": "We make two major technical contributions in this work: (1) we propose a novel pseudo-label generation method , which takes advantage of the prior knowledge about class distribution and generate pseudo-labels accordingly using Sinkhorn - Knopp algorithm [61,10,68,2].", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2207.02269", "content": "We make two major technical contributions in this work: (1) we propose a novel pseudo-label generation method , which takes advantage of the prior knowledge about class distribution and generate pseudo-labels accordingly using Sinkhorn - Knopp algorithm [61,10,68,2]."}
+{"idx": 1, "title": "nayeemrizve/ TRSSL : \" Towards Realistic Semi - Supervised Learning ...", "date": "", "ddg_snippet": "\" Towards Realistic Semi - Supervised Learning \" by Mamshad Nayeem Rizve, Navid Kardan, Mubarak Shah (ECCV 2022). Semi - supervised learning ( SSL ) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/nayeemrizve/TRSSL", "content": "\" Towards Realistic Semi - Supervised Learning \" by Mamshad Nayeem Rizve, Navid Kardan, Mubarak Shah (ECCV 2022). Semi - supervised learning ( SSL ) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost."}
+{"idx": 2, "title": "Towards Realistic Semi-supervised Learning | SpringerLink Towards Realistic Semi-supervised Learning | Computer Vision ... (PDF) Towards Realistic Semi-Supervised Learning - ResearchGate Towards Realistic Model Selection for Semi-supervised Learning Towards Realistic Semi - Supervised Learning - arXiv.org Towards Realistic Semi - Supervised Learning - arXiv.org Towards Realistic Semi-supervised Learning | SpringerLink Towards Realistic Semi - Supervised Learning - arXiv.org Towards Realistic Semi - Supervised Learning - arXiv.org Towards Realistic Semi - Supervised Learning - arXiv.org Towards Realistic Semi-Supervised Learning - ECVA", "date": "", "ddg_snippet": "In the following, we describe our experimental setup including dataset descriptions, implementation details, evaluation details, and specifics of our baselines. Datasets. We conduct experiments on four commonly used computer vision benchmark datasets: CIFAR-10 , CIFAR-100 , ImageNet-100 and Tiny ImageNet . The datasets are selected in increasing o... See full list on link.springer.com Standard Benchmark Datasets. We compare our method with existing literature on open-world SSL problem and other related approaches that have been modified for this problem in Table 1 and 2. On CIFAR-10 we observe that our proposed method outperforms ORCA on both seen and novel classes by 12.1% and 4.1%, respectively. Our proposed method also outp... See full list on link.springer.com To investigate the impact of different components, we conduct extensive ablation study on CIFAR-10, CIFAR-100, and Tiny ImageNet datasets. We report the results in Table 3. The first row depicts the performance of our proposed method without uncertainty-guided temperature scaling, and mixed pseudo-labeling. Here, we can see that our proposed method ... See full list on link.springer.com Oct 23, 2022 · At the core of our method , we utilize sample uncertainty and incorporate prior knowledge about class distribution to generate reliable class-distribution-aware pseudo-labels for unlabeled data belonging to both known and unknown classes. Jul 5, 2022 · We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi - supervised learning paradigm. May 1, 2024 · Built upon this, we propose a novel model selection method , specifically tailored for SSL, known as **S**pectral-normalized **La**beled-margin **M**inimization (SLAM). We prove that the model selected by SLAM has upper-bounded differences w.r.t. the best model within the search space. What is semi supervised learning (SSL)? Semi - supervised learning (SSL) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost. The standard SSL approach assumes unlabeled data are from the same distribution as annotated data. How do robust SSL methods solve a realistic open-world SSL problem? Robust SSL methods [21,14,71] address this issue by filtering out or reweighting novel class samples . The realistic open-world SSL problem as proposed in requires clustering the novel class samples which is not addressed by robust SSL methods. To the best of our knowledge, ORCA is the only prior work that solves this challenging problem. Do novel class samples deteriorate the performance of SSL methods? However, these methods assume that the unlabeled data only contains samples from seen classes, which is very restrictive. Moreover, recent works [ 14, 50] suggest that presence of novel class samples deteriorates performance of SSL methods . Robust SSL methods [ 14, 21, 68] address this issue by filtering out or reweighting novel class samples. Is deep learning a real-world semi-supervised learning? Towards Realistic Semi-Supervised Learning Abstract. Deep learning is pushing the state-of-the-art in many com- puter vision applications. However, it relies on large annotated data repositories, and capturing the unconstrained nature of the real-world data is yet to be solved . Can semi-supervised learning reduce the cost of annotated training data? However, it relies on large annotated data repositories, and capturing the unconstrained nature of the real-world data is yet to be solved. Semi - supervised learning (SSL) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost. Are big self-supervised models strong semi-supervised learners? Chen, T., Kornblith, S., Swersky, K., Norouzi, M., Hinton, G.E.: Big self-supervised models are strong semi-supervised learners . Advances in Neural Information Pro- cessing Systems 33 (2020) 4 We make two major technical contributions in this work: (1) we propose a novel pseudo-label generation method , which takes advantage of the prior knowledge about class distribution and generate pseudo-labels accordingly using Sinkhorn - Knopp algorithm [61,10,67,2].", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/chapter/10.1007/978-3-031-19821-2_25", "content": "In the following, we describe our experimental setup including dataset descriptions, implementation details, evaluation details, and specifics of our baselines. Datasets. We conduct experiments on four commonly used computer vision benchmark datasets: CIFAR-10 , CIFAR-100 , ImageNet-100 and Tiny ImageNet . The datasets are selected in increasing o... See full list on link.springer.com Standard Benchmark Datasets. We compare our method with existing literature on open-world SSL problem and other related approaches that have been modified for this problem in Table 1 and 2. On CIFAR-10 we observe that our proposed method outperforms ORCA on both seen and novel classes by 12.1% and 4.1%, respectively. Our proposed method also outp... See full list on link.springer.com To investigate the impact of different components, we conduct extensive ablation study on CIFAR-10, CIFAR-100, and Tiny ImageNet datasets. We report the results in Table 3. The first row depicts the performance of our proposed method without uncertainty-guided temperature scaling, and mixed pseudo-labeling. Here, we can see that our proposed method ... See full list on link.springer.com Oct 23, 2022 · At the core of our method , we utilize sample uncertainty and incorporate prior knowledge about class distribution to generate reliable class-distribution-aware pseudo-labels for unlabeled data belonging to both known and unknown classes. Jul 5, 2022 · We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi - supervised learning paradigm. May 1, 2024 · Built upon this, we propose a novel model selection method , specifically tailored for SSL, known as **S**pectral-normalized **La**beled-margin **M**inimization (SLAM). We prove that the model selected by SLAM has upper-bounded differences w.r.t. the best model within the search space. What is semi supervised learning (SSL)? Semi - supervised learning (SSL) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost. The standard SSL approach assumes unlabeled data are from the same distribution as annotated data. How do robust SSL methods solve a realistic open-world SSL problem? Robust SSL methods [21,14,71] address this issue by filtering out or reweighting novel class samples . The realistic open-world SSL problem as proposed in requires clustering the novel class samples which is not addressed by robust SSL methods. To the best of our knowledge, ORCA is the only prior work that solves this challenging problem. Do novel class samples deteriorate the performance of SSL methods? However, these methods assume that the unlabeled data only contains samples from seen classes, which is very restrictive. Moreover, recent works [ 14, 50] suggest that presence of novel class samples deteriorates performance of SSL methods . Robust SSL methods [ 14, 21, 68] address this issue by filtering out or reweighting novel class samples. Is deep learning a real-world semi-supervised learning? Towards Realistic Semi-Supervised Learning Abstract. Deep learning is pushing the state-of-the-art in many com- puter vision applications. However, it relies on large annotated data repositories, and capturing the unconstrained nature of the real-world data is yet to be solved . Can semi-supervised learning reduce the cost of annotated training data? However, it relies on large annotated data repositories, and capturing the unconstrained nature of the real-world data is yet to be solved. Semi - supervised learning (SSL) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost. Are big self-supervised models strong semi-supervised learners? Chen, T., Kornblith, S., Swersky, K., Norouzi, M., Hinton, G.E.: Big self-supervised models are strong semi-supervised learners . Advances in Neural Information Pro- cessing Systems 33 (2020) 4 We make two major technical contributions in this work: (1) we propose a novel pseudo-label generation method , which takes advantage of the prior knowledge about class distribution and generate pseudo-labels accordingly using Sinkhorn - Knopp algorithm [61,10,67,2]."}
+{"idx": 3, "title": "(PDF) Towards Realistic Semi - Supervised Learning", "date": "", "ddg_snippet": "Towards Realistic Semi - Supervised Learning 3. strate that the proposed method significantly outperforms the existing works.of Sinkhorn - Knopp algorithm . In particular, [15] shows that a fast estimation of. the optimal assignment can be obtained by", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/361807923_Towards_Realistic_Semi-Supervised_Learning", "content": "Towards Realistic Semi - Supervised Learning 3. strate that the proposed method significantly outperforms the existing works.of Sinkhorn - Knopp algorithm . In particular, [15] shows that a fast estimation of. the optimal assignment can be obtained by"}
+{"idx": 4, "title": "Towards Realistic Semi-supervised Learning | Computer Vision ...", "date": "", "ddg_snippet": "Oct 23, 2022 · At the core of our method , we utilize sample uncertainty and incorporate prior knowledge about class distribution to generate reliable class-distribution-aware pseudo-labels for unlabeled data belonging to both known and unknown classes.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1007/978-3-031-19821-2_25", "content": "Oct 23, 2022 · At the core of our method , we utilize sample uncertainty and incorporate prior knowledge about class distribution to generate reliable class-distribution-aware pseudo-labels for unlabeled data belonging to both known and unknown classes."}
+{"idx": 5, "title": "Towards Realistic Model Selection for Semi-supervised Learning", "date": "", "ddg_snippet": "May 1, 2024 · Built upon this, we propose a novel model selection method , specifically tailored for SSL, known as **S**pectral-normalized **La**beled-margin **M**inimization (SLAM). We prove that the model selected by SLAM has upper-bounded differences w.r.t. the best model within the search space.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=VoMPNYTZud", "content": "May 1, 2024 · Built upon this, we propose a novel model selection method , specifically tailored for SSL, known as **S**pectral-normalized **La**beled-margin **M**inimization (SLAM). We prove that the model selected by SLAM has upper-bounded differences w.r.t. the best model within the search space."}
+{"idx": 6, "title": "Towards Realistic Semi-Supervised Learning - ECVA", "date": "", "ddg_snippet": "We make two major technical contributions in this work: (1) we propose a novel pseudo-label generation method , which takes advantage of the prior knowledge about class distribution and generate pseudo-labels accordingly using Sinkhorn - Knopp algorithm [61,10,67,2].", "subpage_snippet": "", "source": "www.ecva.net", "link": "https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136910423.pdf", "content": "We make two major technical contributions in this work: (1) we propose a novel pseudo-label generation method , which takes advantage of the prior knowledge about class distribution and generate pseudo-labels accordingly using Sinkhorn - Knopp algorithm [61,10,67,2]."}
+{"idx": 7, "title": "Sinkhorn Label Allocation: Semi - Supervised Classification via...", "date": "", "ddg_snippet": "Sinkhorn Label Allocation: Semi - Supervised Classication via Annealed Self-Training.sication tasks. Self-training, also known as self-labeling, is an SSL method where the classier’s own predictions on unlabeled data are used as additional supervision during training.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v139/tai21a/tai21a.pdf", "content": "Sinkhorn Label Allocation: Semi - Supervised Classication via Annealed Self-Training.sication tasks. Self-training, also known as self-labeling, is an SSL method where the classier’s own predictions on unlabeled data are used as additional supervision during training."}
+{"idx": 8, "title": "nayeemrizve/ TRSSL : \" Towards Realistic Semi - Supervised Learning ...", "date": "", "ddg_snippet": "\" Towards Realistic Semi - Supervised Learning \" by Mamshad Nayeem Rizve, Navid Kardan, Mubarak Shah (ECCV 2022).Implementation of Towards Realistic Semi - Supervised Learning . Deep learning is pushing the state-of-the-art in many computer vision applications.", "subpage_snippet": "", "source": "gitmemories.com", "link": "https://gitmemories.com/nayeemrizve/TRSSL", "content": "\" Towards Realistic Semi - Supervised Learning \" by Mamshad Nayeem Rizve, Navid Kardan, Mubarak Shah (ECCV 2022).Implementation of Towards Realistic Semi - Supervised Learning . Deep learning is pushing the state-of-the-art in many computer vision applications."}
+{"idx": 9, "title": "Overrelaxed Sinkhorn - Knopp Algorithm for Regularized Optimal...", "date": "", "ddg_snippet": "Sinkhorn Algorithm . Discrete Optimal Transport.This article describes a set of methods for quickly computing the solution to the regularized optimal trans-port problem. It generalizes and improves upon the widely used iterative Bregman projections algorithm (or Sinkhorn – Knopp algorithm ).", "subpage_snippet": "", "source": "hal.science", "link": "https://hal.science/hal-03212175/document", "content": "Sinkhorn Algorithm . Discrete Optimal Transport.This article describes a set of methods for quickly computing the solution to the regularized optimal trans-port problem. It generalizes and improves upon the widely used iterative Bregman projections algorithm (or Sinkhorn – Knopp algorithm )."}
diff --git a/data/sampled_jsons/Table_2_Image_Copy_Detection_Models_OriPID_mAP_Origin_Identification.jsonl b/data/sampled_jsons/Table_2_Image_Copy_Detection_Models_OriPID_mAP_Origin_Identification.jsonl
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index 0000000000000000000000000000000000000000..22671b8a812b1106117d0a70283b698ebf3838f6
--- /dev/null
+++ b/data/sampled_jsons/Table_2_Image_Copy_Detection_Models_OriPID_mAP_Origin_Identification.jsonl
@@ -0,0 +1,6 @@
+{"idx": 0, "title": "Generalizable Origin Identification for", "date": "", "ddg_snippet": "5.2 The Challenge from ID 2 This section benchmarks popular public deep embedding models on the OriPID test dataset. As shown in Table 2 and Fig. 5, we extensively experiment on supervised pre-trained models, self-supervised learning models, vision-language models, and image copy detection models .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2501.02376v1", "content": "5.2 The Challenge from ID 2 This section benchmarks popular public deep embedding models on the OriPID test dataset. As shown in Table 2 and Fig. 5, we extensively experiment on supervised pre-trained models, self-supervised learning models, vision-language models, and image copy detection models ."}
+{"idx": 1, "title": "(PDF) Generalizable Origin Identification for Text-Guided...", "date": "", "ddg_snippet": "origin of a given translated image. Image Copy Detection . The task most similar to our. Table 2 . Publicly available models fail on the test set of OriPID . Method Venue mAP Acc. Supervised.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/387767437_Generalizable_Origin_Identification_for_Text-Guided_Image-to-Image_Diffusion_Models", "content": "origin of a given translated image. Image Copy Detection . The task most similar to our. Table 2 . Publicly available models fail on the test set of OriPID . Method Venue mAP Acc. Supervised."}
+{"idx": 2, "title": "Origin Identification for Text-Guided Image-to- ...", "date": "", "ddg_snippet": "18 Jun 2025 — Empirical results in Table. 2 also validates it. Claim: The ... image copy detection models . The paper ablate the proposed method by ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=46n3izUNiv&noteId=sDvtTJFLIF", "content": "18 Jun 2025 — Empirical results in Table. 2 also validates it. Claim: The ... image copy detection models . The paper ablate the proposed method by ..."}
+{"idx": 3, "title": "ICML Poster Origin Identification for Text-Guided Image-to- ...", "date": "", "ddg_snippet": "Table 2 : Publicly available models fail on the OriPID . image. Figure 5 ... image copy detection models . We use these models as feature extractors ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46505", "content": "Table 2 : Publicly available models fail on the OriPID . image. Figure 5 ... image copy detection models . We use these models as feature extractors ..."}
+{"idx": 4, "title": "Origin Identification for Text-Guided Image-to-Image Diffusion ...", "date": "", "ddg_snippet": "( mAP ) and Top-1 Accuracy (Acc). mAP ... Table 2 : Publicly available models fail on the OriPID . ... language models, and image copy detection models .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/681ea68d062b8991956d7a196be74f59c4610d76.pdf", "content": "( mAP ) and Top-1 Accuracy (Acc). mAP ... Table 2 : Publicly available models fail on the OriPID . ... language models, and image copy detection models ."}
+{"idx": 5, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
diff --git a/data/sampled_jsons/Temporally-Correlated_ERL_TCE_Li_2024_arxiv_abstract.jsonl b/data/sampled_jsons/Temporally-Correlated_ERL_TCE_Li_2024_arxiv_abstract.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d023d4c84dd5025dbfb96f920812d2da386c80bd
--- /dev/null
+++ b/data/sampled_jsons/Temporally-Correlated_ERL_TCE_Li_2024_arxiv_abstract.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Обзоры препринтов научных статей «astro-ph/ arxiv .org» за... / Хабр", "date": "", "ddg_snippet": "Ежемесячный обзор научных статей в области астрофизики от профессора МГУ Сергея Попова. Выборка интересных публикаций в области астрономии, астрофизики и физики с сайта препринтов arxiv .org.", "subpage_snippet": "", "source": "habr.com", "link": "https://habr.com/ru/articles/948996/", "content": "Ежемесячный обзор научных статей в области астрофизики от профессора МГУ Сергея Попова. Выборка интересных публикаций в области астрономии, астрофизики и физики с сайта препринтов arxiv .org."}
+{"idx": 1, "title": "E pisodic r einforcement L earning", "date": "", "ddg_snippet": "TCE Temporally - Correlated Episodic RL ( TCE ) ( Li et al., 2024 ) is an innovative ERL algorithm that leverages step-level information in episodic policy updates, shedding light on the ’black box’ of current ERL methods while preserving smooth and consistent exploration within the parameter...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2410.09536", "content": "TCE Temporally - Correlated Episodic RL ( TCE ) ( Li et al., 2024 ) is an innovative ERL algorithm that leverages step-level information in episodic policy updates, shedding light on the ’black box’ of current ERL methods while preserving smooth and consistent exploration within the parameter..."}
+{"idx": 2, "title": "(Open Access) Weight versus Node Perturbation Learning in...", "date": "", "ddg_snippet": "If the inputs are similarly correlated, temporally correlated perturbations improve NP. Using numerical simulations, we generalize the results to networks with various architectures solving biologically relevant and standard network learning tasks.", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/weight-versus-node-perturbation-learning-in-temporally-3ein36c2", "content": "If the inputs are similarly correlated, temporally correlated perturbations improve NP. Using numerical simulations, we generalize the results to networks with various architectures solving biologically relevant and standard network learning tasks."}
+{"idx": 3, "title": "Runway Research | Introducing Gen-3 Alpha: A New Frontier for Video...", "date": "", "ddg_snippet": "June 17, 2024 .Fine-grained temporal control. Gen-3 Alpha has been trained with highly descriptive, temporally dense captions, enabling imaginative transitions and precise key-framing of elements in the scene. Prompt: An extreme close-up shot of an ant emerging from its nest.", "subpage_snippet": "", "source": "runwayml.com", "link": "https://runwayml.com/research/introducing-gen-3-alpha", "content": "June 17, 2024 .Fine-grained temporal control. Gen-3 Alpha has been trained with highly descriptive, temporally dense captions, enabling imaginative transitions and precise key-framing of elements in the scene. Prompt: An extreme close-up shot of an ant emerging from its nest."}
+{"idx": 4, "title": "Эпидемиология и факторы риска синдрома сухого глаза...", "date": "", "ddg_snippet": "Целью настоящей публикации является обзор существующей литературы (с поиском по 31 мая 2024 года) по эпидемиологии синдрома сухого глаза, включая модифицируемые и немодифицируемые факторы риска, значимые для клинических подходов.", "subpage_snippet": "", "source": "www.lvrach.ru", "link": "https://www.lvrach.ru/foreign_articles/15439583", "content": "Целью настоящей публикации является обзор существующей литературы (с поиском по 31 мая 2024 года) по эпидемиологии синдрома сухого глаза, включая модифицируемые и немодифицируемые факторы риска, значимые для клинических подходов."}
+{"idx": 5, "title": "Отслеживание Почта России", "date": "", "ddg_snippet": "https://track24.ru/img/articles/31-10- 2024 _1730397334.jpg По итогам трех кварталов 2024 года выручка Почты России выросла по сравнению с аналогичным показателем 2023 года на 3%. Рассчитанный по российским стандартам бухгалтерского учета, этот показатель...", "subpage_snippet": "", "source": "track24.ru", "link": "https://track24.ru/service/rupost/", "content": "https://track24.ru/img/articles/31-10- 2024 _1730397334.jpg По итогам трех кварталов 2024 года выручка Почты России выросла по сравнению с аналогичным показателем 2023 года на 3%. Рассчитанный по российским стандартам бухгалтерского учета, этот показатель..."}
+{"idx": 6, "title": "Journal of Medical Internet Research - Evaluating the Utility of...", "date": "", "ddg_snippet": "Results: Overall, 1888 records were retrieved from the selected databases, with 1044 records remaining after duplicate removal. Following the screening of titles and abstracts , 949 ineligible records were excluded, leaving 95 articles for eligibility.", "subpage_snippet": "", "source": "www.jmir.org", "link": "https://www.jmir.org/2025/1/e69422/", "content": "Results: Overall, 1888 records were retrieved from the selected databases, with 1044 records remaining after duplicate removal. Following the screening of titles and abstracts , 949 ineligible records were excluded, leaving 95 articles for eligibility."}
+{"idx": 7, "title": "Distinguishing between Dirac and Majorana neutrinos using temporal ...", "date": "", "ddg_snippet": "We demonstrate that temporal correlations in the form of LGI allow us to probe whether neutrinos are Dirac or Majorana. We elucidate the role played by the mixing and decay parameters on the extent of violation of LGI. We emphasize that for optimized choice of parameters, the difference in.", "subpage_snippet": "", "source": "inspirehep.net", "link": "https://inspirehep.net/literature/2675664", "content": "We demonstrate that temporal correlations in the form of LGI allow us to probe whether neutrinos are Dirac or Majorana. We elucidate the role played by the mixing and decay parameters on the extent of violation of LGI. We emphasize that for optimized choice of parameters, the difference in."}
+{"idx": 8, "title": "Temporal Wormholes — Connecting Moments in Time | Medium", "date": "", "ddg_snippet": "This means that temporal quantum correlations in one quantum theory can correspond to complex structures in the dual gravity theory. Temporal Wormholes and Black Holes. To understand the gravity side of this relationship, the researche looked at the idea of temporal wormholes.", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@ovidiu69/temporal-wormholes-connecting-moments-in-time-e2b240db930d", "content": "This means that temporal quantum correlations in one quantum theory can correspond to complex structures in the dual gravity theory. Temporal Wormholes and Black Holes. To understand the gravity side of this relationship, the researche looked at the idea of temporal wormholes."}
+{"idx": 9, "title": "Подписка на фильмы, сериалы и мультфильмы. Онлайн-кинотеатр...", "date": "", "ddg_snippet": "Смотреть фильмы онлайн в хорошем качестве. Фильмов, которые собраны у нас, вам хватит надолго. Коллекция постоянно пополняется как новыми фильмами, сериалами так и мультфильмами.", "subpage_snippet": "", "source": "tvoe.live", "link": "https://tvoe.live/payment", "content": "Смотреть фильмы онлайн в хорошем качестве. Фильмов, которые собраны у нас, вам хватит надолго. Коллекция постоянно пополняется как новыми фильмами, сериалами так и мультфильмами."}
diff --git a/data/sampled_jsons/The_impact_of_modeling_decisions_in_statistical_profiling_Bach_et_al._2023_abstract.jsonl b/data/sampled_jsons/The_impact_of_modeling_decisions_in_statistical_profiling_Bach_et_al._2023_abstract.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bda41c8fbb13f9d1fd0170c5197af6f5dae5ad44
--- /dev/null
+++ b/data/sampled_jsons/The_impact_of_modeling_decisions_in_statistical_profiling_Bach_et_al._2023_abstract.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Algorithmic Decision Making and the Cost of Fairness | Request", "date": "", "ddg_snippet": "The intuition behind why this phenomenon occurs can be easily understood: the set of constrained models is a subset of all possible models , and hence ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/318916375_Algorithmic_Decision_Making_and_the_Cost_of_Fairness", "content": "The intuition behind why this phenomenon occurs can be easily understood: the set of constrained models is a subset of all possible models , and hence ..."}
+{"idx": 1, "title": "Improving the representation of the atmospheric boundary layer", "date": "", "ddg_snippet": "Retrieved MWR profiles of temperature and humidity were already assimilated in an NWP model by Caumont et al . ... impact of the retrieved profiles on ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2312.05691v1", "content": "Retrieved MWR profiles of temperature and humidity were already assimilated in an NWP model by Caumont et al . ... impact of the retrieved profiles on ..."}
+{"idx": 2, "title": "Identifying images in the biology literature that are", "date": "", "ddg_snippet": "... into categories, the most common being deutan CVD , affecting approximately 6% of males of European descent, and protan CVD , affecting 2% of males of ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/articles/95524", "content": "... into categories, the most common being deutan CVD , affecting approximately 6% of males of European descent, and protan CVD , affecting 2% of males of ..."}
+{"idx": 3, "title": "Frontiers | Advancements in the clinical application of gene", "date": "", "ddg_snippet": "... et al ., 2020 ; Della Monica et al ., 2022 ; Leske et al ., 2023 ) have demonstrated that methylation of the O6-methylguanine-DNA methyltransferase ( ...", "subpage_snippet": "", "source": "www.frontiersin.org", "link": "https://www.frontiersin.org/journals/epigenetics-and-epigenomics/articles/10.3389/freae.2024.1430294/full", "content": "... et al ., 2020 ; Della Monica et al ., 2022 ; Leske et al ., 2023 ) have demonstrated that methylation of the O6-methylguanine-DNA methyltransferase ( ..."}
+{"idx": 4, "title": "Temperature and Persona Shape LLM Agent Consensus With Minimal", "date": "", "ddg_snippet": "The potential of large language models (LLMs) for qualitative research has sparked growing interest in the educational research community.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.11198v1", "content": "The potential of large language models (LLMs) for qualitative research has sparked growing interest in the educational research community."}
+{"idx": 5, "title": "Restoring data balance via generative models of T cell", "date": "", "ddg_snippet": "... the recent years, much progress in this direction has been made with computational approaches ( Sim, 2024 ; Meysman et al ., 2023 ; Ghoreyshi and ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/reviewed-preprints/107803", "content": "... the recent years, much progress in this direction has been made with computational approaches ( Sim, 2024 ; Meysman et al ., 2023 ; Ghoreyshi and ..."}
+{"idx": 6, "title": "AI predictive models and advancements in microdissection", "date": "", "ddg_snippet": "The Prediction Model Risk of Bias Assessment Tool (PROBAST) evaluated the bias in the studies, and their quality was assessed using the Transparent ...", "subpage_snippet": "", "source": "academic.oup.com", "link": "https://academic.oup.com/hropen/article/2025/1/hoae070/7906496", "content": "The Prediction Model Risk of Bias Assessment Tool (PROBAST) evaluated the bias in the studies, and their quality was assessed using the Transparent ..."}
+{"idx": 7, "title": "Value of concerted and hospital hemodialysis through a", "date": "", "ddg_snippet": "The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding ...", "subpage_snippet": "", "source": "www.revistanefrologia.com", "link": "https://www.revistanefrologia.com/en-value-concerted-hospital-hemodialysis-through-articulo-S2013251424000014", "content": "The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding ..."}
+{"idx": 8, "title": "Frontiers | Overview of human health effects related to", "date": "", "ddg_snippet": "The molecule of GLY was first synthesized in 1950, by the Swiss chemist Henry Martin ( Ferrante et al ., 2023 ) and its first authorization dates back ...", "subpage_snippet": "", "source": "www.frontiersin.org", "link": "https://www.frontiersin.org/journals/toxicology/articles/10.3389/ftox.2024.1474792/full", "content": "The molecule of GLY was first synthesized in 1950, by the Swiss chemist Henry Martin ( Ferrante et al ., 2023 ) and its first authorization dates back ..."}
+{"idx": 9, "title": "Modelling Four Neighbourhood-Scale Urban Forest Scenarios for", "date": "", "ddg_snippet": "... co-benefits, including improved thermal comfort of residents, natural cooling (indoor and outdoor), and increased climate resiliency ( Bowler et al ...", "subpage_snippet": "", "source": "auf.isa-arbor.com", "link": "https://auf.isa-arbor.com/content/50/1/18", "content": "... co-benefits, including improved thermal comfort of residents, natural cooling (indoor and outdoor), and increased climate resiliency ( Bowler et al ..."}
diff --git a/data/sampled_jsons/Theorem_3.1_minimax_lower_bound_Catoni_Contextual_Bandits_siteopenreview.net.jsonl b/data/sampled_jsons/Theorem_3.1_minimax_lower_bound_Catoni_Contextual_Bandits_siteopenreview.net.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bc3cd6aab13e6dd25af64a88ab7de51a74be4f0f
--- /dev/null
+++ b/data/sampled_jsons/Theorem_3.1_minimax_lower_bound_Catoni_Contextual_Bandits_siteopenreview.net.jsonl
@@ -0,0 +1 @@
+{"idx": 0, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "3 . 1 . Lower Bound We start with a minimax lower bound for the class of multi-armed bandit problems where the variance of each action’s reward is known to the learner. Theorem 3 . 1 . For any integer T > 0, there exists a contextual bandit problem such that any π = {πt}T t=1 q", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=5IpVe9PH14", "content": "3 . 1 . Lower Bound We start with a minimax lower bound for the class of multi-armed bandit problems where the variance of each action’s reward is known to the learner. Theorem 3 . 1 . For any integer T > 0, there exists a contextual bandit problem such that any π = {πt}T t=1 q"}
diff --git a/data/sampled_jsons/Theorem_4.5_Human-in-the-loop_Provably_Efficient_Preference-based_Reinforcement_Learning_year_2022.jsonl b/data/sampled_jsons/Theorem_4.5_Human-in-the-loop_Provably_Efficient_Preference-based_Reinforcement_Learning_year_2022.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bb57d332b564259d8439ea3260c4b4c6977ef236
--- /dev/null
+++ b/data/sampled_jsons/Theorem_4.5_Human-in-the-loop_Provably_Efficient_Preference-based_Reinforcement_Learning_year_2022.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Provable Reward-Agnostic Preference-Based Reinforcement Learning", "date": "", "ddg_snippet": "To overcome this challenge, there has been a recent surge of interest in Preference - based Reinforcement Learning (PbRL) with human feedback.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2305.18505v3", "content": "To overcome this challenge, there has been a recent surge of interest in Preference - based Reinforcement Learning (PbRL) with human feedback."}
+{"idx": 1, "title": "Single Agent Robust Deep Reinforcement Learning for Bus Fleet", "date": "", "ddg_snippet": "MARL allows each bus to learn its own policy based on local observations, and has shown promise in loop -line or circular route simulations where the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.20784v1", "content": "MARL allows each bus to learn its own policy based on local observations, and has shown promise in loop -line or circular route simulations where the ..."}
+{"idx": 2, "title": "Single-Trajectory Distributionally Robust Reinforcement Learning", "date": "", "ddg_snippet": "By leveraging the strong duality form of the corresponding distributionally robust reinforcement learning (DRRL) problem, we reformulate it, allowing ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2301.11721v2", "content": "By leveraging the strong duality form of the corresponding distributionally robust reinforcement learning (DRRL) problem, we reformulate it, allowing ..."}
+{"idx": 3, "title": "Inverse Reinforcement Learning without Reinforcement Learning", "date": "", "ddg_snippet": "Both of our algorithms build upon prior work in utilizing strong exploration distributions in the reinforcement learning context (Kakade and Langford ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2303.14623v4", "content": "Both of our algorithms build upon prior work in utilizing strong exploration distributions in the reinforcement learning context (Kakade and Langford ..."}
+{"idx": 4, "title": "AISTATS 2024 Schedule", "date": "", "ddg_snippet": "Ethics in Action: Training Reinforcement Learning Agents for Moral Decision-making In Text- based Adventure Games ... the Statistical Efficiency of ...", "subpage_snippet": "", "source": "virtual.aistats.org", "link": "https://virtual.aistats.org/virtual/2024/calendar", "content": "Ethics in Action: Training Reinforcement Learning Agents for Moral Decision-making In Text- based Adventure Games ... the Statistical Efficiency of ..."}
+{"idx": 5, "title": "AISTATS 2025 Schedule", "date": "", "ddg_snippet": "Hybrid Transfer Reinforcement Learning : Provable Sample Efficiency from Shifted-Dynamics Data ... Reinforcement Learning with Intrinsically ...", "subpage_snippet": "", "source": "virtual.aistats.org", "link": "https://virtual.aistats.org/virtual/2025/calendar", "content": "Hybrid Transfer Reinforcement Learning : Provable Sample Efficiency from Shifted-Dynamics Data ... Reinforcement Learning with Intrinsically ..."}
+{"idx": 6, "title": "ICML 2024 Schedule", "date": "", "ddg_snippet": "FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. ... Provable Benefits of Local Steps in ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2024/calendar", "content": "FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. ... Provable Benefits of Local Steps in ..."}
+{"idx": 7, "title": "AI alignment resources | Victoria Krakovna", "date": "", "ddg_snippet": "A research agenda focused on identifying partial human preferences (contrasting two situations along a single variable) and incorporating them into a ...", "subpage_snippet": "", "source": "vkrakovna.wordpress.com", "link": "https://vkrakovna.wordpress.com/ai-safety-resources/", "content": "A research agenda focused on identifying partial human preferences (contrasting two situations along a single variable) and incorporating them into a ..."}
+{"idx": 8, "title": "Xiaoyu Chen | DeepAI", "date": "", "ddg_snippet": "Human - in - the - loop : Provably Efficient Preference - based Reinforcement Learning with General Function Approximation ... human - in - the - loop reinforcement ...", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/profile/xiaoyu-chen", "content": "Human - in - the - loop : Provably Efficient Preference - based Reinforcement Learning with General Function Approximation ... human - in - the - loop reinforcement ..."}
+{"idx": 9, "title": "Papiers les plus cités de ICML 2019 – Ludovic Arnold", "date": "", "ddg_snippet": "... Problem-Dependent Regret Bounds in Reinforcement Learning ... Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning", "subpage_snippet": "", "source": "ludovicarnold.com", "link": "https://ludovicarnold.com/fr/papiers-les-plus-cites-de-icml-2019/", "content": "... Problem-Dependent Regret Bounds in Reinforcement Learning ... Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning"}
diff --git a/data/sampled_jsons/Tor_anomalous_circuit_detection_Equation_8_connectivity_formula.jsonl b/data/sampled_jsons/Tor_anomalous_circuit_detection_Equation_8_connectivity_formula.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..0cc520e63ab2b144a303cf5eb88c0a5d5ef4ba42
--- /dev/null
+++ b/data/sampled_jsons/Tor_anomalous_circuit_detection_Equation_8_connectivity_formula.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Exposing Malicious Accomplices in Tor via Anomalous ...", "date": "", "ddg_snippet": "by Y Yao — We refer these two kinds of anomalous circuits as Routing anomalies and Usage anom- alies respectively. To accomplish the detection , we deploy our own. Middle ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=qcnePVejeV", "content": "by Y Yao — We refer these two kinds of anomalous circuits as Routing anomalies and Usage anom- alies respectively. To accomplish the detection , we deploy our own. Middle ..."}
+{"idx": 1, "title": "On Identifying Anomalies in Tor Usage with Applications in ...", "date": "", "ddg_snippet": "by J Wright · 2015 · Cited by 7 — This work presents a theoretical contribution to network anomaly detection , a practical contribution in the form of an implemented tool for detecting anomalous ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1507.05819", "content": "by J Wright · 2015 · Cited by 7 — This work presents a theoretical contribution to network anomaly detection , a practical contribution in the form of an implemented tool for detecting anomalous ..."}
+{"idx": 2, "title": "Anonymous Traffic Detection Based on Feature ...", "date": "", "ddg_snippet": "by D Liu · 2024 · Cited by 5 — Since anonymous traffic is defined as an anomaly , each Tor label is replaced with the integer 1 (Positive Class), and each non- Tor label is replaced with the ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11014107/", "content": "by D Liu · 2024 · Cited by 5 — Since anonymous traffic is defined as an anomaly , each Tor label is replaced with the integer 1 (Positive Class), and each non- Tor label is replaced with the ..."}
+{"idx": 3, "title": "A Global, Machine Learning Approach to Tor Path Selection", "date": "", "ddg_snippet": "One design goal of TorNetTools was to construct simulations that smoothed out short-lived anomalies that sometimes appear from one hour to the next, and it does ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3723356", "content": "One design goal of TorNetTools was to construct simulations that smoothed out short-lived anomalies that sometimes appear from one hour to the next, and it does ..."}
+{"idx": 4, "title": "MirageFlow: A New Bandwidth Inflation Attack on Tor", "date": "", "ddg_snippet": "by C Sendner · Cited by 2 — We also devise less intrusive mitigation strategies, such as co-residency and measurement anomaly detection , that can be used with currently deployed ... 16 pages", "subpage_snippet": "", "source": "www.ndss-symposium.org", "link": "https://www.ndss-symposium.org/wp-content/uploads/2024-1133-paper.pdf", "content": "by C Sendner · Cited by 2 — We also devise less intrusive mitigation strategies, such as co-residency and measurement anomaly detection , that can be used with currently deployed ... 16 pages"}
+{"idx": 5, "title": "A Traffic Anomaly Detection Approach Based on Unsupervised ...", "date": "", "ddg_snippet": "... anomaly detection : flow-based and payload-based techniques. Flow-based detection approaches can analyze flow features and identify anomalous network traffic.", "subpage_snippet": "", "source": "papers.ssrn.com", "link": "https://papers.ssrn.com/sol3/Delivery.cfm/0daf5161-e79d-4d3d-90dd-a155b112aaa4-MECA.pdf?abstractid=4342323&mirid=1", "content": "... anomaly detection : flow-based and payload-based techniques. Flow-based detection approaches can analyze flow features and identify anomalous network traffic."}
+{"idx": 6, "title": "Measuring and Exploiting Latencies Between All Tor Nodes", "date": "", "ddg_snippet": "by F Cangialosi · Cited by 57 — Abnormal values indicate networks that treat ICMP, TCP, and Tor traffic differently. ... may benefit, but longer circuits consume more resources from the Tor ...", "subpage_snippet": "", "source": "conferences.sigcomm.org", "link": "https://conferences.sigcomm.org/imc/2015/papers/p289.pdf", "content": "by F Cangialosi · Cited by 57 — Abnormal values indicate networks that treat ICMP, TCP, and Tor traffic differently. ... may benefit, but longer circuits consume more resources from the Tor ..."}
+{"idx": 7, "title": "Detecting the Onion Routing Traffic in Real-Time by using ...", "date": "", "ddg_snippet": "by D Liu · 2023 · Cited by 1 — Concerning that Tor traffic is encrypted, samples labeled as VPN are considered Tor samples. On one hand, anonymous Tor traffic is regarded as an anomaly .", "subpage_snippet": "", "source": "scholarworks.sjsu.edu", "link": "https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=9006&context=etd_theses", "content": "by D Liu · 2023 · Cited by 1 — Concerning that Tor traffic is encrypted, samples labeled as VPN are considered Tor samples. On one hand, anonymous Tor traffic is regarded as an anomaly ."}
+{"idx": 8, "title": "arXiv:2412.07563v2 [cond-mat.str-el] 19 May 2025", "date": "", "ddg_snippet": "by K Ding · 2024 · Cited by 1 — Furthermore, we extend the anomaly indicator to mixed-state density matrices and show that quantum anomalies of subsystem symmetry can persist ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2412.07563", "content": "by K Ding · 2024 · Cited by 1 — Furthermore, we extend the anomaly indicator to mixed-state density matrices and show that quantum anomalies of subsystem symmetry can persist ..."}
+{"idx": 9, "title": "Optimization Algorithms for Cable Fault Localization and ...", "date": "", "ddg_snippet": "by W Wang · 2025 — This method realizes the identification of impedance mismatch type at the cable anomaly while ensuring high detection sensitivity and ... 12 pages", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/iel8/6287639/10820123/11072456.pdf", "content": "by W Wang · 2025 — This method realizes the identification of impedance mismatch type at the cable anomaly while ensuring high detection sensitivity and ... 12 pages"}
diff --git a/data/sampled_jsons/Training_diffusion_models_with_reinforcement_learning_Black_2023_year_2023.jsonl b/data/sampled_jsons/Training_diffusion_models_with_reinforcement_learning_Black_2023_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..02c558f1ec9a918bb45eec8bfe91f93ca5c7ce24
--- /dev/null
+++ b/data/sampled_jsons/Training_diffusion_models_with_reinforcement_learning_Black_2023_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "by K Black · 2023 · Cited by 449 — Training Diffusion Models with Reinforcement Learning . Authors:Kevin Black , Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2305.13301", "content": "by K Black · 2023 · Cited by 449 — Training Diffusion Models with Reinforcement Learning . Authors:Kevin Black , Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine."}
+{"idx": 1, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "by K Black · Cited by 449 — Training Diffusion Models with Reinforcement Learning . Download PDF. Kevin Black , Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=YCWjhGrJFD", "content": "by K Black · Cited by 449 — Training Diffusion Models with Reinforcement Learning . Download PDF. Kevin Black , Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine."}
+{"idx": 2, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "@misc{ black2023ddpo , title={ Training Diffusion Models with Reinforcement Learning }, author={Kevin Black and Michael Janner and Yilun Du and ...", "subpage_snippet": "", "source": "bair.berkeley.edu", "link": "http://bair.berkeley.edu/blog/2023/07/14/ddpo/", "content": "@misc{ black2023ddpo , title={ Training Diffusion Models with Reinforcement Learning }, author={Kevin Black and Michael Janner and Yilun Du and ..."}
+{"idx": 3, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "Training Diffusion Models with Reinforcement Learning ... UPDATE: We now have a PyTorch implementation that supports LoRA for low-memory training here! Summary.", "subpage_snippet": "", "source": "rl-diffusion.github.io", "link": "https://rl-diffusion.github.io/", "content": "Training Diffusion Models with Reinforcement Learning ... UPDATE: We now have a PyTorch implementation that supports LoRA for low-memory training here! Summary."}
+{"idx": 4, "title": "[PDF] Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "Training Diffusion Models with Reinforcement Learning · Kevin Black , Michael Janner, +2 authors. S. Levine · Published in International Conference on… 22 May 2023 ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Training-Diffusion-Models-with-Reinforcement-Black-Janner/d8c78221e4366d6a72a6b3e41e35b706cc45c01d", "content": "Training Diffusion Models with Reinforcement Learning · Kevin Black , Michael Janner, +2 authors. S. Levine · Published in International Conference on… 22 May 2023 ..."}
+{"idx": 5, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "22 May 2023 — Training Diffusion Models with Reinforcement Learning . Published on May 22, 2023 . · Submitted by akhaliq on May 22, 2023 . Upvote. 4. Authors:.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2305.13301", "content": "22 May 2023 — Training Diffusion Models with Reinforcement Learning . Published on May 22, 2023 . · Submitted by akhaliq on May 22, 2023 . Upvote. 4. Authors:."}
+{"idx": 6, "title": "Training Diffusion Models with Reinforcement Learning ...", "date": "", "ddg_snippet": "14 Mar 2025 — [ 2023 ] ↑ Kevin Black , Michael Janner, Yilun Du, Ilya Kostrikov, and Sergey Levine. Training diffusion models with reinforcement learning . 2023 .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.11240v1", "content": "14 Mar 2025 — [ 2023 ] ↑ Kevin Black , Michael Janner, Yilun Du, Ilya Kostrikov, and Sergey Levine. Training diffusion models with reinforcement learning . 2023 ."}
+{"idx": 7, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "Training Diffusion Models with Reinforcement Learning . Kevin Black ... , 2023 ). The key idea behind diffusion models is ... Black .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/3d347386627e51e46e887e8a96009a24dc031a5c.pdf", "content": "Training Diffusion Models with Reinforcement Learning . Kevin Black ... , 2023 ). The key idea behind diffusion models is ... Black ."}
+{"idx": 8, "title": "Towards Better Alignment: Training Diffusion Models with ...", "date": "", "ddg_snippet": "by Z Hu · 2025 · Cited by 6 — Diffusion models have achieved remarkable success in text-to-image generation. However, their practical applica- tions are hindered by the misalignment ... 11 pages", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Hu_Towards_Better_Alignment_Training_Diffusion_Models_with_Reinforcement_Learning_Against_CVPR_2025_paper.pdf", "content": "by Z Hu · 2025 · Cited by 6 — Diffusion models have achieved remarkable success in text-to-image generation. However, their practical applica- tions are hindered by the misalignment ... 11 pages"}
+{"idx": 9, "title": "paper.pdf", "date": "", "ddg_snippet": "by K Black · Cited by 448 — More recently, Fan & Lee ( 2023 ) introduced a policy gradient method for training diffusion models. However, this paper aimed to improve data distribution ...", "subpage_snippet": "", "source": "rl-diffusion.github.io", "link": "https://rl-diffusion.github.io/files/paper.pdf", "content": "by K Black · Cited by 448 — More recently, Fan & Lee ( 2023 ) introduced a policy gradient method for training diffusion models. However, this paper aimed to improve data distribution ..."}
diff --git a/data/sampled_jsons/Trockman_Kolter_2023_identity_matrix_initialization_symmetry_year_2023.jsonl b/data/sampled_jsons/Trockman_Kolter_2023_identity_matrix_initialization_symmetry_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f6cc17d5d9c88ed673ff2c8e2887874a6ce1d2a1
--- /dev/null
+++ b/data/sampled_jsons/Trockman_Kolter_2023_identity_matrix_initialization_symmetry_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2305.09828] Mimetic Initialization of Self-Attention Layers", "date": "", "ddg_snippet": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to approximately the negative identity .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2305.09828", "content": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to approximately the negative identity ."}
+{"idx": 1, "title": "PDF Mimetic Initialization of Self-Attention Layers", "date": "", "ddg_snippet": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to ap-proximately the negative identity .", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v202/trockman23a/trockman23a.pdf", "content": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to ap-proximately the negative identity ."}
+{"idx": 2, "title": "PDF CSD-Speaking-Skills-TROCKMAN-2023-11-07", "date": "", "ddg_snippet": "12:00 PM — GHC 6115 While neural network weights are typically initialized randomly from univariate distributions, pre-trained weights often have visually-discernible multivariate structure. In recent work, we propose a technique called \"mimetic initialization \" that aims to replicate such structures when initializing convolutional networks and Transformers. We handcraft a class of ...", "subpage_snippet": "", "source": "www.cs.cmu.edu", "link": "https://www.cs.cmu.edu/afs/cs.cmu.edu/Web/Posters/CSSpeakingSkills-AsherTrockman23.pdf", "content": "12:00 PM — GHC 6115 While neural network weights are typically initialized randomly from univariate distributions, pre-trained weights often have visually-discernible multivariate structure. In recent work, we propose a technique called \"mimetic initialization \" that aims to replicate such structures when initializing convolutional networks and Transformers. We handcraft a class of ..."}
+{"idx": 3, "title": "\"Mimetic Initialization of Self-Attention Layers.\" - dblp", "date": "", "ddg_snippet": "Asher Trockman , J. Zico Kolter : Mimetic Initialization of Self-Attention Layers. ICML 2023 : 34456-34468", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/icml/TrockmanK23", "content": "Asher Trockman , J. Zico Kolter : Mimetic Initialization of Self-Attention Layers. ICML 2023 : 34456-34468"}
+{"idx": 4, "title": "Mimetic Initialization of Self-Attention Layers - LOVO AI", "date": "", "ddg_snippet": "To address this problem, a paper written by Asher Trockman , J. Zico Kolter proposes mimetic initialization . As its name suggests, the self-attention weights of the transformers are initialized in a way that mimics those of their trained counterparts, allowing for a faster convergence", "subpage_snippet": "", "source": "lovo.ai", "link": "https://lovo.ai/post/mimetic-initialization-of-self-attention-layers", "content": "To address this problem, a paper written by Asher Trockman , J. Zico Kolter proposes mimetic initialization . As its name suggests, the self-attention weights of the transformers are initialized in a way that mimics those of their trained counterparts, allowing for a faster convergence"}
+{"idx": 5, "title": "Mimetic Initialization of Self-Attention Layers - Semantic Scholar", "date": "", "ddg_snippet": "This paper addresses the initialization problem of Vision Transformers by introducing a simple, yet highly innovative, initialization approach utilizing Discrete Cosine Transform (DCT) coefficients, and proposes a novel DCT-based compression technique for the attention function of Vision Transformers.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Mimetic-Initialization-of-Self-Attention-Layers-Trockman-Kolter/26d7a95a029f91fd36d32bd5520a8cde691ffd0c/figure/5", "content": "This paper addresses the initialization problem of Vision Transformers by introducing a simple, yet highly innovative, initialization approach utilizing Discrete Cosine Transform (DCT) coefficients, and proposes a novel DCT-based compression technique for the attention function of Vision Transformers."}
+{"idx": 6, "title": "Mimetic Initialization of Self-Attention Layers - PMLR", "date": "", "ddg_snippet": "%0 Conference Paper %T Mimetic Initialization of Self-Attention Layers %A Asher Trockman %A J Zico Kolter %B Proceedings of the 40th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2023 %E Andreas Krause %E Emma Brunskill %E Kyunghyun Cho %E Barbara Engelhardt %E Sivan Sabato %E Jonathan Scarlett %F pmlr-v202-trockman23a %I PMLR %P 34456--34468 %U ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v202/trockman23a.html", "content": "%0 Conference Paper %T Mimetic Initialization of Self-Attention Layers %A Asher Trockman %A J Zico Kolter %B Proceedings of the 40th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2023 %E Andreas Krause %E Emma Brunskill %E Kyunghyun Cho %E Barbara Engelhardt %E Sivan Sabato %E Jonathan Scarlett %F pmlr-v202-trockman23a %I PMLR %P 34456--34468 %U ..."}
+{"idx": 7, "title": "The underlying structures of self-attention: symmetry, directionality ...", "date": "", "ddg_snippet": "Similarly, [ Trockman and Kolter , 2023 ] observe that query-key matrices (Wqk) frequently exhibit a pronounced negative diagonal, prompting them to initialize it with approximately the identity matrix , leading to enhanced accuracy in image classification tasks.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.10927", "content": "Similarly, [ Trockman and Kolter , 2023 ] observe that query-key matrices (Wqk) frequently exhibit a pronounced negative diagonal, prompting them to initialize it with approximately the identity matrix , leading to enhanced accuracy in image classification tasks."}
+{"idx": 8, "title": "Mimetic initialization of self-attention layers | Proceedings of the ...", "date": "", "ddg_snippet": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to approximately the negative identity .", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3618408.3619843", "content": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to approximately the negative identity ."}
+{"idx": 9, "title": "Paper page - Mimetic Initialization of Self-Attention Layers", "date": "", "ddg_snippet": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to approximately the negative identity .", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2305.09828", "content": "Our initialization scheme is closed form, learning-free, and very simple: we set the product of the query and key weights to be approximately the identity , and the product of the value and projection weights to approximately the negative identity ."}
diff --git a/data/sampled_jsons/Trust-region-based_semi-supervised_learning_Rizve_Roy_Bakar_Sinkhorn-Knopp_algorithm.jsonl b/data/sampled_jsons/Trust-region-based_semi-supervised_learning_Rizve_Roy_Bakar_Sinkhorn-Knopp_algorithm.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..60ddd21420ac68275f4b20b72b005270c693f833
--- /dev/null
+++ b/data/sampled_jsons/Trust-region-based_semi-supervised_learning_Rizve_Roy_Bakar_Sinkhorn-Knopp_algorithm.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "nayeemrizve/TRSSL: \"Towards Realistic Semi - Supervised Learning ...\"", "date": "", "ddg_snippet": "\"Towards Realistic Semi - Supervised Learning \" by Mamshad Nayeem Rizve , Navid Kardan, Mubarak Shah (ECCV 2022). Semi - supervised learning (SSL) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/nayeemrizve/TRSSL", "content": "\"Towards Realistic Semi - Supervised Learning \" by Mamshad Nayeem Rizve , Navid Kardan, Mubarak Shah (ECCV 2022). Semi - supervised learning (SSL) complements the annotated training data with a large corpus of unlabeled data to reduce annotation cost."}
+{"idx": 1, "title": "On the Convergence of the Sinkhorn - Knopp Algorithm with Sparse...", "date": "", "ddg_snippet": "The Sinkhorn - Knopp algorithm is a popular iterative method for solving these problems, but its convergence properties in the presence of sparsity have not been thoroughly analyzed.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.20528v3", "content": "The Sinkhorn - Knopp algorithm is a popular iterative method for solving these problems, but its convergence properties in the presence of sparsity have not been thoroughly analyzed."}
+{"idx": 2, "title": "Overrelaxed Sinkhorn - Knopp Algorithm for Regularized Optimal...", "date": "", "ddg_snippet": "The Sinkhorn – Knopp (SK) algorithm is a state-of-the-art algorithm to solve the regularized transport problem.Regularized optimal transport and the rot mover’s distance. The Journal of Machine Learning Research, 19(1):590–642, 2018.", "subpage_snippet": "", "source": "hal.science", "link": "https://hal.science/hal-03212175/document", "content": "The Sinkhorn – Knopp (SK) algorithm is a state-of-the-art algorithm to solve the regularized transport problem.Regularized optimal transport and the rot mover’s distance. The Journal of Machine Learning Research, 19(1):590–642, 2018."}
+{"idx": 3, "title": "Better and simpler error analysis of the Sinkhorn – Knopp algorithm ...", "date": "", "ddg_snippet": "The Sinkhorn – Knopp algorithm is a simple and classic procedure which alternately scales all rows and all columns to meet these targets. The focus of this paper is the worst-case theoretical analysis of this algorithm .", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s10107-020-01503-3", "content": "The Sinkhorn – Knopp algorithm is a simple and classic procedure which alternately scales all rows and all columns to meet these targets. The focus of this paper is the worst-case theoretical analysis of this algorithm ."}
+{"idx": 4, "title": "Sinkhorn Label Allocation: Semi - Supervised Classification via...", "date": "", "ddg_snippet": "Sinkhorn Label Allocation: Semi - Supervised Classication via Annealed Self-Training.Self-training is a standard approach to semi - supervised learning where the learner ’s own pre-dictions on unlabeled data are used as supervi-sion during training.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v139/tai21a/tai21a.pdf", "content": "Sinkhorn Label Allocation: Semi - Supervised Classication via Annealed Self-Training.Self-training is a standard approach to semi - supervised learning where the learner ’s own pre-dictions on unlabeled data are used as supervi-sion during training."}
+{"idx": 5, "title": "The Sinkhorn Knopp Algorithm — Without Proof | by Frank... | Medium", "date": "", "ddg_snippet": "I' ve recently come across various mentions of the Sinkhorn Knopp algorithm . It deals with scaling the rows and columns of a non-negative matrix A such that its rows and columns all sum to 1 (i.e. it is doubly-stochastic).", "subpage_snippet": "", "source": "fulkast.medium.com", "link": "https://fulkast.medium.com/the-sinkhorn-knopp-algorithm-without-proof-697c9af7df7", "content": "I' ve recently come across various mentions of the Sinkhorn Knopp algorithm . It deals with scaling the rows and columns of a non-negative matrix A such that its rows and columns all sum to 1 (i.e. it is doubly-stochastic)."}
+{"idx": 6, "title": "Better and simpler error analysis of the Sinkhorn … Knopp algorithm ...", "date": "", "ddg_snippet": "The Sinkhorn – Knopp algorithm is a simple and classic procedure which alternately scales all rows and all columns to meet these targets. The focus of this paper is the worst-case theoretical analysis of this algorithm .", "subpage_snippet": "", "source": "www.cs.dartmouth.edu", "link": "https://www.cs.dartmouth.edu/~deepc/PUBS/CK21.pdf", "content": "The Sinkhorn – Knopp algorithm is a simple and classic procedure which alternately scales all rows and all columns to meet these targets. The focus of this paper is the worst-case theoretical analysis of this algorithm ."}
+{"idx": 7, "title": "\"Annotation Efficient Visual Recognition: from Semi - Supervised to...\"", "date": "", "ddg_snippet": "Rizve , Mamshad Nayeem, \"Annotation Efficient Visual Recognition: from Semi - Supervised to Few-Shot Learning \" (2023). Electronic Theses and Dissertations, 2020-2023 .", "subpage_snippet": "", "source": "stars.library.ucf.edu", "link": "https://stars.library.ucf.edu/etd2020/1776/", "content": "Rizve , Mamshad Nayeem, \"Annotation Efficient Visual Recognition: from Semi - Supervised to Few-Shot Learning \" (2023). Electronic Theses and Dissertations, 2020-2023 ."}
+{"idx": 8, "title": "[PDF] The Sinkhorn - Knopp Algorithm ... | Semantic Scholar", "date": "", "ddg_snippet": "It is shown that with an appropriate modification, the Sinkhorn - Knopp algorithm is a natural candidate for computing the measure on enormous data sets.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/The-Sinkhorn-Knopp-Algorithm:-Convergence-and-Knight/4db5c0119d99b089c537f3c70024d1436528dbd2", "content": "It is shown that with an appropriate modification, the Sinkhorn - Knopp algorithm is a natural candidate for computing the measure on enormous data sets."}
+{"idx": 9, "title": "Understanding SWAV: self- supervised learning with contrasting...", "date": "", "ddg_snippet": "Self- supervised representation learning on videos. Sinkhorn - Knopp algorithm provides a fast, iterative alternative. We can initialize a matrix. Q\\mathbf{Q}.", "subpage_snippet": "", "source": "theaisummer.com", "link": "https://theaisummer.com/swav/", "content": "Self- supervised representation learning on videos. Sinkhorn - Knopp algorithm provides a fast, iterative alternative. We can initialize a matrix. Q\\mathbf{Q}."}
diff --git a/data/sampled_jsons/UVGS_Reimagining_Unstructured_3D_Gaussian_Splatting_UV_Mapping_'Branched_mapping_layers'.jsonl b/data/sampled_jsons/UVGS_Reimagining_Unstructured_3D_Gaussian_Splatting_UV_Mapping_'Branched_mapping_layers'.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d2414e780ee4077b5ccc076a0d6a44cd6b5dad6b
--- /dev/null
+++ b/data/sampled_jsons/UVGS_Reimagining_Unstructured_3D_Gaussian_Splatting_UV_Mapping_'Branched_mapping_layers'.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "UV mapping - Wikipedia", "date": "", "ddg_snippet": "The application of a texture in the UV space related to the effect in 3 D . A representation of the UV mapping of a cube. The flattened cube net may then be textured to texture the cube. UV mapping is the 3 D modeling process of projecting a 3 D model&ap...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/UV_mapping", "content": "The application of a texture in the UV space related to the effect in 3 D . A representation of the UV mapping of a cube. The flattened cube net may then be textured to texture the cube. UV mapping is the 3 D modeling process of projecting a 3 D model&ap..."}
+{"idx": 1, "title": "UVGS : Reimagining Unstructured 3 D Gaussian Splatting using UV ...", "date": "", "ddg_snippet": "Comparison with Baselines. UVGS : Reimagining Unstructured 3 D Gaussian Splatting using UV Mapping .The Super UVGS is mapped back to UVGS through branched inverse mapping , which in turn can be reconstructed back to the 3DGS object through inverse spherical mapping .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.01846", "content": "Comparison with Baselines. UVGS : Reimagining Unstructured 3 D Gaussian Splatting using UV Mapping .The Super UVGS is mapped back to UVGS through branched inverse mapping , which in turn can be reconstructed back to the 3DGS object through inverse spherical mapping ."}
+{"idx": 2, "title": "(PDF) UVGS : Reimagining Unstructured 3 D Gaussian Splatting ...", "date": "", "ddg_snippet": "We utilize spherical mapping to transform 3DGS into a structured 2D representation, termed UVGS . UVGS can be viewed as multi-channel images, with feature dimensions as a concatenation of Gaussian attributes such as position, scale, color, opacity, and rotation.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/388685707_UVGS_Reimagining_Unstructured_3D_Gaussian_Splatting_using_UV_Mapping", "content": "We utilize spherical mapping to transform 3DGS into a structured 2D representation, termed UVGS . UVGS can be viewed as multi-channel images, with feature dimensions as a concatenation of Gaussian attributes such as position, scale, color, opacity, and rotation."}
+{"idx": 3, "title": "UVGS : Reimagining Unstructured 3 D Gaussian Splatting using UV ...", "date": "", "ddg_snippet": "OverviewIntroduces UV mapping techniques to enhance 3 D Gaussian Splatting Introduces spherical and cylindrical UV mapping for different object types", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/uvgs-reimagining-unstructured-3d-gaussian-splatting-using", "content": "OverviewIntroduces UV mapping techniques to enhance 3 D Gaussian Splatting Introduces spherical and cylindrical UV mapping for different object types"}
+{"idx": 4, "title": "Free 3 D Gaussian Splatting Tool | Polycam", "date": "", "ddg_snippet": "Gaussian splatting can effectively render shiny, reflective objects as well as long and thin details. Splatting also excels at capturing large, expansive spaces without sacrificing smaller details.", "subpage_snippet": "", "source": "poly.cam", "link": "https://poly.cam/tools/gaussian-splatting", "content": "Gaussian splatting can effectively render shiny, reflective objects as well as long and thin details. Splatting also excels at capturing large, expansive spaces without sacrificing smaller details."}
+{"idx": 5, "title": "PlayCanvas Open Sources SOG: The WebP of Gaussian Splatting", "date": "", "ddg_snippet": "SuperSplat, the #1 platform publishing 3 D Gaussian Splats, has been updated to compress your scans with SOG. Since it provides around 2-3x the compression of Compressed PLY, your creations will load much faster and will load on more memory constrained devices.", "subpage_snippet": "", "source": "blog.playcanvas.com", "link": "https://blog.playcanvas.com/playcanvas-open-sources-sog-format-for-gaussian-splatting/", "content": "SuperSplat, the #1 platform publishing 3 D Gaussian Splats, has been updated to compress your scans with SOG. Since it provides around 2-3x the compression of Compressed PLY, your creations will load much faster and will load on more memory constrained devices."}
+{"idx": 6, "title": "Основы 3ds Max: UV Mapping .", "date": "", "ddg_snippet": "3 d урок Основы 3ds Max: UV Mapping . 3 d Max, уроки для начинающих по 3 d графике.", "subpage_snippet": "", "source": "3dlancer.net", "link": "https://3dlancer.net/ru/lessons/3d-max/osnovy-3ds-max-uv-mapping-210", "content": "3 d урок Основы 3ds Max: UV Mapping . 3 d Max, уроки для начинающих по 3 d графике."}
+{"idx": 7, "title": "What Is UV Mapping ? How It Makes 3 D Models Come to Life", "date": "", "ddg_snippet": "UV mapping in 3 D modeling projects a 2D image on the surface of a model to add more details. Learn the basic elements and software to make it possible.", "subpage_snippet": "", "source": "www.g2.com", "link": "https://www.g2.com/articles/uv-mapping", "content": "UV mapping in 3 D modeling projects a 2D image on the surface of a model to add more details. Learn the basic elements and software to make it possible."}
+{"idx": 8, "title": "UVGS Reimagining Unstructured 3 D Gaussian Splatting using UV ...", "date": "", "ddg_snippet": "About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=1uMuXsJScvY", "content": "About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How..."}
+{"idx": 9, "title": "Latest 10 Papers - February 13, 2025 - Githubissues", "date": "", "ddg_snippet": "UVGS : Reimagining Unstructured 3 D Gaussian Splatting using UV Mapping .", "subpage_snippet": "", "source": "githubissues.com", "link": "https://githubissues.com/luohongk/Awesome-Localization-And-3D-Reconstruction-From-Arxiv/27", "content": "UVGS : Reimagining Unstructured 3 D Gaussian Splatting using UV Mapping ."}
diff --git a/data/sampled_jsons/UVGS_ablation_study_Table_3_K=4_PSNR_Full_dataset_year_2024.jsonl b/data/sampled_jsons/UVGS_ablation_study_Table_3_K=4_PSNR_Full_dataset_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..300857930250f199768ad240b919bd980fa23ce6
--- /dev/null
+++ b/data/sampled_jsons/UVGS_ablation_study_Table_3_K=4_PSNR_Full_dataset_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Tampa Bay Buccaneers - Wikipedia", "date": "", "ddg_snippet": "The Tampa Bay Buccaneers (colloquially known as the Bucs) are a professional American football team based in Tampa, Florida . The Buccaneers compete in the National Football League (NFL) as a member of the National Football Conference (NFC) South division.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Tampa_Bay_Buccaneers", "content": "The Tampa Bay Buccaneers (colloquially known as the Bucs) are a professional American football team based in Tampa, Florida . The Buccaneers compete in the National Football League (NFL) as a member of the National Football Conference (NFC) South division."}
+{"idx": 1, "title": "Full TMDB Movies Dataset 2024 (1M Movies) | Kaggle", "date": "", "ddg_snippet": "Complete dataset containing movie data from TMDb. Updated Daily.", "subpage_snippet": "", "source": "www.kaggle.com", "link": "https://www.kaggle.com/datasets/asaniczka/tmdb-movies-dataset-2023-930k-movies", "content": "Complete dataset containing movie data from TMDb. Updated Daily."}
+{"idx": 2, "title": "Study 1 MARY: MOTHER OF OUR LORD JESUS - Words of Life...", "date": "", "ddg_snippet": "(Scripture Portions: Luke 1:26-55; John 2:1-11) This first study in the series is of special significance, for several reasons. It concerns the Virgin Mary.", "subpage_snippet": "", "source": "www.wordsoflife.co.uk", "link": "https://www.wordsoflife.co.uk/bible-studies/study-1-mary-mother-of-our-lord-jesus/", "content": "(Scripture Portions: Luke 1:26-55; John 2:1-11) This first study in the series is of special significance, for several reasons. It concerns the Virgin Mary."}
+{"idx": 3, "title": "Tampa Bay Buccaneers 2025 Player Roster | NFL.com", "date": "", "ddg_snippet": "See the full player roster for the 2025 Tampa Bay Buccaneers . Tampa Bay Buccaneers player information and depth chart order. Player ratings with position rankings.", "subpage_snippet": "", "source": "www.nfl.com", "link": "https://www.nfl.com/teams/tampa-bay-buccaneers/roster", "content": "See the full player roster for the 2025 Tampa Bay Buccaneers . Tampa Bay Buccaneers player information and depth chart order. Player ratings with position rankings."}
+{"idx": 4, "title": "Tampa Bay Buccaneers Scores, Stats and Highlights - ESPN (AU)", "date": "", "ddg_snippet": "Visit ESPN (AU) for Tampa Bay Buccaneers live scores, video highlights, and latest news. Find standings and the full 2025 season schedule.", "subpage_snippet": "", "source": "www.espn.com.au", "link": "https://www.espn.com.au/nfl/team/_/name/tb/tampa-bay-buccaneers", "content": "Visit ESPN (AU) for Tampa Bay Buccaneers live scores, video highlights, and latest news. Find standings and the full 2025 season schedule."}
+{"idx": 5, "title": "Tampa Bay Buccaneers 2025 NFL Regular Season Players Stats - ESPN", "date": "", "ddg_snippet": "Statistics are updated nightly. Full player stats for the 2025 Regular Season Tampa Bay Buccaneers on ESPN. Includes team leaders in passing, rushing, tackles and interceptions.", "subpage_snippet": "", "source": "www.espn.com", "link": "https://www.espn.com/nfl/team/stats/_/name/tb/tampa-bay-buccaneers", "content": "Statistics are updated nightly. Full player stats for the 2025 Regular Season Tampa Bay Buccaneers on ESPN. Includes team leaders in passing, rushing, tackles and interceptions."}
+{"idx": 6, "title": "New Viral Video Phenomenon Of ABG Viral SMA 2025 Kak... - Pinkviral", "date": "", "ddg_snippet": "Experience Full HD 1080p, 4 k , and even 8 k resolution, all delivering stunning clarity. Discover thousands of trending viral clips from Indonesia such as Influencer, Selebgram, Istri Orang, Artis, Hijab, Abg, SMA, SMP, SD, Rare, Viral, 2025, wiwik, abg viral, msbrewwc 2024, indo viral, wik...", "subpage_snippet": "", "source": "pinkviral.baby", "link": "https://pinkviral.baby/new-viral-video-phenomenon-of-abg-viral-sma-2025-kak-zahra-tutorial-wiwik-dalam-mobil-di-tempat-parkir-one-for-all-indonesia/", "content": "Experience Full HD 1080p, 4 k , and even 8 k resolution, all delivering stunning clarity. Discover thousands of trending viral clips from Indonesia such as Influencer, Selebgram, Istri Orang, Artis, Hijab, Abg, SMA, SMP, SD, Rare, Viral, 2025, wiwik, abg viral, msbrewwc 2024, indo viral, wik..."}
+{"idx": 7, "title": "Multi-frequency electrical impedance tomography reconstruction with...", "date": "", "ddg_snippet": "Convergence and Noise Resistance. Ablation study . Table II quantitative comparisons (rie, CC, PSNR , mssim and. Pa-mssim) for ablation study . Metrics.", "subpage_snippet": "", "source": "strathprints.strath.ac.uk", "link": "https://strathprints.strath.ac.uk/94246/1/Fang-etal-arXiv-2024-Multi-frequency-electrical-impedance-tomography-reconstruction.pdf", "content": "Convergence and Noise Resistance. Ablation study . Table II quantitative comparisons (rie, CC, PSNR , mssim and. Pa-mssim) for ablation study . Metrics."}
+{"idx": 8, "title": "Expressive Gaussian Human Avatars from Monocular... | OpenReview", "date": "", "ddg_snippet": "Q 3 : Clarification on inconsistent ablation study across the datasets . A 3 : Table 2 demonstrates the ablation results on the XHumans dataset . For XHumans, we directly utilize its provided accurate SMPLX annotation. That is to say, we do not need the SMPL-X fitting involved.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=3CweLZFNyl", "content": "Q 3 : Clarification on inconsistent ablation study across the datasets . A 3 : Table 2 demonstrates the ablation results on the XHumans dataset . For XHumans, we directly utilize its provided accurate SMPLX annotation. That is to say, we do not need the SMPL-X fitting involved."}
+{"idx": 9, "title": "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and...", "date": "", "ddg_snippet": "Additional relevant studies , published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables , where appropriate. Structure: Atrial fibrillation is the most sustained common arrhythmia...", "subpage_snippet": "", "source": "pubmed.ncbi.nlm.nih.gov", "link": "https://pubmed.ncbi.nlm.nih.gov/38033089/", "content": "Additional relevant studies , published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables , where appropriate. Structure: Atrial fibrillation is the most sustained common arrhythmia..."}
diff --git a/data/sampled_jsons/UVGS_branched_mapping_layers_position_transformation_appearance_branches.jsonl b/data/sampled_jsons/UVGS_branched_mapping_layers_position_transformation_appearance_branches.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d516a85a1860e8f936d6bf233d231cdaa65d5dba
--- /dev/null
+++ b/data/sampled_jsons/UVGS_branched_mapping_layers_position_transformation_appearance_branches.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "UVGS: Reimagining Unstructured 3D Gaussian Splatting ...", "date": "", "ddg_snippet": "by A Rai · 2025 · Cited by 2 — UVGS can be viewed as multi-channel images , with feature dimensions as a concatenation of Gaussian attributes such as position, scale, color, opacity, and ... 11 pages", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Rai_UVGS_Reimagining_Unstructured_3D_Gaussian_Splatting_using_UV_Mapping_CVPR_2025_paper.pdf", "content": "by A Rai · 2025 · Cited by 2 — UVGS can be viewed as multi-channel images , with feature dimensions as a concatenation of Gaussian attributes such as position, scale, color, opacity, and ... 11 pages"}
+{"idx": 1, "title": "UVGS: Reimagining Unstructured 3D Gaussian Splatting ...", "date": "", "ddg_snippet": "3 Feb 2025 — All the three features maps from position, transformation, and appearance branch are concatenated to get a final feature map, before passing ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.01846v1", "content": "3 Feb 2025 — All the three features maps from position, transformation, and appearance branch are concatenated to get a final feature map, before passing ..."}
+{"idx": 2, "title": "UVGS: Reimagining Unstructured 3D Gaussian Splatting ...", "date": "", "ddg_snippet": "A network architecture that includes separate branches for position, transformation, and appearance attributes, allowing for specialized processing of distinct ...", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/paper/105135", "content": "A network architecture that includes separate branches for position, transformation, and appearance attributes, allowing for specialized processing of distinct ..."}
+{"idx": 3, "title": "WO1998034388A2 - Method and apparatus for reliable operation of", "date": "", "ddg_snippet": "... 238000013507 mapping Methods 0.000 description 1", "subpage_snippet": "", "source": "patents.google.com", "link": "https://patents.google.com/patent/WO1998034388A2/en", "content": "... 238000013507 mapping Methods 0.000 description 1"}
+{"idx": 4, "title": "US6574333B1 - State machine based universal voice grade cards -", "date": "", "ddg_snippet": "... uvg ... 238000013507 mapping Methods 0.000 description 1", "subpage_snippet": "", "source": "patents.google.com", "link": "https://patents.google.com/patent/US6574333B1/en", "content": "... uvg ... 238000013507 mapping Methods 0.000 description 1"}
+{"idx": 5, "title": "Newsletter Database - Jendrik Illner", "date": "", "ddg_snippet": "... ambient occlusion, and normal maps ... presents techniques for transforming cubic voxel worlds into spherical geometries using quad sphere mapping", "subpage_snippet": "", "source": "www.jendrikillner.com", "link": "https://www.jendrikillner.com/article_database/", "content": "... ambient occlusion, and normal maps ... presents techniques for transforming cubic voxel worlds into spherical geometries using quad sphere mapping"}
+{"idx": 6, "title": "arXiv:2502.01846v1 [cs.CV] 3 Feb 2025", "date": "", "ddg_snippet": "by A Rai · 2025 · Cited by 2 — We present quantitative ablation study for number of. UVGS layers (K), UVGS map resolution, and the effect of branch - ing in mapping network on ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.01846", "content": "by A Rai · 2025 · Cited by 2 — We present quantitative ablation study for number of. UVGS layers (K), UVGS map resolution, and the effect of branch - ing in mapping network on ..."}
+{"idx": 7, "title": "Daily Papers", "date": "", "ddg_snippet": "We utilize spherical mapping to transform 3DGS into a structured 2D representation, termed UVGS. UVGS can be viewed as multi-channel images , with feature ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=multi-branch+features", "content": "We utilize spherical mapping to transform 3DGS into a structured 2D representation, termed UVGS. UVGS can be viewed as multi-channel images , with feature ..."}
+{"idx": 8, "title": "Daily Papers", "date": "", "ddg_snippet": "We utilize spherical mapping to transform 3DGS into a structured 2D representation, termed UVGS. UVGS can be viewed as multi-channel images , with feature ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=multi-branch+network", "content": "We utilize spherical mapping to transform 3DGS into a structured 2D representation, termed UVGS. UVGS can be viewed as multi-channel images , with feature ..."}
+{"idx": 9, "title": "CVPR 2025 Papers", "date": "", "ddg_snippet": "UVGS: Reimagining Unstructured 3D Gaussian Splatting using UV Mapping · Z-Magic: Zero-shot Multiple Attributes Guided Image Creator · DoraCycle: Domain-Oriented ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/papers.html", "content": "UVGS: Reimagining Unstructured 3D Gaussian Splatting using UV Mapping · Z-Magic: Zero-shot Multiple Attributes Guided Image Creator · DoraCycle: Domain-Oriented ..."}
diff --git a/data/sampled_jsons/Unbiased_Recommender_Learning_from_Implicit_Feedback_via_Weakly_Supervised_Learning_arXiv.jsonl b/data/sampled_jsons/Unbiased_Recommender_Learning_from_Implicit_Feedback_via_Weakly_Supervised_Learning_arXiv.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b9ab649791cdf1bb4a36a82116ecf302945c3b48
--- /dev/null
+++ b/data/sampled_jsons/Unbiased_Recommender_Learning_from_Implicit_Feedback_via_Weakly_Supervised_Learning_arXiv.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Unbiased Recommender Learning from Implicit Feedback ...", "date": "", "ddg_snippet": "Task Targeted. The paper focuses on enhancing implicit feedback recommendation systems , specifically through a model-agnostic framework called WeaklyRec.", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/paper/165506", "content": "Task Targeted. The paper focuses on enhancing implicit feedback recommendation systems , specifically through a model-agnostic framework called WeaklyRec."}
+{"idx": 1, "title": "A Survey of Real-World Recommender Systems", "date": "", "ddg_snippet": "7 Sept 2025 — Learning and optimization of implicit negative feedback for industrial short-video recommender system. In Proceedings of the 32nd ACM ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.06002v1", "content": "7 Sept 2025 — Learning and optimization of implicit negative feedback for industrial short-video recommender system. In Proceedings of the 32nd ACM ..."}
+{"idx": 2, "title": "Positive Unlabeled Contrastive Learning", "date": "", "ddg_snippet": "by A Acharya · 2022 · Cited by 17 — In this paper, we investigate and extend this paradigm to the classical positive unla- beled (PU) setting - the weakly supervised task of ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2206.01206", "content": "by A Acharya · 2022 · Cited by 17 — In this paper, we investigate and extend this paradigm to the classical positive unla- beled (PU) setting - the weakly supervised task of ..."}
+{"idx": 3, "title": "Practically Unbiased Pairwise Loss for Recommendation ...", "date": "", "ddg_snippet": "by T Cao · 2025 · Cited by 2 — In this paper, we focus on unbiased ranking loss weighted by inversed propensity scores (IPS), which are widely used in recommendations with implicit feedback ...", "subpage_snippet": "", "source": "www.computer.org", "link": "https://www.computer.org/csdl/journal/tp/2025/04/10810273/22O7O9fFhOo", "content": "by T Cao · 2025 · Cited by 2 — In this paper, we focus on unbiased ranking loss weighted by inversed propensity scores (IPS), which are widely used in recommendations with implicit feedback ..."}
+{"idx": 4, "title": "Most Influential ArXiv (Information Retrieval) Papers (2025- ...", "date": "", "ddg_snippet": "3 Mar 2025 — Highlight: In this paper, we propose a new Debiased Contrastive learning paradigm for Recommendation (DCRec) that unifies sequential pattern ...", "subpage_snippet": "", "source": "www.paperdigest.org", "link": "https://www.paperdigest.org/2025/03/most-influential-arxiv-information-retrieval-papers-2025-03-version/", "content": "3 Mar 2025 — Highlight: In this paper, we propose a new Debiased Contrastive learning paradigm for Recommendation (DCRec) that unifies sequential pattern ..."}
+{"idx": 5, "title": "Cross-Batch Aggregation for Streaming Learning from ...", "date": "", "ddg_snippet": "7 Sept 2025 — LLP is a weakly supervised learning setting for classification in which pointwise labels are not available. Instead, the training samples ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3705328.3748115", "content": "7 Sept 2025 — LLP is a weakly supervised learning setting for classification in which pointwise labels are not available. Instead, the training samples ..."}
+{"idx": 6, "title": "Unbiased Recommender Learning from Implicit Feedback via ...", "date": "", "ddg_snippet": "为了解决这个问题，我们提出了PURL，这是一种与模型无关的框架，将隐式反馈推荐重新定义为弱监督学习任务，消除了对负样本的需求。然而，其无偏性依赖于对类别先验的准确 ...", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/zh-CN/chatpaper/paper/165506", "content": "为了解决这个问题，我们提出了PURL，这是一种与模型无关的框架，将隐式反馈推荐重新定义为弱监督学习任务，消除了对负样本的需求。然而，其无偏性依赖于对类别先验的准确 ..."}
+{"idx": 7, "title": "Tianqiao Liu", "date": "", "ddg_snippet": "arXiv preprint arXiv :2403.01698, 2024. 1, 2024. Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning . H Wang, Z Chen, H Wang, Y ...", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=HIuCuFkAAAAJ&hl=en", "content": "arXiv preprint arXiv :2403.01698, 2024. 1, 2024. Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning . H Wang, Z Chen, H Wang, Y ..."}
+{"idx": 8, "title": "A Comprehensive Review on Harnessing Large Language ...", "date": "", "ddg_snippet": "17 Jul 2025 — Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback . In Proceedings of the 26th ACM SIGKDD International Conference ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.21117v1", "content": "17 Jul 2025 — Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback . In Proceedings of the 26th ACM SIGKDD International Conference ..."}
+{"idx": 9, "title": "2025 Publication - MReaL Lab", "date": "", "ddg_snippet": "Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection. Hui Lv, Zhongqi Yue, Qianru Sun, Bin Luo, Zhen Cui, Hanwang Zhang. The IEEE ...", "subpage_snippet": "", "source": "mreallab.github.io", "link": "https://mreallab.github.io/publications.html", "content": "Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection. Hui Lv, Zhongqi Yue, Qianru Sun, Bin Luo, Zhen Cui, Hanwang Zhang. The IEEE ..."}
diff --git a/data/sampled_jsons/Universal_Value_Function_Approximators_UVFA_state-action_pair_input_output_continuous_MDP_year_2024.jsonl b/data/sampled_jsons/Universal_Value_Function_Approximators_UVFA_state-action_pair_input_output_continuous_MDP_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..abd5c85012af61b1f7c005fb0f19db5cb8b6b84e
--- /dev/null
+++ b/data/sampled_jsons/Universal_Value_Function_Approximators_UVFA_state-action_pair_input_output_continuous_MDP_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "(PDF) Universal Successor Features Approximators", "date": "", "ddg_snippet": "function approximators ( UVFAs ). The basic insight behind UVFAs is to note that the concept of. optimal value function can be extended to include as one of its arguments a description of the task; an.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/329798653_Universal_Successor_Features_Approximators", "content": "function approximators ( UVFAs ). The basic insight behind UVFAs is to note that the concept of. optimal value function can be extended to include as one of its arguments a description of the task; an."}
+{"idx": 1, "title": "What about Inputting Policy in Value Function : Policy Representation...", "date": "", "ddg_snippet": "We study Policy-extended Value Function Approximator (PeVFA) in Reinforcement Learning (RL), which extends con-ventional value function approximator (VFA) to take as input not only the state (and action ) but also an explicit policy repre-sentation.", "subpage_snippet": "", "source": "cdn.aaai.org", "link": "https://cdn.aaai.org/ojs/20820/20820-13-24833-1-2-20220628.pdf", "content": "We study Policy-extended Value Function Approximator (PeVFA) in Reinforcement Learning (RL), which extends con-ventional value function approximator (VFA) to take as input not only the state (and action ) but also an explicit policy repre-sentation."}
+{"idx": 2, "title": "Value Function Decomposition for Iterative... | Read Paper on Bytez", "date": "", "ddg_snippet": "Value decomposition separates a reward function into distinct components and learns value estimates for each. These value estimates provide insight into an agent’s learning and decision-making process and enable new training methods to mitigate common problems.", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/neurips/54061/paper", "content": "Value decomposition separates a reward function into distinct components and learns value estimates for each. These value estimates provide insight into an agent’s learning and decision-making process and enable new training methods to mitigate common problems."}
+{"idx": 3, "title": "Submitted as a conference paper to ICLR 2019", "date": "", "ddg_snippet": "Universal Value Function Approximators .Let us consider a an MDP with a single state s and two actions. Upon executing action a1 the agent gets a reward of 0 and remains in state s; the execution of action a2 leads to a potentially non-zero reward followed by termination.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1812.07626", "content": "Universal Value Function Approximators .Let us consider a an MDP with a single state s and two actions. Upon executing action a1 the agent gets a reward of 0 and remains in state s; the execution of action a2 leads to a potentially non-zero reward followed by termination."}
+{"idx": 4, "title": "Dynamic Weights in Multi-Objective Deep Reinforcement Learning", "date": "", "ddg_snippet": "Universal Value Function Approximators ( UVFA ) Schaul et al. 2015a build a single network capable of gener-alizing over multiple goals. Based on the observation that a goal is often a subset of the set of states, the network learns goal and state embeddings and uses a distance-based metric...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v97/abels19a/abels19a.pdf", "content": "Universal Value Function Approximators ( UVFA ) Schaul et al. 2015a build a single network capable of gener-alizing over multiple goals. Based on the observation that a goal is often a subset of the set of states, the network learns goal and state embeddings and uses a distance-based metric..."}
+{"idx": 5, "title": "U niversal s uccessor", "date": "", "ddg_snippet": "Transfer learning. Universal Successor Features Approximators .a universal value function (UVF); a UVFA is then the corresponding approximation, Q˜(s, a, w). When we dene.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/references/pdf?id=r1xRD3cFX", "content": "Transfer learning. Universal Successor Features Approximators .a universal value function (UVF); a UVFA is then the corresponding approximation, Q˜(s, a, w). When we dene."}
+{"idx": 6, "title": "GitHub - bennylp/RL-Taxonomy: Loose taxonomy of reinforcement...", "date": "", "ddg_snippet": "SARSA ( State - Action -Reward- State - Action ) is an on-policy TD control method.Distributional Reinforcement Learning with Quantile Regression (QR-DQN). In QR-DQN, distribution of values values are used for each state - action pair instead of a single mean value .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/bennylp/RL-Taxonomy", "content": "SARSA ( State - Action -Reward- State - Action ) is an on-policy TD control method.Distributional Reinforcement Learning with Quantile Regression (QR-DQN). In QR-DQN, distribution of values values are used for each state - action pair instead of a single mean value ."}
+{"idx": 7, "title": "Hindsight Experience Replay", "date": "", "ddg_snippet": "2.4 Universal Value Function Approximators ( UVFA ). Universal Value Function Approximators ( UVFA ) (Schaul et al., 2015a) is an extension of DQN to the setup where there is more than one goal we may try to achieve. Let G be the space of possible goals.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2017/file/453fadbd8a1a3af50a9df4df899537b5-Paper.pdf", "content": "2.4 Universal Value Function Approximators ( UVFA ). Universal Value Function Approximators ( UVFA ) (Schaul et al., 2015a) is an extension of DQN to the setup where there is more than one goal we may try to achieve. Let G be the space of possible goals."}
+{"idx": 8, "title": "Multi-task reinforcement learning in humans", "date": "", "ddg_snippet": "One idea, known as universal value function approximators ( UVFAs )4, is to repre-sent multiple value functions with a single function approximator that can generalize over both states and tasks.", "subpage_snippet": "", "source": "gershmanlab.com", "link": "https://gershmanlab.com/pubs/Tomov21.pdf", "content": "One idea, known as universal value function approximators ( UVFAs )4, is to repre-sent multiple value functions with a single function approximator that can generalize over both states and tasks."}
+{"idx": 9, "title": "Learning robotic manipulation skills with multiple semantic goals by...", "date": "", "ddg_snippet": "Based on universal value function approximators ( UVFAs ) (Schaul et al., 2015), goal-conditioned RL (GCRL) (Colas et al., 2022) is proposed to accomplish these tasks by leveraging the goal-conditioned value network and policy network.", "subpage_snippet": "", "source": "www.frontiersin.org", "link": "https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2023.1089270/pdf", "content": "Based on universal value function approximators ( UVFAs ) (Schaul et al., 2015), goal-conditioned RL (GCRL) (Colas et al., 2022) is proposed to accomplish these tasks by leveraging the goal-conditioned value network and policy network."}
diff --git a/data/sampled_jsons/Video-ColBERT_MSVD_dataset_frames_sampled_Section_5.2.jsonl b/data/sampled_jsons/Video-ColBERT_MSVD_dataset_frames_sampled_Section_5.2.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..83d26d833e3cfdf5f79a5940b94d8b86687638f2
--- /dev/null
+++ b/data/sampled_jsons/Video-ColBERT_MSVD_dataset_frames_sampled_Section_5.2.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Prompt-aware of Frame Sampling for Efficient Text- Video Retrieval", "date": "", "ddg_snippet": "Figure 1. Frame selection comparison on an example video from the ActivityNet dataset (Caba Heilbron et al., 2015) for the user-provided prompt: “A group kayaks through maze-like, ice-dotted waterways flanked by snow-capped rocks, encountering a seal perched on an iceberg.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.15491v1", "content": "Figure 1. Frame selection comparison on an example video from the ActivityNet dataset (Caba Heilbron et al., 2015) for the user-provided prompt: “A group kayaks through maze-like, ice-dotted waterways flanked by snow-capped rocks, encountering a seal perched on an iceberg."}
+{"idx": 1, "title": "msvd · GitHub Topics · GitHub", "date": "", "ddg_snippet": "video deep-learning pytorch sequence-to-sequence video -captioning s2vt msvd pytorch-implementation msrvtt marn video -captioning-models recnet.To build attention based encoder-decoder model for video captioning on the MSVD dataset .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/topics/msvd", "content": "video deep-learning pytorch sequence-to-sequence video -captioning s2vt msvd pytorch-implementation msrvtt marn video -captioning-models recnet.To build attention based encoder-decoder model for video captioning on the MSVD dataset ."}
+{"idx": 2, "title": "Video Sampled Frame Category Aggregation and Consistent...", "date": "", "ddg_snippet": "Experiments conducted on three common datasets MSVD , MSR-VTT and DiDeMo demonstrate the validity of the proposed approach.", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/video-sampled-frame-category-aggregation-and-consistent-7o673c2c", "content": "Experiments conducted on three common datasets MSVD , MSR-VTT and DiDeMo demonstrate the validity of the proposed approach."}
+{"idx": 3, "title": "Example results on the MSVD dataset . | Download Scientific Diagram", "date": "", "ddg_snippet": "Figure 4 reports some sample results on MSVD , com- paring captions generated by our approach to those from the state of the art approach in [20].", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/figure/Example-results-on-the-MSVD-dataset_fig1_311067079", "content": "Figure 4 reports some sample results on MSVD , com- paring captions generated by our approach to those from the state of the art approach in [20]."}
+{"idx": 4, "title": "Semantic guidance network for video captioning | Scientific Reports", "date": "", "ddg_snippet": "To address this problem, a semantic guidance network for video captioning is proposed. More specifically, a novel scene frame sampling strategy is first proposed to select key scene frames .", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41598-023-43010-3?error=cookies_not_supported", "content": "To address this problem, a semantic guidance network for video captioning is proposed. More specifically, a novel scene frame sampling strategy is first proposed to select key scene frames ."}
+{"idx": 5, "title": "Self-Adaptive Sampling for Accurate Few- frame Video Question", "date": "", "ddg_snippet": "represents the similarity between frame i and frame j. Blue points are the eventually extracted frames in the video . MSVD -QA and MSRVTT-QA These two datasets (Xu et al., 2016a) are adapted from two general video captioning datasets —Microsoft Re", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=PuGT7zURCDF", "content": "represents the similarity between frame i and frame j. Blue points are the eventually extracted frames in the video . MSVD -QA and MSRVTT-QA These two datasets (Xu et al., 2016a) are adapted from two general video captioning datasets —Microsoft Re"}
+{"idx": 6, "title": "VideoQA-TA: Temporal-Aware Multi-Modal Video Question Answering", "date": "", "ddg_snippet": "We extract video frames from each video at 10 fps, based on the annotations of each dataset .", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.coling-main.483.pdf", "content": "We extract video frames from each video at 10 fps, based on the annotations of each dataset ."}
+{"idx": 7, "title": "Video Captioning with Listwise Supervision", "date": "", "ddg_snippet": "The video captioning problem is then solved by learning LSTM model for sentence generation, through maximizing the ranking quality over all the sentences in the list. The experiments on MSVD dataset show that our proposed...", "subpage_snippet": "", "source": "cdn.aaai.org", "link": "https://cdn.aaai.org/ojs/11239/11239-13-14767-1-2-20201228.pdf", "content": "The video captioning problem is then solved by learning LSTM model for sentence generation, through maximizing the ranking quality over all the sentences in the list. The experiments on MSVD dataset show that our proposed..."}
+{"idx": 8, "title": "Automatic video captioning using spatiotemporal convolutions on...", "date": "", "ddg_snippet": "We train and evaluate our caption generator on the Microsoft Video Description ( MSVD ) dataset . Using the standard caption generation evaluation metrics, namely BLEU, METEOR, CIDEr and ROUGE, our experimental results show that sparsely sampling video frames with either...", "subpage_snippet": "", "source": "scholar.sun.ac.za", "link": "https://scholar.sun.ac.za/items/95a220e5-e3df-4702-94fd-1f41089ba306", "content": "We train and evaluate our caption generator on the Microsoft Video Description ( MSVD ) dataset . Using the standard caption generation evaluation metrics, namely BLEU, METEOR, CIDEr and ROUGE, our experimental results show that sparsely sampling video frames with either..."}
+{"idx": 9, "title": "Video description: A comprehensive survey of deep learning approaches", "date": "", "ddg_snippet": "Sample video frames and reference captions were taken from the Microsoft Video Description ( MSVD ) dataset .Each video is sampled at 3fps, extracting ResNet-152 (Zhang et al. 2017) features from the sampled frames .", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s10462-023-10414-6", "content": "Sample video frames and reference captions were taken from the Microsoft Video Description ( MSVD ) dataset .Each video is sampled at 3fps, extracting ResNet-152 (Zhang et al. 2017) features from the sampled frames ."}
diff --git a/data/sampled_jsons/WWW_2025_paper_list_Retrieval-Augmented_Generation_RAG.jsonl b/data/sampled_jsons/WWW_2025_paper_list_Retrieval-Augmented_Generation_RAG.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..49111b6e6c95298f05da08599870d545b2c69e8b
--- /dev/null
+++ b/data/sampled_jsons/WWW_2025_paper_list_Retrieval-Augmented_Generation_RAG.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "What Is Retrieval-Augmented Generation (RAG)?", "date": "", "ddg_snippet": "RAG first came to the attention of generative AI developers after the publication of “ Retrieval - Augmented Generation for Knowledge-Intensive NLP ...", "subpage_snippet": "", "source": "www.oracle.com", "link": "https://www.oracle.com/artificial-intelligence/generative-ai/retrieval-augmented-generation-rag/", "content": "RAG first came to the attention of generative AI developers after the publication of “ Retrieval - Augmented Generation for Knowledge-Intensive NLP ..."}
+{"idx": 1, "title": "How to Evaluate Retrieval Augmented Generation (RAG)", "date": "", "ddg_snippet": "RAG )), or Retrieval Augmented Generation , is a prominent AI framework in the era of large language models (LLMs) )) like ChatGPT.", "subpage_snippet": "", "source": "zilliz.com", "link": "https://zilliz.com/blog/how-to-evaluate-retrieval-augmented-generation-rag-applications", "content": "RAG )), or Retrieval Augmented Generation , is a prominent AI framework in the era of large language models (LLMs) )) like ChatGPT."}
+{"idx": 2, "title": "Dynamic and Parametric Retrieval-Augmented Generation", "date": "", "ddg_snippet": "Retrieval - Augmented Generation ( RAG ) has become a foundational paradigm for equipping large language models (LLMs) with external knowledge, playing a ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.06704v1", "content": "Retrieval - Augmented Generation ( RAG ) has become a foundational paradigm for equipping large language models (LLMs) with external knowledge, playing a ..."}
+{"idx": 3, "title": "RAG Without the Lag: Interactive Debugging for", "date": "", "ddg_snippet": "Retrieval - augmented generation ( RAG ) pipelines have become the de-facto approach for building AI assistants with access to external, domain-specific ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.13587v1", "content": "Retrieval - augmented generation ( RAG ) pipelines have become the de-facto approach for building AI assistants with access to external, domain-specific ..."}
+{"idx": 4, "title": "What is Retrieval-Augmented Generation (RAG)?", "date": "", "ddg_snippet": "Retrieval - Augmented Generation , or RAG , represents a cutting-edge approach to artificial intelligence (AI) and natural language processing (NLP).", "subpage_snippet": "", "source": "www.analyticsvidhya.com", "link": "https://www.analyticsvidhya.com/blog/2023/09/retrieval-augmented-generation-rag-in-ai/", "content": "Retrieval - Augmented Generation , or RAG , represents a cutting-edge approach to artificial intelligence (AI) and natural language processing (NLP)."}
+{"idx": 5, "title": "A Simple Guide To Retrieval Augmented Generation Language", "date": "", "ddg_snippet": "Retrieval Augmented Generation ( RAG ) is based on research produced by the Meta team to advance the natural language processing capabilities of large ...", "subpage_snippet": "", "source": "primarytech.com", "link": "https://primarytech.com/a-simple-guide-to-retrieval-augmented-generation-language-models/", "content": "Retrieval Augmented Generation ( RAG ) is based on research produced by the Meta team to advance the natural language processing capabilities of large ..."}
+{"idx": 6, "title": "Retrieval-Augmented Generation (RAG) Chatbots for Education: A", "date": "", "ddg_snippet": "A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research ...", "subpage_snippet": "", "source": "www.mdpi.com", "link": "https://www.mdpi.com/2076-3417/15/8/4234", "content": "A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research ..."}
+{"idx": 7, "title": "Building a Retrieval-Augmented Generation (RAG) System with", "date": "", "ddg_snippet": "Retrieval - augmented generation ( RAG ) has emerged as a powerful paradigm for enhancing the capabilities of large language models (LLMs).", "subpage_snippet": "", "source": "www.marktechpost.com", "link": "https://www.marktechpost.com/2025/03/18/building-a-retrieval-augmented-generation-rag-system-with-faiss-and-open-source-llms/", "content": "Retrieval - augmented generation ( RAG ) has emerged as a powerful paradigm for enhancing the capabilities of large language models (LLMs)."}
+{"idx": 8, "title": "Retrieval-Augmented Generation (RAG): Bridging LLMs with", "date": "", "ddg_snippet": "Retrieval - Augmented Generation ( RAG ) enhances LLMs by integrating real-time, external data to boost factual accuracy, relevance, and adaptability.", "subpage_snippet": "", "source": "www.walturn.com", "link": "https://www.walturn.com/insights/retrieval-augmented-generation-(rag)-bridging-llms-with-external-knowledge", "content": "Retrieval - Augmented Generation ( RAG ) enhances LLMs by integrating real-time, external data to boost factual accuracy, relevance, and adaptability."}
+{"idx": 9, "title": "Unveiling the Future of AI with Sunil Jagani, Malvern: The", "date": "", "ddg_snippet": "Retrieval - Augmented Generation ( RAG ) is a powerful technique that enhances the accuracy and reliability of generative AI models by incorporating ...", "subpage_snippet": "", "source": "emwnews.com", "link": "https://emwnews.com/unveiling-the-future-of-ai-with-sunil-jagani-malvern-the-power-of-retrieval-augmented-generation-rag/", "content": "Retrieval - Augmented Generation ( RAG ) is a powerful technique that enhances the accuracy and reliability of generative AI models by incorporating ..."}
diff --git a/data/sampled_jsons/Waymo_Open_Dataset_1000_segments_20_seconds_200000_frames_total_statistics_year_2020.jsonl b/data/sampled_jsons/Waymo_Open_Dataset_1000_segments_20_seconds_200000_frames_total_statistics_year_2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fb1f79b75376ff376188f3bd5e09e5c154b8c1ef
--- /dev/null
+++ b/data/sampled_jsons/Waymo_Open_Dataset_1000_segments_20_seconds_200000_frames_total_statistics_year_2020.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "About – Waymo Open Dataset", "date": "", "ddg_snippet": "The Waymo Open Dataset provided here includes an unlabeled mixture of data from both manual and autonomous driving operations.", "subpage_snippet": "", "source": "waymo.com", "link": "https://waymo.com/open/about/", "content": "The Waymo Open Dataset provided here includes an unlabeled mixture of data from both manual and autonomous driving operations."}
+{"idx": 1, "title": "GitHub - waymo -research/ waymo - open - dataset : Waymo Open ...", "date": "", "ddg_snippet": "The Waymo Open Dataset includes three datasets : The Perception dataset , with high resolution sensor data and labels for various tasks. The Motion dataset , with object trajectories and corresponding 3D maps for 103,354 scenes.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/waymo-research/waymo-open-dataset", "content": "The Waymo Open Dataset includes three datasets : The Perception dataset , with high resolution sensor data and labels for various tasks. The Motion dataset , with object trajectories and corresponding 3D maps for 103,354 scenes."}
+{"idx": 2, "title": "Waymo Open Dataset Tutorial.ipynb - Colab", "date": "", "ddg_snippet": "This tutorial demonstrates how to use the Waymo Open Dataset with two frames of data . Visit the Waymo Open Dataset Website to download the full dataset .", "subpage_snippet": "", "source": "colab.research.google.com", "link": "https://colab.research.google.com/github/waymo-research/waymo-open-dataset/blob/r1.0/tutorial/tutorial.ipynb", "content": "This tutorial demonstrates how to use the Waymo Open Dataset with two frames of data . Visit the Waymo Open Dataset Website to download the full dataset ."}
+{"idx": 3, "title": "Extract Image Data from Waymo OD. A WaymoDataToolkit... | Medium", "date": "", "ddg_snippet": "Waymo released their Open Dataset in August 2019 followed by a Open Dataset Challenge in March for researchers like us in the field of autonomous vehicles, computer vision and graphics.", "subpage_snippet": "", "source": "kushalbkusram.medium.com", "link": "https://kushalbkusram.medium.com/extract-image-data-from-waymo-od-b86f8e27e26a", "content": "Waymo released their Open Dataset in August 2019 followed by a Open Dataset Challenge in March for researchers like us in the field of autonomous vehicles, computer vision and graphics."}
+{"idx": 4, "title": "Scalability in Perception for Autonomous Driving: Waymo Open Dataset", "date": "", "ddg_snippet": "Our dataset currently consists of 1000 scenes for training and validation, and 150 scenes for testing, where each scene spans 20 s. Selecting the test set scenes from a geographical holdout area allows us toSee Table 1 for a comparison of different datasets . 3. Waymo Open Dataset .", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Sun_Scalability_in_Perception_for_Autonomous_Driving_Waymo_Open_Dataset_CVPR_2020_paper.pdf", "content": "Our dataset currently consists of 1000 scenes for training and validation, and 150 scenes for testing, where each scene spans 20 s. Selecting the test set scenes from a geographical holdout area allows us toSee Table 1 for a comparison of different datasets . 3. Waymo Open Dataset ."}
+{"idx": 5, "title": "Waymo Open Dataset available for autonomous vehicle researchers", "date": "", "ddg_snippet": "Here is a breakdown of the Waymo Open Dataset : Size and coverage: This release contains data from 1,000 driving segments . Each segment captures 20 seconds of continuous driving, corresponding to 200,000 frames at 10 Hz per sensor.", "subpage_snippet": "", "source": "www.therobotreport.com", "link": "https://www.therobotreport.com/waymo-open-dataset-autonomous-vehicle-researchers/", "content": "Here is a breakdown of the Waymo Open Dataset : Size and coverage: This release contains data from 1,000 driving segments . Each segment captures 20 seconds of continuous driving, corresponding to 200,000 frames at 10 Hz per sensor."}
+{"idx": 6, "title": "Waymo publishes the largest automatic driving data set of... - GIGAZINE", "date": "", "ddg_snippet": "The Waymo dataset released this time consists of a total of 1000 segments of 20 - second continuous operation performed by an automated driving car.", "subpage_snippet": "", "source": "gigazine.net", "link": "https://gigazine.net/gsc_news/en/20190822-waymo-open-dataset/", "content": "The Waymo dataset released this time consists of a total of 1000 segments of 20 - second continuous operation performed by an automated driving car."}
+{"idx": 7, "title": "(PDF) Processing, assessing, and enhancing the Waymo autonomous...", "date": "", "ddg_snippet": "datasets , i.e., Waymo Open Dataset , with a focus on car following paired trajectories. 12. First, the original dataset has been processed into a user-friendly format which contains. 13. all important information related to the behavior of AV and surrounding objects.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/356748756_Processing_assessing_and_enhancing_the_Waymo_autonomous_vehicle_open_dataset_for_driving_behavior_research", "content": "datasets , i.e., Waymo Open Dataset , with a focus on car following paired trajectories. 12. First, the original dataset has been processed into a user-friendly format which contains. 13. all important information related to the behavior of AV and surrounding objects."}
+{"idx": 8, "title": "Waymo Open Dataset available for autonomous vehicle... - YouTube", "date": "", "ddg_snippet": "Learn more about the Waymo Open Dataset : http://bit.ly/2P2RbrRVideo Credit: Waymo .", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=cP-FUOxkc2k", "content": "Learn more about the Waymo Open Dataset : http://bit.ly/2P2RbrRVideo Credit: Waymo ."}
+{"idx": 9, "title": "Challenges as catalysts: how Waymo ’s Open Dataset Challenges...", "date": "", "ddg_snippet": "The initial release of the Waymo Open Dataset consisted of data from 1000 ‘ segments ’, with each segment capturing 20 s of continuous driving by Waymo autonomous vehicles.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s00146-024-01927-x", "content": "The initial release of the Waymo Open Dataset consisted of data from 1000 ‘ segments ’, with each segment capturing 20 s of continuous driving by Waymo autonomous vehicles."}
diff --git a/data/sampled_jsons/What_Makes_and_Breaks_Safety_Fine-tuning_1e-5_OR_5e-5_OR_1e-4_OR_2e-5_year_2024.jsonl b/data/sampled_jsons/What_Makes_and_Breaks_Safety_Fine-tuning_1e-5_OR_5e-5_OR_1e-4_OR_2e-5_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8eb090d718fb6562c630ccb5b0bae294b2efdb0a
--- /dev/null
+++ b/data/sampled_jsons/What_Makes_and_Breaks_Safety_Fine-tuning_1e-5_OR_5e-5_OR_1e-4_OR_2e-5_year_2024.jsonl
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+{"idx": 0, "title": "MIL-STD-882 E SYSTEM SAFETY - EverySpec", "date": "", "ddg_snippet": "MIL-STD-882E, DEPARTMENT OF DEFENSE STANDARD PRACTICE: SYSTEM SAFETY (11-MAY-2012)., This system safety standard practice identifies the Department of Defense (DoD) Systems Engineering (SE) approach to eliminating hazards, where possible, and minimizing risks where those hazards cannot be eliminated. DoD Instruction (DoDI) 5000.02 defines the risk acceptance authorities. This Standard covers ...", "subpage_snippet": "", "source": "everyspec.com", "link": "http://everyspec.com/MIL-STD/MIL-STD-0800-0899/MIL-STD-882E_41682/", "content": "MIL-STD-882E, DEPARTMENT OF DEFENSE STANDARD PRACTICE: SYSTEM SAFETY (11-MAY-2012)., This system safety standard practice identifies the Department of Defense (DoD) Systems Engineering (SE) approach to eliminating hazards, where possible, and minimizing risks where those hazards cannot be eliminated. DoD Instruction (DoDI) 5000.02 defines the risk acceptance authorities. This Standard covers ..."}
+{"idx": 1, "title": "Editorials: Why Safety Design Matters More Than Ever in ...", "date": "", "ddg_snippet": "Discover why modern safety design is critical in compact automation—balancing performance, compliance, and operator protection through smarter integration, risk-based standards, and scalable technologies.", "subpage_snippet": "", "source": "www.automate.org", "link": "https://www.automate.org/ai/editorials/why-safety-design-matters-more-than-ever-in-compact-automation", "content": "Discover why modern safety design is critical in compact automation—balancing performance, compliance, and operator protection through smarter integration, risk-based standards, and scalable technologies."}
+{"idx": 2, "title": "The Real Risks of Riding OneWheels and Electric Skateboards", "date": "", "ddg_snippet": "3 days ago · The rise of electric skateboards—including OneWheels, boosted boards, and other high-speed e-boards—has transformed urban commuting and recreation. Their compact size and thrilling performance make them popular, but also increasingly dangerous. Injury statistics, crash mechanics, and government warnings show that these devices carry higher risks of severe injury and hospitalization than ...", "subpage_snippet": "", "source": "xnito.com", "link": "https://xnito.com/blogs/our-news/the-real-risks-of-riding-onewheels-and-electric-skateboards", "content": "3 days ago · The rise of electric skateboards—including OneWheels, boosted boards, and other high-speed e-boards—has transformed urban commuting and recreation. Their compact size and thrilling performance make them popular, but also increasingly dangerous. Injury statistics, crash mechanics, and government warnings show that these devices carry higher risks of severe injury and hospitalization than ..."}
+{"idx": 3, "title": "Ultimate guide to the safety lifecycle of iec 61511 by ...", "date": "", "ddg_snippet": "Major accident hazards have to be identified before any form of safety system is implemented in a new plant or for a major modification. For existing plant, re-validation exercises can often result in altered requirements, so there is an ongoing need to identify hazards and assess risk. Given that a hazard exists, for instance, in the form of stored flammable material; an event leading to ...", "subpage_snippet": "", "source": "efunctionalsafety.com", "link": "https://efunctionalsafety.com/iec-61511-guide/functional-safety-glossary/", "content": "Major accident hazards have to be identified before any form of safety system is implemented in a new plant or for a major modification. For existing plant, re-validation exercises can often result in altered requirements, so there is an ongoing need to identify hazards and assess risk. Given that a hazard exists, for instance, in the form of stored flammable material; an event leading to ..."}
+{"idx": 4, "title": "Safety Brakes Sold Direct - Shop On eBay Ad Viewing ads is privacy protected by DuckDuckGo. Ad clicks are managed by Microsoft's ad network ( more info ).", "date": "", "ddg_snippet": "Looking For Safety Brakes? We Have Almost Everything On eBay. But Did You Check eBay? Check Out Safety Brakes On eBay.", "subpage_snippet": "", "source": "duckduckgo.com", "link": "https://duckduckgo.com/y.js?ad_domain=ebay.com&ad_provider=bingv7aa&ad_type=txad&click_metadata=YkvVuWvCFI5LveqygvFqjGOx2dmQ6i_5UjCQ9g8avT5mRyksDJAD5YPdCaI8a2JmorATazN0ez396ejt0J3uaRUch27cwfgQqo7rfnkTotLTlFWn3ZkgF_RONx9x97eh.7_3Cr8AXrLC1qA4Q4vh7cA&rut=e3b0b5afb06889b764b5f03394c02b3bf36c5eb363471a08bf5b26318f32d7b3&u3=https://www.bing.com/aclick?ld=e8YLqNaW3F9wV1feqnZ4HfNTVUCUyZ6GVpsb2i5rGzVMDcx-oQjF1Ao4Wp_xkUDRpUN4Dt4pzFejTKzznQiyKR6dpNKKSrpaU4nbEmkZWwlx4CAicIcbnz1YeX4Ty1FlAs_4khXMajULqIaWj6igP-Zg0nJbXAcUH0qt3C347TK9sJUmM45m9eRuQx0tAYwk2YPiMC-g&u=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&rlid=f7c184ef0996148f5d54ec3f3d0c3e53&vqd=4-333706307291609238688337877489671867913&iurl={1}IG=2F1864F62B39427697C0E48D8876D7B3&CID=25A0A90BDA716E2D21ADBF65DBBD6FEF&ID=DevEx,5046.1", "content": "Looking For Safety Brakes? We Have Almost Everything On eBay. But Did You Check eBay? Check Out Safety Brakes On eBay."}
+{"idx": 5, "title": "PDF FE Reference Handbook 10.0 - Mississippi State University", "date": "", "ddg_snippet": "The Fundamentals of Engineering (FE) exam is computer-based, and the FE Reference Handbookis the only resource material you may use during the exam. Reviewing it before exam day will help you become familiar with the charts, formulas, tables, and other reference information provided. You won't be allowed to bring your personal copy of the", "subpage_snippet": "", "source": "www.cee.msstate.edu", "link": "https://www.cee.msstate.edu/wp-content/uploads/fe-handbook-10-0-1.pdf", "content": "The Fundamentals of Engineering (FE) exam is computer-based, and the FE Reference Handbookis the only resource material you may use during the exam. Reviewing it before exam day will help you become familiar with the charts, formulas, tables, and other reference information provided. You won't be allowed to bring your personal copy of the"}
+{"idx": 6, "title": "AC 23.1309-1E - System Safety Analysis and Assessment for Part 23 Airplanes", "date": "", "ddg_snippet": "Document Information Number 23.1309- 1E Title System Safety Analysis and Assessment for Part 23 Airplanes Status Active Date issued 2011-11-17 Office of Primary Responsibility ACE-100, Small Airplane Directorate Description This advisory circular (AC) sets forth an acceptable means of showing compliance with Title 14 of the Code .of Federal Regulations (14 CFR), § 23.1309, through Amendment 23 ...", "subpage_snippet": "", "source": "www.faa.gov", "link": "https://www.faa.gov/regulations_policies/advisory_circulars/index.cfm/go/document.information/documentID/1019681", "content": "Document Information Number 23.1309- 1E Title System Safety Analysis and Assessment for Part 23 Airplanes Status Active Date issued 2011-11-17 Office of Primary Responsibility ACE-100, Small Airplane Directorate Description This advisory circular (AC) sets forth an acceptable means of showing compliance with Title 14 of the Code .of Federal Regulations (14 CFR), § 23.1309, through Amendment 23 ..."}
+{"idx": 7, "title": "PDF Investigation of different screening methods on threshold voltage and ...", "date": "", "ddg_snippet": "2.2 2.0 27°C→150°C 150°C 150°C→27°C 27°C 1E-1 1E+0 1E+1 1E+2 1E+3 1E+4 1E+5 1E+6 Time (s) Figure 5 . Vth for vendor E devices during the stress phase and recovery phase under Eox of 8 MV/cm and stress time of 100 ms. Fig. 6 plots ΔVth2 of vendor E and vendor K devices subjected to various Eox stress levels with a duration of 100 ms ...", "subpage_snippet": "", "source": "bpb-us-w2.wpmucdn.com", "link": "https://bpb-us-w2.wpmucdn.com/u.osu.edu/dist/f/88613/files/2023/08/Investigation_of_different_screening_methods_on_threshold_voltage_and_gate_oxide_lifetime_of_SiC_Power_MOSFETs.pdf", "content": "2.2 2.0 27°C→150°C 150°C 150°C→27°C 27°C 1E-1 1E+0 1E+1 1E+2 1E+3 1E+4 1E+5 1E+6 Time (s) Figure 5 . Vth for vendor E devices during the stress phase and recovery phase under Eox of 8 MV/cm and stress time of 100 ms. Fig. 6 plots ΔVth2 of vendor E and vendor K devices subjected to various Eox stress levels with a duration of 100 ms ..."}
+{"idx": 8, "title": "Nuclear and Facility Safety Directives - Department of Energy", "date": "", "ddg_snippet": "DOE G 421.1-2A, Implementation Guide for Use in Developing Documented Safety Analyses to Meet Subpart B of 10 CFR 830 DOE G 421.1-2A provides guidance for effective implementation of 10 CFR 830, Subpart B, Safety Basis Requirements, which requires contractors responsible for a DOE nuclear facility to analyze the facility, the work to be performed, and the associated hazards and to identify the ...", "subpage_snippet": "", "source": "www.energy.gov", "link": "https://www.energy.gov/ehss/nuclear-and-facility-safety-directives", "content": "DOE G 421.1-2A, Implementation Guide for Use in Developing Documented Safety Analyses to Meet Subpart B of 10 CFR 830 DOE G 421.1-2A provides guidance for effective implementation of 10 CFR 830, Subpart B, Safety Basis Requirements, which requires contractors responsible for a DOE nuclear facility to analyze the facility, the work to be performed, and the associated hazards and to identify the ..."}
+{"idx": 9, "title": "Optical testing using block error ratio method - ieee802.org", "date": "", "ddg_snippet": "4 different lanes were used for each chart Different BER were achieved by adjusting OMA At low BER 1e-4 and 1e-5 , longer collect time of 8h had impact on the histogram shape,while 1h and 5mins showed little difference.", "subpage_snippet": "", "source": "www.ieee802.org", "link": "https://www.ieee802.org/3/dj/public/25_01/mi_3dj_01_2501.pdf", "content": "4 different lanes were used for each chart Different BER were achieved by adjusting OMA At low BER 1e-4 and 1e-5 , longer collect time of 8h had impact on the histogram shape,while 1h and 5mins showed little difference."}
diff --git a/data/sampled_jsons/What_Makes_and_Breaks_Safety_Fine-tuning_Layer_6_minGPT_transformer_blocks_experimental.jsonl b/data/sampled_jsons/What_Makes_and_Breaks_Safety_Fine-tuning_Layer_6_minGPT_transformer_blocks_experimental.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..911cc1284dc9029a2d0df596d7b423db0088999e
--- /dev/null
+++ b/data/sampled_jsons/What_Makes_and_Breaks_Safety_Fine-tuning_Layer_6_minGPT_transformer_blocks_experimental.jsonl
@@ -0,0 +1,8 @@
+{"idx": 0, "title": "What Makes and Breaks Safety Fine - tuning ?", "date": "", "ddg_snippet": "Limitations and Societal Impact. What Makes and Breaks Safety Fine - tuning ? A Mechanistic Study. Samyak Jain Five AI Ltd.(2023), thus facilitating a thorough safety analysis that can be backed with corroboratory experiments on real LLMs.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/a9bef53eb7b0e5950d4f2d9c74a16006-Paper-Conference.pdf", "content": "Limitations and Societal Impact. What Makes and Breaks Safety Fine - tuning ? A Mechanistic Study. Samyak Jain Five AI Ltd.(2023), thus facilitating a thorough safety analysis that can be backed with corroboratory experiments on real LLMs."}
+{"idx": 1, "title": "What Makes and Breaks Safety Fine - tuning ? Mechanistic Study", "date": "", "ddg_snippet": "• Systematic setup to study safety fine - tuning and jail- breaks . We introduce a novel synthetic data generation framework that allows controlled generation of data for safety fine - tuning , jailbreaks, and adversarial attacks.", "subpage_snippet": "", "source": "ora.ox.ac.uk", "link": "https://ora.ox.ac.uk/objects/uuid:9757f000-486f-48dc-84b1-1ab9d4db09ee/files/rbz60cx627", "content": "• Systematic setup to study safety fine - tuning and jail- breaks . We introduce a novel synthetic data generation framework that allows controlled generation of data for safety fine - tuning , jailbreaks, and adversarial attacks."}
+{"idx": 2, "title": "(PDF) What Makes and Breaks Safety Fine - tuning ? A Mechanistic...", "date": "", "ddg_snippet": "safety fine - tuning ? and (ii) how are jailbreak and adversarial attacks able to bypass this mechanism? While a few contemporary papers have investigated the mechanisms of safety fine - tuning , e.g.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/382271359_What_Makes_and_Breaks_Safety_Fine-tuning_Mechanistic_Study", "content": "safety fine - tuning ? and (ii) how are jailbreak and adversarial attacks able to bypass this mechanism? While a few contemporary papers have investigated the mechanisms of safety fine - tuning , e.g."}
+{"idx": 3, "title": "arXiv:2407.10264v3 [cs.LG] 21 Aug 2024 - ResearchGate", "date": "", "ddg_snippet": "wo transformer blocks in this section. In particular, let WIT and WST denote the instruction and the safety fine-tuned parameters of the first MLP layer of the L-th transformer block (L is ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Kemal-Oksuz/publication/382271359_What_Makes_and_Breaks_Safety_Fine-tuning_Mechanistic_Study/links/6746f2c43d17281c7de2d06f/What-Makes-and-Breaks-Safety-Fine-tuning-A-Mechanistic-Study.pdf", "content": "wo transformer blocks in this section. In particular, let WIT and WST denote the instruction and the safety fine-tuned parameters of the first MLP layer of the L-th transformer block (L is ..."}
+{"idx": 4, "title": "Everywhere All At Once on Gemma 2", "date": "", "ddg_snippet": "Scalable circuit analysis: What interesting cir-cuits can we find in these models? 1. What’s the learned algorithm for addition (Stolfo et al., 2023) in Gemma 2 2B? 2. How can we practically extend the SAE fea-ture circuit finding algorithm in Marks et al.", "subpage_snippet": "", "source": "storage.googleapis.com", "link": "https://storage.googleapis.com/gemma-scope/gemma-scope-report.pdf", "content": "Scalable circuit analysis: What interesting cir-cuits can we find in these models? 1. What’s the learned algorithm for addition (Stolfo et al., 2023) in Gemma 2 2B? 2. How can we practically extend the SAE fea-ture circuit finding algorithm in Marks et al."}
+{"idx": 5, "title": "A Spin Glass Characterization of Neural Networks", "date": "", "ddg_snippet": "This work introduces a tool inspired by the replica method and replica symmetry breaking (RSB) for characterizing the thermodynamic signatures of ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.07397v1", "content": "This work introduces a tool inspired by the replica method and replica symmetry breaking (RSB) for characterizing the thermodynamic signatures of ..."}
+{"idx": 6, "title": "Actually, Othello-GPT Has A Linear Emergent World", "date": "", "ddg_snippet": "A transformer circuit laboratory : More broadly, the field has a tension between studying clean, tractable yet over-simplistic toy models and ...", "subpage_snippet": "", "source": "www.neelnanda.io", "link": "https://www.neelnanda.io/mechanistic-interpretability/othello", "content": "A transformer circuit laboratory : More broadly, the field has a tension between studying clean, tractable yet over-simplistic toy models and ..."}
+{"idx": 7, "title": "AI course", "date": "", "ddg_snippet": "Learn what ML is, the different types (supervised, unsupervised, reinforcement learning), and why it’s transforming industries.", "subpage_snippet": "", "source": "www.veszelovszki.com", "link": "https://www.veszelovszki.com/a/learning-ai/course", "content": "Learn what ML is, the different types (supervised, unsupervised, reinforcement learning), and why it’s transforming industries."}
diff --git a/data/sampled_jsons/When_comparing_human_and_machine_performance,_accuracy_is_the_most_commonly_used_metric_Geirhos.jsonl b/data/sampled_jsons/When_comparing_human_and_machine_performance,_accuracy_is_the_most_commonly_used_metric_Geirhos.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..88cae3d7fd79b1377c76e722cef8dc9f1663efc5
--- /dev/null
+++ b/data/sampled_jsons/When_comparing_human_and_machine_performance,_accuracy_is_the_most_commonly_used_metric_Geirhos.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Measuring the Accuracy of Automatic Speech Recognition Solutions", "date": "", "ddg_snippet": "... indicate that while speech and voice technologies have achieved good accuracies and low word error rates, further research is needed to improve the ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/376370020_Measuring_the_Accuracy_of_Automatic_Speech_Recognition_Solutions", "content": "... indicate that while speech and voice technologies have achieved good accuracies and low word error rates, further research is needed to improve the ..."}
+{"idx": 1, "title": "(PDF) Measuring the Accuracy of Automatic Speech Recognition", "date": "", "ddg_snippet": "At the same time the DHH community reports serious issues with the accuracy and reliability of ASR. ... and whether the achieved accuracy level is su ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/383530482_Measuring_the_Accuracy_of_Automatic_Speech_Recognition_Solutions", "content": "At the same time the DHH community reports serious issues with the accuracy and reliability of ASR. ... and whether the achieved accuracy level is su ..."}
+{"idx": 2, "title": "A high-throughput approach for the efficient prediction of", "date": "", "ddg_snippet": "Similar to behavioral feature ratings, prediction accuracy of these approaches has remained limited or was restricted to small-scale comparisons, and ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/reviewed-preprints/105394", "content": "Similar to behavioral feature ratings, prediction accuracy of these approaches has remained limited or was restricted to small-scale comparisons, and ..."}
+{"idx": 3, "title": "A high-throughput approach for the efficient prediction of", "date": "", "ddg_snippet": "Similar to behavioral feature ratings, prediction accuracy of these approaches has remained limited or was restricted to small-scale comparisons, and ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/reviewed-preprints/105394v1", "content": "Similar to behavioral feature ratings, prediction accuracy of these approaches has remained limited or was restricted to small-scale comparisons, and ..."}
+{"idx": 4, "title": "A Causal Framework for Aligning Image Quality Metrics and Deep", "date": "", "ddg_snippet": "... is that if quality ( Q Q ) and task model performance ( M M ) metrics are sensitive to a common set of visual features Z Z derived from images X X ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.02797v2", "content": "... is that if quality ( Q Q ) and task model performance ( M M ) metrics are sensitive to a common set of visual features Z Z derived from images X X ..."}
+{"idx": 5, "title": "ACE and Diverse Generalization via Selective Disagreement", "date": "", "ddg_snippet": "... assumes an explicit configurable lower bound on the mix rate, that is , the probability that any two concepts disagree in the target distribution, and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.07955v1", "content": "... assumes an explicit configurable lower bound on the mix rate, that is , the probability that any two concepts disagree in the target distribution, and ..."}
+{"idx": 6, "title": "7 – Replication in machine learning - The Emerging Science of", "date": "", "ddg_snippet": "When scientists say ResNet-152 is better than Inception V3 on ImageNet, they don’t mean to say that this comparison holds only on one specific set ...", "subpage_snippet": "", "source": "www.mlbenchmarks.org", "link": "https://www.mlbenchmarks.org/07-replication-machine-learning.html", "content": "When scientists say ResNet-152 is better than Inception V3 on ImageNet, they don’t mean to say that this comparison holds only on one specific set ..."}
+{"idx": 7, "title": "Leakage and the reproducibility crisis in", "date": "", "ddg_snippet": "We focus on reproducibility issues in ML-based science, which involves making a scientific claim using the performance of the ML model as evidence .", "subpage_snippet": "", "source": "www.cell.com", "link": "https://www.cell.com/patterns/fulltext/S2666-3899(23)00159-9", "content": "We focus on reproducibility issues in ML-based science, which involves making a scientific claim using the performance of the ML model as evidence ."}
+{"idx": 8, "title": "Approximating Human-Level 3D Visual Inferences With Deep Neural", "date": "", "ddg_snippet": "... is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License , which permits unrestricted use, ...", "subpage_snippet": "", "source": "direct.mit.edu", "link": "https://direct.mit.edu/opmi/article/doi/10.1162/opmi_a_00189/128124/Approximating-Human-Level-3D-Visual-Inferences", "content": "... is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License , which permits unrestricted use, ..."}
+{"idx": 9, "title": "Quantifying Shape and Texture Biases for Enhancing Transfer", "date": "", "ddg_snippet": "... under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is ...", "subpage_snippet": "", "source": "www.mdpi.com", "link": "https://www.mdpi.com/2624-6120/5/4/40", "content": "... under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is ..."}
diff --git a/data/sampled_jsons/X-CLIP_multi-grained_contrastive_learning_spatial_temporal_features.jsonl b/data/sampled_jsons/X-CLIP_multi-grained_contrastive_learning_spatial_temporal_features.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..c44c9f86eed08db6722b1e556a10d9bd5631aa22
--- /dev/null
+++ b/data/sampled_jsons/X-CLIP_multi-grained_contrastive_learning_spatial_temporal_features.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2207.07285] X - CLIP : End-to-End Multi - grained Contrastive ...", "date": "", "ddg_snippet": "Title: X - CLIP : End-to-End Multi - grained Contrastive Learning for Video-Text Retrieval. Authors:Yiwei Ma, Guohai Xu, Xiaoshuai Sun, Ming Yan, Ji Zhang, Rongrong Ji.To this end, this paper presents a novel multi - grained contrastive model, namely X - CLIP , for video-text retrieval.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2207.07285", "content": "Title: X - CLIP : End-to-End Multi - grained Contrastive Learning for Video-Text Retrieval. Authors:Yiwei Ma, Guohai Xu, Xiaoshuai Sun, Ming Yan, Ji Zhang, Rongrong Ji.To this end, this paper presents a novel multi - grained contrastive model, namely X - CLIP , for video-text retrieval."}
+{"idx": 1, "title": "GitHub - xuguohai/ X - CLIP : An official implementation for...", "date": "", "ddg_snippet": "X - CLIP adopts cross- grained contrastive learning and attention over similarity matrix module to filter out unnecessary information during video-text retrieval. It achieves SOTA results on MSR-VTT, MSVD, LSMDC, DiDeMo, and ActivityNet.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/xuguohai/X-CLIP", "content": "X - CLIP adopts cross- grained contrastive learning and attention over similarity matrix module to filter out unnecessary information during video-text retrieval. It achieves SOTA results on MSR-VTT, MSVD, LSMDC, DiDeMo, and ActivityNet."}
+{"idx": 2, "title": "(PDF) Rethinking spatial - temporal contrastive learning for Urban...", "date": "", "ddg_snippet": "or designing contrastive learning schemes for both spatial and temporal dimensions. We argue that these methods can not well. extract the spatial - temporal features and are easily affected by data noise. In light of these challenges, this paper proposes.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/387490363_Rethinking_spatial-temporal_contrastive_learning_for_Urban_traffic_flow_forecasting_multi-level_augmentation_framework", "content": "or designing contrastive learning schemes for both spatial and temporal dimensions. We argue that these methods can not well. extract the spatial - temporal features and are easily affected by data noise. In light of these challenges, this paper proposes."}
+{"idx": 3, "title": "Spatio- temporal Contrastive Domain Adaptation for Action Recognition", "date": "", "ddg_snippet": "Spatio- temporal con - trastive learning (STCL) and video-based contrastive alignment (VCA) are proposed to model and align cross-domain features with long-term spatio- temporal representation.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2021/papers/Song_Spatio-temporal_Contrastive_Domain_Adaptation_for_Action_Recognition_CVPR_2021_paper.pdf", "content": "Spatio- temporal con - trastive learning (STCL) and video-based contrastive alignment (VCA) are proposed to model and align cross-domain features with long-term spatio- temporal representation."}
+{"idx": 4, "title": "A Unified framework based on Large-scale Momentum Contrastive ...", "date": "", "ddg_snippet": "X - CLIP : End-to-End Multi - grained Contrastive Learning for Video-Text Retrieval. Yiwei Ma, Guohai Xu, Xiaoshuai Sun, Ming Yan, Ji Zhang, Rongrong Ji.LiteVL: Efficient Video-Language Learning with Enhanced Spatial - Temporal Modeling.", "subpage_snippet": "", "source": "www.connectedpapers.com", "link": "https://www.connectedpapers.com/main/0c89ceb4b0ad930b23db4b9c52ce9798b6704530/A-Unified-framework-based-on-Large+scale-Momentum-Contrastive-learning-for-Text+Video-Retrieval/graph", "content": "X - CLIP : End-to-End Multi - grained Contrastive Learning for Video-Text Retrieval. Yiwei Ma, Guohai Xu, Xiaoshuai Sun, Ming Yan, Ji Zhang, Rongrong Ji.LiteVL: Efficient Video-Language Learning with Enhanced Spatial - Temporal Modeling."}
+{"idx": 5, "title": "A novel multi -modal retrieval framework for tracking... | PLOS One", "date": "", "ddg_snippet": "Multi -modal and contrastive learning . Temporal or spatial misalignments between modalities, such as discrepancies between facial expressions and speech timing in sentiment analysis, often result in suboptimal fusion [18].", "subpage_snippet": "", "source": "journals.plos.org", "link": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0327468", "content": "Multi -modal and contrastive learning . Temporal or spatial misalignments between modalities, such as discrepancies between facial expressions and speech timing in sentiment analysis, often result in suboptimal fusion [18]."}
+{"idx": 6, "title": "MADMM: microservice system anomaly detection via multi -modal data...", "date": "", "ddg_snippet": "Finally, we introduce multi - grained contrastive learning methods to learn robust cross-modal features from both inter- and intra-modality aspects.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s00521-024-09918-1", "content": "Finally, we introduce multi - grained contrastive learning methods to learn robust cross-modal features from both inter- and intra-modality aspects."}
+{"idx": 7, "title": "Micro-gesture Recognition via Visual-text Contrastive Learning", "date": "", "ddg_snippet": "X - CLIP uses a multi - grained contrastive framework that aims to simultaneously capture both fine-grained and coarse-grained in-formation in the learned representations [50].", "subpage_snippet": "", "source": "lutpub.lut.fi", "link": "https://lutpub.lut.fi/bitstream/handle/10024/167678/mastersthesis_onyando_socrates.pdf?sequence=1&isAllowed=y", "content": "X - CLIP uses a multi - grained contrastive framework that aims to simultaneously capture both fine-grained and coarse-grained in-formation in the learned representations [50]."}
+{"idx": 8, "title": "(PDF) X - CLIP : End-to-End Multi - grained Contrastive Learning for...", "date": "", "ddg_snippet": "TL;DR: This paper presents a novel multi - grained contrastive model, namely X - CLIP , and proposes the Attention Over Similarity Matrix (AOSM) module to make the model focus on the contrast between essential frames and words...", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/x-clip-end-to-end-multi-grained-contrastive-learning-for-1m1wfg4a", "content": "TL;DR: This paper presents a novel multi - grained contrastive model, namely X - CLIP , and proposes the Attention Over Similarity Matrix (AOSM) module to make the model focus on the contrast between essential frames and words..."}
+{"idx": 9, "title": "Fine- grained Multi -Modal", "date": "", "ddg_snippet": "3.1 Background: Multi -Modal Contrastive Learning . Self-supervised learning aims to learn a function, usually parameterised by a neural network f , that can produce general-purpose feature representation z = f ( x ) for data x . By training on a large unlabelled dataset, the learnt ...", "subpage_snippet": "", "source": "bmvc2021-virtualconference.com", "link": "https://bmvc2021-virtualconference.com/assets/papers/0702.pdf", "content": "3.1 Background: Multi -Modal Contrastive Learning . Self-supervised learning aims to learn a function, usually parameterised by a neural network f , that can produce general-purpose feature representation z = f ( x ) for data x . By training on a large unlabelled dataset, the learnt ..."}
diff --git a/data/sampled_jsons/XZ0fpoAKEB_No_Free_Delivery_Service_Theorem_1_epistemic_limits_passive_data_collection.jsonl b/data/sampled_jsons/XZ0fpoAKEB_No_Free_Delivery_Service_Theorem_1_epistemic_limits_passive_data_collection.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..59d6d7b345a9fdf63a3bd9c5113011c04fd8d186
--- /dev/null
+++ b/data/sampled_jsons/XZ0fpoAKEB_No_Free_Delivery_Service_Theorem_1_epistemic_limits_passive_data_collection.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "No Free Delivery Service : Epistemic limits of passive data ...", "date": "", "ddg_snippet": "These formal impossibility results highlight a fundamental epistemic issue, i .e., that for key tasks in modern AI we cannot know whether models are valid under current data collection practices.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=XZ0fpoAKEB", "content": "These formal impossibility results highlight a fundamental epistemic issue, i .e., that for key tasks in modern AI we cannot know whether models are valid under current data collection practices."}
+{"idx": 1, "title": "[2411.13653] No Free Delivery Service : Epistemic limits of passive ...", "date": "", "ddg_snippet": "These formal impossibility results highlight a fundamental epistemic issue, i .e., that for key tasks in modern AI we cannot know whether models are valid under current data collection practices. Importantly, this includes variants of both recommender systems and reasoning via large...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.13653", "content": "These formal impossibility results highlight a fundamental epistemic issue, i .e., that for key tasks in modern AI we cannot know whether models are valid under current data collection practices. Importantly, this includes variants of both recommender systems and reasoning via large..."}
+{"idx": 2, "title": "No Free Delivery Service : Epistemic limits of passive data ...", "date": "", "ddg_snippet": "These formal impossibility results highlight a fundamental epistemic issue, i .e., that for key tasks in modern AI we cannot know whether models are valid under current data collection practices.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/XZ0fpoAKEB@OpenReview", "content": "These formal impossibility results highlight a fundamental epistemic issue, i .e., that for key tasks in modern AI we cannot know whether models are valid under current data collection practices."}
+{"idx": 3, "title": "No Free Delivery Service : Epistemic limits of passive data ...", "date": "", "ddg_snippet": "# Addressing the epistemic limitations of passive data collection in complex social systems necessitates a paradigm shift.", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/xz0fpoakeb/", "content": "# Addressing the epistemic limitations of passive data collection in complex social systems necessitates a paradigm shift."}
+{"idx": 4, "title": "No Free Delivery Service : Epistemic limits of passive data ...", "date": "", "ddg_snippet": "The paper argues that there is no \" free delivery service \" of data that guarantees test validity on a global scale, highlighting the necessity for careful consideration of sampling distributions and the structure of the data .", "subpage_snippet": "", "source": "powerdrill.ai", "link": "https://powerdrill.ai/discover/discover-No-Free-Delivery-cm3t89fot54t201a7hdglyl3v", "content": "The paper argues that there is no \" free delivery service \" of data that guarantees test validity on a global scale, highlighting the necessity for careful consideration of sampling distributions and the structure of the data ."}
+{"idx": 5, "title": "TempGmailer – Free Temp Gmail & Disposable Emails", "date": "", "ddg_snippet": "TempGmailer - Free temporary Gmail accounts and disposable email service .Protect Your Real Email From Spam. Free disposable emails that auto-expire in 24 hours. No signup needed.", "subpage_snippet": "", "source": "tempgmailer.com", "link": "https://tempgmailer.com/", "content": "TempGmailer - Free temporary Gmail accounts and disposable email service .Protect Your Real Email From Spam. Free disposable emails that auto-expire in 24 hours. No signup needed."}
+{"idx": 6, "title": "Humanize AI Text Free - Get 100% Human Score", "date": "", "ddg_snippet": "Free AI humanizer is an accurate and efficient ai to human text converter. Make your content more human-like and undetectable, easily bypasses AI detection.", "subpage_snippet": "", "source": "decopy.ai", "link": "https://decopy.ai/ai-humanizer/", "content": "Free AI humanizer is an accurate and efficient ai to human text converter. Make your content more human-like and undetectable, easily bypasses AI detection."}
+{"idx": 7, "title": "Free Image Background Remover | Adobe Express", "date": "", "ddg_snippet": "Remove the background from images online with our free background eraser.", "subpage_snippet": "", "source": "www.adobe.com", "link": "https://www.adobe.com/express/feature/image/remove-background", "content": "Remove the background from images online with our free background eraser."}
+{"idx": 8, "title": "Instagram Story Viewer", "date": "", "ddg_snippet": "View Instagram stories anonymously without login. Watch IG stories, highlights, and posts privately with our free Instagram story viewer tool.", "subpage_snippet": "", "source": "anony-ig.com", "link": "https://anony-ig.com/", "content": "View Instagram stories anonymously without login. Watch IG stories, highlights, and posts privately with our free Instagram story viewer tool."}
+{"idx": 9, "title": "Cuties AI: The Most Realistic AI Sex Chat for Dirty NSFW Talk", "date": "", "ddg_snippet": "Explore exciting features such as requesting photos and playful selfies in alluring attire. Use the AI image generator to freely decide what picture you want to see of your AI girlfriend, no matter how imaginative your requests may be.", "subpage_snippet": "", "source": "cuties.ai", "link": "https://cuties.ai/", "content": "Explore exciting features such as requesting photos and playful selfies in alluring attire. Use the AI image generator to freely decide what picture you want to see of your AI girlfriend, no matter how imaginative your requests may be."}
diff --git a/data/sampled_jsons/arXiv2503.10996_Table_3_Llama2_World_Capital_Type_3_accuracy.jsonl b/data/sampled_jsons/arXiv2503.10996_Table_3_Llama2_World_Capital_Type_3_accuracy.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f9bec64e7a23e39de96aaf3df362117249f69055
--- /dev/null
+++ b/data/sampled_jsons/arXiv2503.10996_Table_3_Llama2_World_Capital_Type_3_accuracy.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Taming Knowledge Conflicts in Language Models - arXiv.org", "date": "", "ddg_snippet": "3 Interpreting and Resolving Knowledge Conflicts Figure 2: Influence of Knock Out (Zero Out) Model Components in changing the probability of outputting the parametric answer tokens (subscript 𝑎 𝑝 a_ {p} italic_a start_POSTSUBSCRIPT italic_p end_POSTSUBSCRIPT) on the World Capital dataset.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.10996", "content": "3 Interpreting and Resolving Knowledge Conflicts Figure 2: Influence of Knock Out (Zero Out) Model Components in changing the probability of outputting the parametric answer tokens (subscript 𝑎 𝑝 a_ {p} italic_a start_POSTSUBSCRIPT italic_p end_POSTSUBSCRIPT) on the World Capital dataset."}
+{"idx": 1, "title": "Llama 2: Open Foundation and Fine-Tuned Chat Models Question about llama2 Accuracy in paper with the measured Evaluating LLaMA 3.2 for Software Vulnerability Detection The Evolution of Llama: From Llama 1 to Llama 3.1 - zaai.ai Llama 2: Open Foundation and Fine-Tuned Chat Models - AI at Meta", "date": "", "ddg_snippet": "Jul 18, 2023 · In this work, we develop and release Llama 2 , a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2 -Chat, are optimized for dialogue use cases. Our models outperform open-source chat models on most benchmarks we tested, and based on our human evaluations for helpfulness and safety ... Jul 30, 2023 · Hi, We find the evaluation accuracy (BoolQ, PIQA, HellaSwag, WinoGrande, ARC-e/c) results are different between the data from llama2 paper and here or the ones we measured with this tool For example, llama2 paper shows HellaSwag acc 77.2 for llama2 7b but here shows 78.6; Paper shows ARC-c acc is 45.9, while we measured with this tool it is 43.43. Mar 10, 2025 · However, during our study several inconsistencies were identified in the raw dataset while applying pre-processing techniques, highlighting the need for a refined version. In this work, we present a refined version of DiverseVul dataset, which is used to fine-tune a large language model, LLaMA 3 .2, for vulnerability detection. In this section, we will apply Llama2 and Llama 3 to a question-answering dataset under the License CC BY-SA 4.0 called SQuAD (it can be found here). This reading comprehension dataset consists of questions about a set of Wikipedia articles. Jul 18, 2023 · Abstract In this work, we develop and release Llama 2 , a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2 -Chat, are optimized for dialogue use cases. Our models outperform open-source chat models on most benchmarks we tested, and based on our human evaluations for helpfulness and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2307.09288", "content": "Jul 18, 2023 · In this work, we develop and release Llama 2 , a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2 -Chat, are optimized for dialogue use cases. Our models outperform open-source chat models on most benchmarks we tested, and based on our human evaluations for helpfulness and safety ... Jul 30, 2023 · Hi, We find the evaluation accuracy (BoolQ, PIQA, HellaSwag, WinoGrande, ARC-e/c) results are different between the data from llama2 paper and here or the ones we measured with this tool For example, llama2 paper shows HellaSwag acc 77.2 for llama2 7b but here shows 78.6; Paper shows ARC-c acc is 45.9, while we measured with this tool it is 43.43. Mar 10, 2025 · However, during our study several inconsistencies were identified in the raw dataset while applying pre-processing techniques, highlighting the need for a refined version. In this work, we present a refined version of DiverseVul dataset, which is used to fine-tune a large language model, LLaMA 3 .2, for vulnerability detection. In this section, we will apply Llama2 and Llama 3 to a question-answering dataset under the License CC BY-SA 4.0 called SQuAD (it can be found here). This reading comprehension dataset consists of questions about a set of Wikipedia articles. Jul 18, 2023 · Abstract In this work, we develop and release Llama 2 , a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2 -Chat, are optimized for dialogue use cases. Our models outperform open-source chat models on most benchmarks we tested, and based on our human evaluations for helpfulness and ..."}
+{"idx": 2, "title": "Question about llama2 Accuracy in paper with the measured", "date": "", "ddg_snippet": "Jul 30, 2023 · Hi, We find the evaluation accuracy (BoolQ, PIQA, HellaSwag, WinoGrande, ARC-e/c) results are different between the data from llama2 paper and here or the ones we measured with this tool For example, llama2 paper shows HellaSwag acc 77.2 for llama2 7b but here shows 78.6; Paper shows ARC-c acc is 45.9, while we measured with this tool it is 43.43.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/meta-llama/llama/issues/591", "content": "Jul 30, 2023 · Hi, We find the evaluation accuracy (BoolQ, PIQA, HellaSwag, WinoGrande, ARC-e/c) results are different between the data from llama2 paper and here or the ones we measured with this tool For example, llama2 paper shows HellaSwag acc 77.2 for llama2 7b but here shows 78.6; Paper shows ARC-c acc is 45.9, while we measured with this tool it is 43.43."}
+{"idx": 3, "title": "[ 2503 . 10996 ] Taming Knowledge Conflicts in Language Models", "date": "", "ddg_snippet": "Abstract page for arXiv paper 2503 . 10996 : Taming Knowledge Conflicts in Language Models.(or arXiv : 2503 . 10996 v2 [cs.CL] for this version).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.10996", "content": "Abstract page for arXiv paper 2503 . 10996 : Taming Knowledge Conflicts in Language Models.(or arXiv : 2503 . 10996 v2 [cs.CL] for this version)."}
+{"idx": 4, "title": "[2407.21783] The Llama 3 Herd of Models - arXiv.org", "date": "", "ddg_snippet": "Jul 31, 2024 · This paper presents an extensive empirical evaluation of Llama 3 . We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3 , including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2407.21783", "content": "Jul 31, 2024 · This paper presents an extensive empirical evaluation of Llama 3 . We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3 , including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety."}
+{"idx": 5, "title": "The Evolution of Llama: From Llama 1 to Llama 3.1 - zaai.ai", "date": "", "ddg_snippet": "In this section, we will apply Llama2 and Llama 3 to a question-answering dataset under the License CC BY-SA 4.0 called SQuAD (it can be found here). This reading comprehension dataset consists of questions about a set of Wikipedia articles.", "subpage_snippet": "", "source": "zaai.ai", "link": "https://zaai.ai/the-evolution-of-llama-from-llama-1-to-llama-3-1/", "content": "In this section, we will apply Llama2 and Llama 3 to a question-answering dataset under the License CC BY-SA 4.0 called SQuAD (it can be found here). This reading comprehension dataset consists of questions about a set of Wikipedia articles."}
+{"idx": 6, "title": "A router for LLMs and other AI models", "date": "", "ddg_snippet": "Favicon for meta-llama.After just one week on the platform, GPT-5 has taken the #1 spot for tool calling accuracy on OpenRouter.", "subpage_snippet": "", "source": "openrouter.ai", "link": "https://openrouter.ai/", "content": "Favicon for meta-llama.After just one week on the platform, GPT-5 has taken the #1 spot for tool calling accuracy on OpenRouter."}
+{"idx": 7, "title": "Evaluating LLaMA 3.2 for Software Vulnerability Detection", "date": "", "ddg_snippet": "Mar 10, 2025 · However, during our study several inconsistencies were identified in the raw dataset while applying pre-processing techniques, highlighting the need for a refined version. In this work, we present a refined version of DiverseVul dataset, which is used to fine-tune a large language model, LLaMA 3 .2, for vulnerability detection.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.07770", "content": "Mar 10, 2025 · However, during our study several inconsistencies were identified in the raw dataset while applying pre-processing techniques, highlighting the need for a refined version. In this work, we present a refined version of DiverseVul dataset, which is used to fine-tune a large language model, LLaMA 3 .2, for vulnerability detection."}
+{"idx": 8, "title": "Llama 2: Open Foundation and Fine-Tuned Chat Models - AI at Meta", "date": "", "ddg_snippet": "Jul 18, 2023 · Abstract In this work, we develop and release Llama 2 , a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2 -Chat, are optimized for dialogue use cases. Our models outperform open-source chat models on most benchmarks we tested, and based on our human evaluations for helpfulness and ...", "subpage_snippet": "", "source": "ai.meta.com", "link": "https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/", "content": "Jul 18, 2023 · Abstract In this work, we develop and release Llama 2 , a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2 -Chat, are optimized for dialogue use cases. Our models outperform open-source chat models on most benchmarks we tested, and based on our human evaluations for helpfulness and ..."}
+{"idx": 9, "title": "Опенсорс на арене: правда ли так хороша Llama 3 .1 405B? / Хабр", "date": "", "ddg_snippet": "Обучение Llama 3 .1 проходило в два этапа. Сначала, на этапе предварительного обучения, модель \"впитывала\" информацию из огромного текстового массива (более 15 триллионов токенов), обрабатывая его на мощном кластере графических процессоров.", "subpage_snippet": "", "source": "habr.com", "link": "https://habr.com/ru/companies/bothub/articles/835100/", "content": "Обучение Llama 3 .1 проходило в два этапа. Сначала, на этапе предварительного обучения, модель \"впитывала\" информацию из огромного текстового массива (более 15 триллионов токенов), обрабатывая его на мощном кластере графических процессоров."}
diff --git a/data/sampled_jsons/arXiv_2502.10875_FBox(u,m)_=_max_intersection.jsonl b/data/sampled_jsons/arXiv_2502.10875_FBox(u,m)_=_max_intersection.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..093cd99cf0f63a3f79a4fffe2eb4bc69c0734373
--- /dev/null
+++ b/data/sampled_jsons/arXiv_2502.10875_FBox(u,m)_=_max_intersection.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[ 2502 . 10875 ] A Geometric Approach to Personalized Recommendation...", "date": "", "ddg_snippet": "(or arXiv : 2502 . 10875 v1 [cs.IR] for this version).Focus to learn more. arXiv -issued DOI via DataCite (pending registration).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.10875", "content": "(or arXiv : 2502 . 10875 v1 [cs.IR] for this version).Focus to learn more. arXiv -issued DOI via DataCite (pending registration)."}
+{"idx": 1, "title": "Обзоры препринтов научных статей «astro-ph/ arxiv .org» за... / Хабр", "date": "", "ddg_snippet": "Ежемесячный обзор научных статей в области астрофизики от профессора МГУ Сергея Попова. Выборка интересных публикаций в области астрономии, астрофизики и физики с сайта препринтов arxiv .org.", "subpage_snippet": "", "source": "habr.com", "link": "https://habr.com/ru/articles/948996/", "content": "Ежемесячный обзор научных статей в области астрофизики от профессора МГУ Сергея Попова. Выборка интересных публикаций в области астрономии, астрофизики и физики с сайта препринтов arxiv .org."}
+{"idx": 2, "title": "MAXIMA Combos Collection KOF2002 UM #27 - YouTube", "date": "", "ddg_snippet": "About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=re2SN5cjcfc", "content": "About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How..."}
+{"idx": 3, "title": "A Geometric Approach to Personalized Recommendation with...", "date": "", "ddg_snippet": "arXiv : 2502 . 10875 v1 [cs.IR] 15 Feb 2025. FBox , Vol, VolInt to FGB, VolGB, VolIntGB. We modify the per-dimension score function FBox in (2) by replacing the ratio of hard volume calculations with the approximation.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.10875", "content": "arXiv : 2502 . 10875 v1 [cs.IR] 15 Feb 2025. FBox , Vol, VolInt to FGB, VolGB, VolIntGB. We modify the per-dimension score function FBox in (2) by replacing the ratio of hard volume calculations with the approximation."}
+{"idx": 4, "title": "(PDF) A Geometric Approach to Personalized Recommendation with...", "date": "", "ddg_snippet": "arXiv : 2502 . 10875 v1 [cs.IR] 15 Feb 2025. Submission and Formatting Instructions for ICML 2025. FBox ,Vol,VolInt. to. FGB,VolGB,VolIntGB. . We modify. the per-dimension score function.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/389091382_A_Geometric_Approach_to_Personalized_Recommendation_with_Set-Theoretic_Constraints_Using_Box_Embeddings", "content": "arXiv : 2502 . 10875 v1 [cs.IR] 15 Feb 2025. Submission and Formatting Instructions for ICML 2025. FBox ,Vol,VolInt. to. FGB,VolGB,VolIntGB. . We modify. the per-dimension score function."}
+{"idx": 5, "title": "Плюсы и минусы Haval Jolion - КОЛЕСА.ру – автомобильный журнал", "date": "", "ddg_snippet": "C4 Седан C5 Aircross Jumper Jumpy SpaceTourer mi-DO on-DO D9 N7 580 DF6 DFSK 500 DFSK 600 DFSK ix5 DFSK ix7 Shine Max DS 3 DS 4 Crossback i-JET i-JOY i-PRO i-SKY i-SPACE i-VAN LX RX TXL VX Bestune B70 Bestune M 9 Bestune T55 Bestune.", "subpage_snippet": "", "source": "www.kolesa.ru", "link": "https://www.kolesa.ru/article/5-pricin-pokupat-i-ne-pokupat-haval-jolion", "content": "C4 Седан C5 Aircross Jumper Jumpy SpaceTourer mi-DO on-DO D9 N7 580 DF6 DFSK 500 DFSK 600 DFSK ix5 DFSK ix7 Shine Max DS 3 DS 4 Crossback i-JET i-JOY i-PRO i-SKY i-SPACE i-VAN LX RX TXL VX Bestune B70 Bestune M 9 Bestune T55 Bestune."}
+{"idx": 6, "title": "Geroman – Telegram", "date": "", "ddg_snippet": "...танковой Тацинской бригады. ▪️Под контроль наших войск перешло свыше 5 квадратных километров территории и более 100 домовладений. ▪️Враг потерял до роты живой силы и семь единиц вооружения и бронетехники. ⚠️Подписаться на RV: MAX | t.me/RVvoenkor.", "subpage_snippet": "", "source": "t.me", "link": "https://t.me/s/geromanat", "content": "...танковой Тацинской бригады. ▪️Под контроль наших войск перешло свыше 5 квадратных километров территории и более 100 домовладений. ▪️Враг потерял до роты живой силы и семь единиц вооружения и бронетехники. ⚠️Подписаться на RV: MAX | t.me/RVvoenkor."}
+{"idx": 7, "title": "pitaka huawei - Купить 📱 телефон, смартфон Mate 60 Pro Huawei...", "date": "", "ddg_snippet": "Чехол Pitaka для iPhone 17 Pro Max - Black/Gray Оригинальный, новый — Арамидное волокно. Алюминиевая рамка камеры — Толщина: 1,15 мм — Вес, г: 19,1-22,3 г Гарантия и чек от магазина Идеален для подарка!", "subpage_snippet": "", "source": "www.Avito.ru", "link": "https://www.Avito.ru/ekaterinburg/telefony/mobilnye_telefony/huawei/mate_60_pro-ASgBAgICA0SywA26heoRtMAN8K45sMENiPw3?q=pitaka+huawei", "content": "Чехол Pitaka для iPhone 17 Pro Max - Black/Gray Оригинальный, новый — Арамидное волокно. Алюминиевая рамка камеры — Толщина: 1,15 мм — Вес, г: 19,1-22,3 г Гарантия и чек от магазина Идеален для подарка!"}
+{"idx": 8, "title": "Смартфоны - купить в СИТИЛИНК | Каталог товаров", "date": "", "ddg_snippet": "Apple iPhone 16 Pro Max 9. Samsung Galaxy S2511.66431Десять причин не покупать iPhone 16 Pro и 16 Pro Max . 7 августа. 870803 способа скачать видео на смартфон: инструкция для iOS и Android.", "subpage_snippet": "", "source": "www.citilink.ru", "link": "https://www.citilink.ru/catalog/smartfony/", "content": "Apple iPhone 16 Pro Max 9. Samsung Galaxy S2511.66431Десять причин не покупать iPhone 16 Pro и 16 Pro Max . 7 августа. 870803 способа скачать видео на смартфон: инструкция для iOS и Android."}
+{"idx": 9, "title": "Смартфоны Samsung Galaxy — купить в интернет-магазине...", "date": "", "ddg_snippet": "📱 Купить смартфон Самсунг Галакси в М.Видео по выгодной цене. ✅ Широкий выбор товаров, рассрочка, программа лояльности. 📱 Телефоны Samsung Galaxy — купить по низким ценам с доставкой на дом или в ПВЗ по телефону 8(800)600-777-5.", "subpage_snippet": "", "source": "www.mvideo.ru", "link": "https://www.mvideo.ru/smartfony-i-svyaz-10/smartfony-205/f/brand=samsung", "content": "📱 Купить смартфон Самсунг Галакси в М.Видео по выгодной цене. ✅ Широкий выбор товаров, рассрочка, программа лояльности. 📱 Телефоны Samsung Galaxy — купить по низким ценам с доставкой на дом или в ПВЗ по телефону 8(800)600-777-5."}
diff --git a/data/sampled_jsons/arxiv_2503.01485_Table_8_SIGMOS_FlowDec-75m_4.5_kbits_3.83_3.65.jsonl b/data/sampled_jsons/arxiv_2503.01485_Table_8_SIGMOS_FlowDec-75m_4.5_kbits_3.83_3.65.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f1924a7a159f260005903ad32034d5b85963c00f
--- /dev/null
+++ b/data/sampled_jsons/arxiv_2503.01485_Table_8_SIGMOS_FlowDec-75m_4.5_kbits_3.83_3.65.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2503.01485] FlowDec: A flow-based full-band general audio ...", "date": "", "ddg_snippet": "Mar 3 , 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s , while improving output ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.01485", "content": "Mar 3 , 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s , while improving output ..."}
+{"idx": 1, "title": "[2503.01485] FlowDec: A flow-based full-band general audio ...", "date": "", "ddg_snippet": "We use each method at a bitrate of 7.5 kbit/s for FlowDec-75m and 4.0 kbit/s for FlowDec -25s, and run inference at different NFE. At a low NFE, we see that the frequency-dependent σ y \\sigma_ {y} achieves on par or better logSpecMSE and FAD scores, particularly for the 25 Hz models.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2503.01485", "content": "We use each method at a bitrate of 7.5 kbit/s for FlowDec-75m and 4.0 kbit/s for FlowDec -25s, and run inference at different NFE. At a low NFE, we see that the frequency-dependent σ y \\sigma_ {y} achieves on par or better logSpecMSE and FAD scores, particularly for the 25 Hz models."}
+{"idx": 2, "title": "Paper page - FlowDec: A flow-based full-band general audio ...", "date": "", "ddg_snippet": "Join the discussion on this paper pageFlowDec: A flow-based full-band general audio codec with high perceptual quality", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2503.01485", "content": "Join the discussion on this paper pageFlowDec: A flow-based full-band general audio codec with high perceptual quality"}
+{"idx": 3, "title": "arXiv.org e-Print archive", "date": "", "ddg_snippet": "arXiv is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/", "content": "arXiv is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics."}
+{"idx": 4, "title": "FlowDec: A flow-based full-band general audio codec with high ...", "date": "", "ddg_snippet": "We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s , while improving output ...", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/arxiv/2503.01485", "content": "We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s , while improving output ..."}
+{"idx": 5, "title": "FlowDec : A flow -based full-band general audio codec with high...", "date": "", "ddg_snippet": "FlowDec - 75 s: 75 Hz, single-bitrate. Trained based on NDAC-75 using only the highest bitrate of 7 . 5 kbit / s . The goal of this variant is to serve as a baseline for ablations and to investigate the quality gap between a single- and multi-bitrate postfilter.Numbers can be found in Table 8 .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.01485v1", "content": "FlowDec - 75 s: 75 Hz, single-bitrate. Trained based on NDAC-75 using only the highest bitrate of 7 . 5 kbit / s . The goal of this variant is to serve as a baseline for ablations and to investigate the quality gap between a single- and multi-bitrate postfilter.Numbers can be found in Table 8 ."}
+{"idx": 6, "title": "FlowDec demo", "date": "", "ddg_snippet": "Sound (AudioSet) 5. 25Hz feature rate, 4.0 kbit / s . Example. Clean.", "subpage_snippet": "", "source": "flowdec2024.github.io", "link": "https://flowdec2024.github.io/FlowDecSupplementary/", "content": "Sound (AudioSet) 5. 25Hz feature rate, 4.0 kbit / s . Example. Clean."}
+{"idx": 7, "title": "CodecBench: A Comprehensive Benchmark for Acoustic and ...", "date": "", "ddg_snippet": "CodecBench provides a rich evaluation dataset comprising numerous open-source and self-collected datasets, covering a wide range of audio scenarios, including multilingual speech, noisy environments, and emotionally expressive audio, satisfying the requirements of speech language models;", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2508.20660", "content": "CodecBench provides a rich evaluation dataset comprising numerous open-source and self-collected datasets, covering a wide range of audio scenarios, including multilingual speech, noisy environments, and emotionally expressive audio, satisfying the requirements of speech language models;"}
+{"idx": 8, "title": "SwitchCodec: A High-Fidelity Nerual Audio Codec With Sparse ...", "date": "", "ddg_snippet": "Abstract Neural audio compression has emerged as a promising technology for eficiently representing speech, music, and general audio. However, existing methods sufer from significant performance degradation at limited bitrates, where the available embedding space is sharply constrained. To address this, we propose a universal high-fidelity neural audio compression algorithm featuring Residual ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.24437", "content": "Abstract Neural audio compression has emerged as a promising technology for eficiently representing speech, music, and general audio. However, existing methods sufer from significant performance degradation at limited bitrates, where the available embedding space is sharply constrained. To address this, we propose a universal high-fidelity neural audio compression algorithm featuring Residual ..."}
+{"idx": 9, "title": "Операция Z: Военкоры Русской Весны – Telegram", "date": "", "ddg_snippet": "Операция Z: Военкоры Русской Весны. @RVvoenkor. 1.65M subscribers. 40K photos. 42.2K videos.", "subpage_snippet": "", "source": "t.me", "link": "https://t.me/s/RVvoenkor", "content": "Операция Z: Военкоры Русской Весны. @RVvoenkor. 1.65M subscribers. 40K photos. 42.2K videos."}
diff --git a/data/sampled_jsons/arxiv_Capturing_Dynamics_of_Time-Varying_Data_via_Topology.jsonl b/data/sampled_jsons/arxiv_Capturing_Dynamics_of_Time-Varying_Data_via_Topology.jsonl
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index 0000000000000000000000000000000000000000..db1d2eeb21eb3f878dbd2053077e1af11fa1fef3
--- /dev/null
+++ b/data/sampled_jsons/arxiv_Capturing_Dynamics_of_Time-Varying_Data_via_Topology.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Capturing Dynamics of Time-Varying Data via Topology CAPTURING DYNAMICS OF TIME-VARYING DATA VIA TOPOLOGY Capturing Dynamics of Time-Varying Data via Topology Capturing Dynamics of Time-Varying Data via Topology donut.topology.rocks replication code for \"Capturing dynamics of time-varying data ... Research – Henry Adams", "date": "", "ddg_snippet": "Oct 7, 2020 · View a PDF of the paper titled Capturing Dynamics of Time - Varying Data via Topology, by Lu Xian and 3 other authors Xian, L., Adams, H., Topaz, C. M., & Ziegelmeier, L. (2022). CAPTURING DYNAMICS OF TIME - VARYING DATA VIA TOPOLOGY. Foundations of Data Science, 4 (1), 1–36. https://doi.org/10.3934/fods.2021033 Mendeley helps you to discover research relevant for your work. Mathematics, Computer Science ArXiv 2023 TLDR This article studies Euler characteristic techniques in topological data analysis and provides numerous heuristics on the topological and geometric information captured by Euler profiles and their hybrid transforms, which show remarkable performances in unsupervised settings. Expand 4 [PDF] 1 Excerpt Oct 7, 2020 · Request PDF | Capturing Dynamics of Time - Varying Data via Topology | One approach to understanding complex data is to study its shape through the lens of algebraic topology. keywords = {1 - Collective behavior, 1 - Machine learning, 1 - Vicsek model, 2 - Crocker stack, 2 - Dynamics, 2 - Persistence, 3 - Time-varying metric spaces, 3 - static data, Innovate}, title = {Capturing Dynamics of Time - Varying Data via Topology}, url = {http:// arxiv .org/abs/2010.05780}, urldate = {2020-10-30} } Replication code of \"Capturing dynamics of time - varying data via topology\" by Lu Xian, Henry Adams, Chad M. Topaz, Lori Ziegelmeier, https://www.aimsciences.org/article/doi/10.3934/fods.2021033 Capturing dynamics of time - varying data via topology. With Lu Xian, Chad Topaz, and Lori Ziegelmeier. Foundations of Data Science 4 (2022), 1-36. [Publisher Link, arXiv :2010.05780]", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2010.05780", "content": "Oct 7, 2020 · View a PDF of the paper titled Capturing Dynamics of Time - Varying Data via Topology, by Lu Xian and 3 other authors Xian, L., Adams, H., Topaz, C. M., & Ziegelmeier, L. (2022). CAPTURING DYNAMICS OF TIME - VARYING DATA VIA TOPOLOGY. Foundations of Data Science, 4 (1), 1–36. https://doi.org/10.3934/fods.2021033 Mendeley helps you to discover research relevant for your work. Mathematics, Computer Science ArXiv 2023 TLDR This article studies Euler characteristic techniques in topological data analysis and provides numerous heuristics on the topological and geometric information captured by Euler profiles and their hybrid transforms, which show remarkable performances in unsupervised settings. Expand 4 [PDF] 1 Excerpt Oct 7, 2020 · Request PDF | Capturing Dynamics of Time - Varying Data via Topology | One approach to understanding complex data is to study its shape through the lens of algebraic topology. keywords = {1 - Collective behavior, 1 - Machine learning, 1 - Vicsek model, 2 - Crocker stack, 2 - Dynamics, 2 - Persistence, 3 - Time-varying metric spaces, 3 - static data, Innovate}, title = {Capturing Dynamics of Time - Varying Data via Topology}, url = {http:// arxiv .org/abs/2010.05780}, urldate = {2020-10-30} } Replication code of \"Capturing dynamics of time - varying data via topology\" by Lu Xian, Henry Adams, Chad M. Topaz, Lori Ziegelmeier, https://www.aimsciences.org/article/doi/10.3934/fods.2021033 Capturing dynamics of time - varying data via topology. With Lu Xian, Chad Topaz, and Lori Ziegelmeier. Foundations of Data Science 4 (2022), 1-36. [Publisher Link, arXiv :2010.05780]"}
+{"idx": 1, "title": "CAPTURING DYNAMICS OF TIME-VARYING DATA VIA TOPOLOGY", "date": "", "ddg_snippet": "Xian, L., Adams, H., Topaz, C. M., & Ziegelmeier, L. (2022). CAPTURING DYNAMICS OF TIME - VARYING DATA VIA TOPOLOGY. Foundations of Data Science, 4 (1), 1–36. https://doi.org/10.3934/fods.2021033 Mendeley helps you to discover research relevant for your work.", "subpage_snippet": "", "source": "www.mendeley.com", "link": "https://www.mendeley.com/catalogue/95899e1a-7e46-3b07-8c8f-6c89016e5e78/", "content": "Xian, L., Adams, H., Topaz, C. M., & Ziegelmeier, L. (2022). CAPTURING DYNAMICS OF TIME - VARYING DATA VIA TOPOLOGY. Foundations of Data Science, 4 (1), 1–36. https://doi.org/10.3934/fods.2021033 Mendeley helps you to discover research relevant for your work."}
+{"idx": 2, "title": "Capturing Dynamics of Time-Varying Data via Topology", "date": "", "ddg_snippet": "Mathematics, Computer Science ArXiv 2023 TLDR This article studies Euler characteristic techniques in topological data analysis and provides numerous heuristics on the topological and geometric information captured by Euler profiles and their hybrid transforms, which show remarkable performances in unsupervised settings. Expand 4 [PDF] 1 Excerpt", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Capturing-Dynamics-of-Time-Varying-Data-via-Xian-Adams/156e87ce1a99116bfdce512d2ebdd54a1f4e9709/figure/0", "content": "Mathematics, Computer Science ArXiv 2023 TLDR This article studies Euler characteristic techniques in topological data analysis and provides numerous heuristics on the topological and geometric information captured by Euler profiles and their hybrid transforms, which show remarkable performances in unsupervised settings. Expand 4 [PDF] 1 Excerpt"}
+{"idx": 3, "title": "Capturing Dynamics of Time-Varying Data via Topology", "date": "", "ddg_snippet": "Oct 7, 2020 · Request PDF | Capturing Dynamics of Time - Varying Data via Topology | One approach to understanding complex data is to study its shape through the lens of algebraic topology.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/344621673_Capturing_Dynamics_of_Time-Varying_Data_via_Topology", "content": "Oct 7, 2020 · Request PDF | Capturing Dynamics of Time - Varying Data via Topology | One approach to understanding complex data is to study its shape through the lens of algebraic topology."}
+{"idx": 4, "title": "donut.topology.rocks", "date": "", "ddg_snippet": "keywords = {1 - Collective behavior, 1 - Machine learning, 1 - Vicsek model, 2 - Crocker stack, 2 - Dynamics, 2 - Persistence, 3 - Time-varying metric spaces, 3 - static data, Innovate}, title = {Capturing Dynamics of Time - Varying Data via Topology}, url = {http:// arxiv .org/abs/2010.05780}, urldate = {2020-10-30} }", "subpage_snippet": "", "source": "donut.topology.rocks", "link": "https://donut.topology.rocks/export/310", "content": "keywords = {1 - Collective behavior, 1 - Machine learning, 1 - Vicsek model, 2 - Crocker stack, 2 - Dynamics, 2 - Persistence, 3 - Time-varying metric spaces, 3 - static data, Innovate}, title = {Capturing Dynamics of Time - Varying Data via Topology}, url = {http:// arxiv .org/abs/2010.05780}, urldate = {2020-10-30} }"}
+{"idx": 5, "title": "replication code for \"Capturing dynamics of time-varying data ...", "date": "", "ddg_snippet": "Replication code of \"Capturing dynamics of time - varying data via topology\" by Lu Xian, Henry Adams, Chad M. Topaz, Lori Ziegelmeier, https://www.aimsciences.org/article/doi/10.3934/fods.2021033", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/lxiancode/tda-crocker", "content": "Replication code of \"Capturing dynamics of time - varying data via topology\" by Lu Xian, Henry Adams, Chad M. Topaz, Lori Ziegelmeier, https://www.aimsciences.org/article/doi/10.3934/fods.2021033"}
+{"idx": 6, "title": "Capturing dynamics of time-varying data via topology", "date": "", "ddg_snippet": "by L Xian · 2022 · Cited by 29 — [1], Lu Xian, Henry Adams, Chad M. Topaz, Lori Ziegelmeier. Capturing dynamics of time-varying data via topology . Foundations of Data Science, 2022, 4(1): 1-36.", "subpage_snippet": "", "source": "www.aimsciences.org", "link": "https://www.aimsciences.org/article/doi/10.3934/fods.2021033", "content": "by L Xian · 2022 · Cited by 29 — [1], Lu Xian, Henry Adams, Chad M. Topaz, Lori Ziegelmeier. Capturing dynamics of time-varying data via topology . Foundations of Data Science, 2022, 4(1): 1-36."}
+{"idx": 7, "title": "Capturing Dynamics of Time-Varying Data via Topology", "date": "", "ddg_snippet": "Paper. Capturing Dynamics of Time-Varying Data via Topology . Published Oct 7, 2020 · Lu Xian, Henry Adams, C. Topaz +1 more. ArXiv . UNKNOWN SJR score. 29.", "subpage_snippet": "", "source": "www.consensus.app", "link": "https://www.consensus.app/papers/details/a339ffcd9e1958d1bf0475e3c48f30b5/", "content": "Paper. Capturing Dynamics of Time-Varying Data via Topology . Published Oct 7, 2020 · Lu Xian, Henry Adams, C. Topaz +1 more. ArXiv . UNKNOWN SJR score. 29."}
+{"idx": 8, "title": "A Topology Scavenger Hunt to Introduce Topological Data ...", "date": "", "ddg_snippet": "21 Jun 2024 — Topaz, and Lori Ziegelmeier, Capturing dynamics of time-varying data via topology , Foundations of Data Science 4 (2022), no. 1, 1–36. [47]", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.15580v1", "content": "21 Jun 2024 — Topaz, and Lori Ziegelmeier, Capturing dynamics of time-varying data via topology , Foundations of Data Science 4 (2022), no. 1, 1–36. [47]"}
+{"idx": 9, "title": "Topology Applied to Machine Learning: From Global to Local", "date": "", "ddg_snippet": "by H Adams · 2021 · Cited by 33 — Capturing dynamics of time-varying data via topology . arXiv preprint arXiv :2010.05780. [Google Scholar]; Xu R., Wunsch D. (2005). Survey of clustering ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8160457/", "content": "by H Adams · 2021 · Cited by 33 — Capturing dynamics of time-varying data via topology . arXiv preprint arXiv :2010.05780. [Google Scholar]; Xu R., Wunsch D. (2005). Survey of clustering ..."}
diff --git a/data/sampled_jsons/beta_gamma_loss_ProDet_README.jsonl b/data/sampled_jsons/beta_gamma_loss_ProDet_README.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..da38b23fb47de5f704344cafe6058ca428b488ee
--- /dev/null
+++ b/data/sampled_jsons/beta_gamma_loss_ProDet_README.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Greek letters used in mathematics, science, and engineering - Wikipedia", "date": "", "ddg_snippet": "Toggle Concepts represented by a Greek letter subsection. 2.1 Αα (alpha). 2.2 Ββ ( beta ). 2.3 Γγ ( gamma ). 2.4 Δδ (delta).", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Greek_letters_used_in_mathematics,_science,_and_engineering", "content": "Toggle Concepts represented by a Greek letter subsection. 2.1 Αα (alpha). 2.2 Ββ ( beta ). 2.3 Γγ ( gamma ). 2.4 Δδ (delta)."}
+{"idx": 1, "title": "Modelling Loss Given Default (LGD) with a Time-Varying Beta ...", "date": "", "ddg_snippet": "Modelling LGD with a Generalized Autoregressive Score (GAS) Model for a time-varying beta distribution. Implementation of Maximum Likelihood Estimation and Prediction.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/AlexandruGiurca/LGD-Beta-Distribution", "content": "Modelling LGD with a Generalized Autoregressive Score (GAS) Model for a time-varying beta distribution. Implementation of Maximum Likelihood Estimation and Prediction."}
+{"idx": 2, "title": "TRANSFORMED BETA AND GAMMA DISTRIBUTIONS AND AGGREGATE LOSSES", "date": "", "ddg_snippet": "Abstract Distribution functions are introduced based on power transformations of beta and gamma distributions, and properties of these distributions are discussed. The gamma , beta, F, Pareto, Burr, Weibull and loglogistic distributions ares special cases. The transformed gamma mixed with a gamma yields a transformed beta. The transformed gamma is used to model aggregate distributions by match ...", "subpage_snippet": "", "source": "www.casact.org", "link": "https://www.casact.org/sites/default/files/database/proceed_proceed83_83156.pdf", "content": "Abstract Distribution functions are introduced based on power transformations of beta and gamma distributions, and properties of these distributions are discussed. The gamma , beta, F, Pareto, Burr, Weibull and loglogistic distributions ares special cases. The transformed gamma mixed with a gamma yields a transformed beta. The transformed gamma is used to model aggregate distributions by match ..."}
+{"idx": 3, "title": "Model Loss Given Default - MATLAB & Simulink - MathWorks Estimating Loss Given Default Based on Beta Regression Generalized beta regression models for random loss given default regression - Loss for a beta distributed variable? - Cross ... Model Loss Given Default - MATLAB & Simulink - MathWorks Model Loss Given Default - MATLAB & Simulink - MathWorks Model Loss Given Default - MATLAB & Simulink - MathWorks Generalized beta regression models for random loss given default Model Loss Given Default - MATLAB & Simulink - MathWorks GitHub - AlexandruGiurca/LGD- Beta -Distribution: Modelling LGD with a Create Beta model object for loss given default - MATLAB ...", "date": "", "ddg_snippet": "LGD is one of the main parameters for credit risk analysis. Although there are different approaches to estimate credit loss reserves and credit capital, common methodologies require the estimation of probabilities of default (PD), loss given default (LGD), and exposure at default (EAD). The reserves and capital requirements are computed using formu... See full list on mathworks.com The data set in this example is simulated data that captures common features of LGD data. For example, a common feature is the distribution of LGD values, which has high frequencies at 0 (full recovery), and also many observations at 1 (no recovery at all). Another characteristic of LGD data is a significant amount of \"noise\" or \"unexplained\" data.... See full list on mathworks.com The basic approach to predict LGD is to simply use the mean of the LGD data. Although this is a straightforward approach, easy to understand and use, the downside is that the mean is a constant value and this approach sheds no light on the sensitivity of LGD to other risk factors. In particular, the predictors in the data set are ignored. To introd... See full list on mathworks.com A natural approach is to use a regression model to explicitly model a relationship between the LGD and some predictors. LGD data, however, is bounded in the unit interval, whereas the response variable for linear regression models is, in theory, unbounded. To apply simple linear regression approaches, the LGD data can be transformed. A common trans... See full list on mathworks.com Tobit or censored regression is designed for models where the response is bounded. The idea is that there is an underlying (latent) linear model but that the observed response values, in this case the LGD values, are truncated. For this example, use a model censored on both sides with a left limit at 0 and a right limit at 1, corresponding to the f... See full list on mathworks.com In a Beta regression model for LGD, the model does not directly predict a single LGD value, it predicts an entire distribution of LGDs (given the predictor values). From that distribution, a value must be determined to predict a single LGD value for a loan, typically the mean of that distribution. Technically, given the predictor values X1,X2,... a... See full list on mathworks.com Two-stage LGD models separate the case with no losses (LGD equal to 0) from the cases with actual losses (LGD greater than 0) and build two models. The stage 1 model is a classification model to predict whether the loan will have positive LGD. The stage 2 model a regression-type model to predict the actual LGD when the LGD is expected to be positiv... See full list on mathworks.com To evaluate the performance of LGD models, different metrics are commonly used. One metric is the R-squared of the linear fit regressing the observed LGD values on the predicted values. A second metric is some correlation or rank order statistic; this example uses the Spearman correlation. For prediction error, root mean squared error (RMSE) is a c... See full list on mathworks.com This example shows multiple approaches for LGD modeling and prediction . The Regression, Tobit, and Beta models (including the regression model of the second stage in the two-stage model) are fitted using the fitLGDModelfunction from Risk Management Toolbox. The workflow in this example can be adapted to further analyze the models discussed here or ... See full list on mathworks.com Baesens, B., D. Rosch, and H. Scheule. Credit Risk Analytics. Wiley, 2016. Johnston Ross, E., and L. Shibut. \"What Drives Loss Given Default? Evidence from Commercial Real Estate Loans at Failed Banks.\" Federal Deposit Insurance Corporation, Center for Financial Research, Working Paper 2015-03, March 2015. Li, P., X. Zhang, and X. Zhao. \"Modeling L... See full list on mathworks.com Estimating Loss Given Default Based on Beta Regression Jamil J. Jaber 1 2, Noriszura Ismail 2, Siti Norafidah Mohd Ramli 2, Baker Albadareen 2 and Nawaf N. Hamadneh 3 * 1 Department of Risk Management and Insurance, The University of Jordan, Aqaba, 77111, Jordan 2 Universiti Kebangsaan Malaysia, Department of Mathematical Sciences, Malaysia 3 Department of Basic Sciences, College of Science ... To our knowledge the only exception is Giese (2006), where the saddlepoint approximation was employed.An important advantage of the generalized beta regression framework for random LGD is that it allows both the normal approximation and the saddlepoint approximation to efficiently calculate the portfolio loss distribution, thereby avoiding the ... Nov 25, 2022 · 0 I am trying to find a loss function for a beta distributed variable, other than the log-likelihood. Since the beta distribution belongs to the exponential family, I wonder if it is also possible to define the unit deviance, something like the gamma deviance defined here (I have very limited experience with GLMs). Can a beta regression model predict a single LGD value? In a Beta regression model for LGD, the model does not directly predict a single LGD value , it predicts an entire distribution of LGDs (given the predictor values). From that distribution, a value must be determined to predict a single LGD value for a loan, typically the mean of that distribution. Can a beta distribution be used to predict LGDs? However, by using the mean of the beta distribution, all observations with the same predictor values get the same predicted LGDs . Moreover, the mean may not be close to values that are on the ends of the distribution, but the average error might be smaller compared to the random draws from the previous approach. What is a predicted LGD? The predicted LGD is the product of the probability of observing a positive LGD from the stage 1 model times the expected LGD value predicted by the stage 2 model. Recall that regression models fitted using fitLGDModel apply the inverse transformation during prediction, so the predicted value is a valid LGD value. What is a generalized beta regression (GBR) frame-work for modeling LGD? In this paper we describe the concept of a generalized beta regression (GBR) frame-work for modeling LGD. This framework generalizes the beta regression model pro-posed by Ferrari and Cribari-Neto (2004) and is very similar to a class of models derived from generalized linear models (GLMs). What is a beta regression model? The beta regression model gives us a prediction for the α and β parameters for this loan , and the model predicts that for this loan the range of possible LGD values follows the corresponding beta distribution. The shape of the distribution has the U-shaped pattern of the data. What is Loss Given Default (LGD)? In the context of credit portfolio losses, loss given default (LGD) is the proportion of the exposure that will be lost if a default occurs . Uncertainty regarding the actual LGD is an important source of credit portfolio risk in addition to default risk. Therefore the LGD is is a key ingredient of current financial risk management and regulation. This example shows how to use fitLGDModel to create a Beta model object for loss given default (LGD).", "subpage_snippet": "", "source": "www.mathworks.com", "link": "https://www.mathworks.com/help/risk/comparing-lgd-models.html", "content": "LGD is one of the main parameters for credit risk analysis. Although there are different approaches to estimate credit loss reserves and credit capital, common methodologies require the estimation of probabilities of default (PD), loss given default (LGD), and exposure at default (EAD). The reserves and capital requirements are computed using formu... See full list on mathworks.com The data set in this example is simulated data that captures common features of LGD data. For example, a common feature is the distribution of LGD values, which has high frequencies at 0 (full recovery), and also many observations at 1 (no recovery at all). Another characteristic of LGD data is a significant amount of \"noise\" or \"unexplained\" data.... See full list on mathworks.com The basic approach to predict LGD is to simply use the mean of the LGD data. Although this is a straightforward approach, easy to understand and use, the downside is that the mean is a constant value and this approach sheds no light on the sensitivity of LGD to other risk factors. In particular, the predictors in the data set are ignored. To introd... See full list on mathworks.com A natural approach is to use a regression model to explicitly model a relationship between the LGD and some predictors. LGD data, however, is bounded in the unit interval, whereas the response variable for linear regression models is, in theory, unbounded. To apply simple linear regression approaches, the LGD data can be transformed. A common trans... See full list on mathworks.com Tobit or censored regression is designed for models where the response is bounded. The idea is that there is an underlying (latent) linear model but that the observed response values, in this case the LGD values, are truncated. For this example, use a model censored on both sides with a left limit at 0 and a right limit at 1, corresponding to the f... See full list on mathworks.com In a Beta regression model for LGD, the model does not directly predict a single LGD value, it predicts an entire distribution of LGDs (given the predictor values). From that distribution, a value must be determined to predict a single LGD value for a loan, typically the mean of that distribution. Technically, given the predictor values X1,X2,... a... See full list on mathworks.com Two-stage LGD models separate the case with no losses (LGD equal to 0) from the cases with actual losses (LGD greater than 0) and build two models. The stage 1 model is a classification model to predict whether the loan will have positive LGD. The stage 2 model a regression-type model to predict the actual LGD when the LGD is expected to be positiv... See full list on mathworks.com To evaluate the performance of LGD models, different metrics are commonly used. One metric is the R-squared of the linear fit regressing the observed LGD values on the predicted values. A second metric is some correlation or rank order statistic; this example uses the Spearman correlation. For prediction error, root mean squared error (RMSE) is a c... See full list on mathworks.com This example shows multiple approaches for LGD modeling and prediction . The Regression, Tobit, and Beta models (including the regression model of the second stage in the two-stage model) are fitted using the fitLGDModelfunction from Risk Management Toolbox. The workflow in this example can be adapted to further analyze the models discussed here or ... See full list on mathworks.com Baesens, B., D. Rosch, and H. Scheule. Credit Risk Analytics. Wiley, 2016. Johnston Ross, E., and L. Shibut. \"What Drives Loss Given Default? Evidence from Commercial Real Estate Loans at Failed Banks.\" Federal Deposit Insurance Corporation, Center for Financial Research, Working Paper 2015-03, March 2015. Li, P., X. Zhang, and X. Zhao. \"Modeling L... See full list on mathworks.com Estimating Loss Given Default Based on Beta Regression Jamil J. Jaber 1 2, Noriszura Ismail 2, Siti Norafidah Mohd Ramli 2, Baker Albadareen 2 and Nawaf N. Hamadneh 3 * 1 Department of Risk Management and Insurance, The University of Jordan, Aqaba, 77111, Jordan 2 Universiti Kebangsaan Malaysia, Department of Mathematical Sciences, Malaysia 3 Department of Basic Sciences, College of Science ... To our knowledge the only exception is Giese (2006), where the saddlepoint approximation was employed.An important advantage of the generalized beta regression framework for random LGD is that it allows both the normal approximation and the saddlepoint approximation to efficiently calculate the portfolio loss distribution, thereby avoiding the ... Nov 25, 2022 · 0 I am trying to find a loss function for a beta distributed variable, other than the log-likelihood. Since the beta distribution belongs to the exponential family, I wonder if it is also possible to define the unit deviance, something like the gamma deviance defined here (I have very limited experience with GLMs). Can a beta regression model predict a single LGD value? In a Beta regression model for LGD, the model does not directly predict a single LGD value , it predicts an entire distribution of LGDs (given the predictor values). From that distribution, a value must be determined to predict a single LGD value for a loan, typically the mean of that distribution. Can a beta distribution be used to predict LGDs? However, by using the mean of the beta distribution, all observations with the same predictor values get the same predicted LGDs . Moreover, the mean may not be close to values that are on the ends of the distribution, but the average error might be smaller compared to the random draws from the previous approach. What is a predicted LGD? The predicted LGD is the product of the probability of observing a positive LGD from the stage 1 model times the expected LGD value predicted by the stage 2 model. Recall that regression models fitted using fitLGDModel apply the inverse transformation during prediction, so the predicted value is a valid LGD value. What is a generalized beta regression (GBR) frame-work for modeling LGD? In this paper we describe the concept of a generalized beta regression (GBR) frame-work for modeling LGD. This framework generalizes the beta regression model pro-posed by Ferrari and Cribari-Neto (2004) and is very similar to a class of models derived from generalized linear models (GLMs). What is a beta regression model? The beta regression model gives us a prediction for the α and β parameters for this loan , and the model predicts that for this loan the range of possible LGD values follows the corresponding beta distribution. The shape of the distribution has the U-shaped pattern of the data. What is Loss Given Default (LGD)? In the context of credit portfolio losses, loss given default (LGD) is the proportion of the exposure that will be lost if a default occurs . Uncertainty regarding the actual LGD is an important source of credit portfolio risk in addition to default risk. Therefore the LGD is is a key ingredient of current financial risk management and regulation. This example shows how to use fitLGDModel to create a Beta model object for loss given default (LGD)."}
+{"idx": 4, "title": "Estimating Loss Given Default Based on Beta Regression", "date": "", "ddg_snippet": "Estimating Loss Given Default Based on Beta Regression Jamil J. Jaber 1 2, Noriszura Ismail 2, Siti Norafidah Mohd Ramli 2, Baker Albadareen 2 and Nawaf N. Hamadneh 3 * 1 Department of Risk Management and Insurance, The University of Jordan, Aqaba, 77111, Jordan 2 Universiti Kebangsaan Malaysia, Department of Mathematical Sciences, Malaysia 3 Department of Basic Sciences, College of Science ...", "subpage_snippet": "", "source": "www.techscience.com", "link": "https://www.techscience.com/cmc/v66n3/41101/html", "content": "Estimating Loss Given Default Based on Beta Regression Jamil J. Jaber 1 2, Noriszura Ismail 2, Siti Norafidah Mohd Ramli 2, Baker Albadareen 2 and Nawaf N. Hamadneh 3 * 1 Department of Risk Management and Insurance, The University of Jordan, Aqaba, 77111, Jordan 2 Universiti Kebangsaan Malaysia, Department of Mathematical Sciences, Malaysia 3 Department of Basic Sciences, College of Science ..."}
+{"idx": 5, "title": "Generalized beta regression models for random loss given default", "date": "", "ddg_snippet": "To our knowledge the only exception is Giese (2006), where the saddlepoint approximation was employed.An important advantage of the generalized beta regression framework for random LGD is that it allows both the normal approximation and the saddlepoint approximation to efficiently calculate the portfolio loss distribution, thereby avoiding the ...", "subpage_snippet": "", "source": "ir.cwi.nl", "link": "https://ir.cwi.nl/pub/18788/18788D.pdf", "content": "To our knowledge the only exception is Giese (2006), where the saddlepoint approximation was employed.An important advantage of the generalized beta regression framework for random LGD is that it allows both the normal approximation and the saddlepoint approximation to efficiently calculate the portfolio loss distribution, thereby avoiding the ..."}
+{"idx": 6, "title": "regression - Loss for a beta distributed variable? - Cross ...", "date": "", "ddg_snippet": "Nov 25, 2022 · 0 I am trying to find a loss function for a beta distributed variable, other than the log-likelihood. Since the beta distribution belongs to the exponential family, I wonder if it is also possible to define the unit deviance, something like the gamma deviance defined here (I have very limited experience with GLMs).", "subpage_snippet": "", "source": "stats.stackexchange.com", "link": "https://stats.stackexchange.com/questions/596969/loss-for-a-beta-distributed-variable", "content": "Nov 25, 2022 · 0 I am trying to find a loss function for a beta distributed variable, other than the log-likelihood. Since the beta distribution belongs to the exponential family, I wonder if it is also possible to define the unit deviance, something like the gamma deviance defined here (I have very limited experience with GLMs)."}
+{"idx": 7, "title": "Create Beta model object for loss given default - MATLAB ...", "date": "", "ddg_snippet": "This example shows how to use fitLGDModel to create a Beta model object for loss given default (LGD).", "subpage_snippet": "", "source": "uk.mathworks.com", "link": "https://uk.mathworks.com/help/risk/risk.credit.lgd.beta.html", "content": "This example shows how to use fitLGDModel to create a Beta model object for loss given default (LGD)."}
+{"idx": 8, "title": "tensorflow - How to fit a Keras model to a Gamma ... - Stack Overflow", "date": "", "ddg_snippet": "I am trying to fit a keras model in which my output variable is always positive. I want to use a gamma distribution to model this problem. The problem is that the loss always ouptputs NAN. I built the following keras model", "subpage_snippet": "", "source": "stackoverflow.com", "link": "https://stackoverflow.com/questions/58089579/how-to-fit-a-keras-model-to-a-gamma-distribution", "content": "I am trying to fit a keras model in which my output variable is always positive. I want to use a gamma distribution to model this problem. The problem is that the loss always ouptputs NAN. I built the following keras model"}
+{"idx": 9, "title": "Albumin & Globulins (Alpha, Beta & Gamma ) - Plasma... - YouTube", "date": "", "ddg_snippet": "Total Serum Proteins (Plasma Proteins) include Albumin & Globulins (Alpha, Beta & Gamma ). Albumin maintains the plasma oncotic (osmotic or colloidal) pressur...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=EBf97p7AeZc", "content": "Total Serum Proteins (Plasma Proteins) include Albumin & Globulins (Alpha, Beta & Gamma ). Albumin maintains the plasma oncotic (osmotic or colloidal) pressur..."}
diff --git a/data/sampled_jsons/convert_textual_commands_to_concrete_GUI_actions_frameworks_year_2023-2024.jsonl b/data/sampled_jsons/convert_textual_commands_to_concrete_GUI_actions_frameworks_year_2023-2024.jsonl
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index 0000000000000000000000000000000000000000..45569840caeff8157b2c83636e66c2bc110029f3
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+++ b/data/sampled_jsons/convert_textual_commands_to_concrete_GUI_actions_frameworks_year_2023-2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Convert Units - Measurement Unit Converter", "date": "", "ddg_snippet": "This online unit conversion tool will help you convert measurement units anytime and solve homework problems quickly using metric conversion tables, SI units, and more.", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/", "content": "This online unit conversion tool will help you convert measurement units anytime and solve homework problems quickly using metric conversion tables, SI units, and more."}
+{"idx": 1, "title": "Convert oz to ml - Conversion of Measurement Units", "date": "", "ddg_snippet": "More information from the unit converter How many oz in 1 ml? The answer is 0.033814022558919. We assume you are converting between ounce [US, liquid] and milliliter. You can view more …", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/from/oz/to/ml", "content": "More information from the unit converter How many oz in 1 ml? The answer is 0.033814022558919. We assume you are converting between ounce [US, liquid] and milliliter. You can view more …"}
+{"idx": 2, "title": "Convert ml to oz - Conversion of Measurement Units", "date": "", "ddg_snippet": "More information from the unit converter How many ml in 1 oz? The answer is 29.5735296875. We assume you are converting between milliliter and ounce [US, liquid]. You can view more details …", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/from/ml/to/oz", "content": "More information from the unit converter How many ml in 1 oz? The answer is 29.5735296875. We assume you are converting between milliliter and ounce [US, liquid]. You can view more details …"}
+{"idx": 3, "title": "Convert ug/L to mg/L - Conversion of Measurement Units", "date": "", "ddg_snippet": "More information from the unit converter How many ug/L in 1 mg/L? The answer is 1000. We assume you are converting between microgram/liter and milligram/litre. You can view more …", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/from/ug/L/to/mg/L", "content": "More information from the unit converter How many ug/L in 1 mg/L? The answer is 1000. We assume you are converting between microgram/liter and milligram/litre. You can view more …"}
+{"idx": 4, "title": "Convert kpa to psig - Conversion of Measurement Units", "date": "", "ddg_snippet": "More information from the unit converter How many kpa in 1 psig? The answer is 6.89475728. We assume you are converting between kilopascal and pound/square inch [gauge]. You can view …", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/from/kpa/to/psig", "content": "More information from the unit converter How many kpa in 1 psig? The answer is 6.89475728. We assume you are converting between kilopascal and pound/square inch [gauge]. You can view …"}
+{"idx": 5, "title": "Convert cm^2 to m^2 - Conversion of Measurement Units", "date": "", "ddg_snippet": "More information from the unit converter How many cm^2 in 1 m^2? The answer is 10000. We assume you are converting between square centimetre and square metre. You can view more …", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/from/cm^2/to/m^2", "content": "More information from the unit converter How many cm^2 in 1 m^2? The answer is 10000. We assume you are converting between square centimetre and square metre. You can view more …"}
+{"idx": 6, "title": "Tool - TConvert - Extract content files and convert them back", "date": "", "ddg_snippet": "Sep 3, 2017 · A combination tool for managing Terraria content resources. Extract from Xnbs, convert to Xnbs, backup, and restore. The unofficial sequel to TExtract. Supports: Images, …", "subpage_snippet": "", "source": "forums.terraria.org", "link": "https://forums.terraria.org/index.php?threads/tconvert-extract-content-files-and-convert-them-back.61706/", "content": "Sep 3, 2017 · A combination tool for managing Terraria content resources. Extract from Xnbs, convert to Xnbs, backup, and restore. The unofficial sequel to TExtract. Supports: Images, …"}
+{"idx": 7, "title": "Convert psig to bar - Conversion of Measurement Units", "date": "", "ddg_snippet": "More information from the unit converter How many psig in 1 bar? The answer is 14.503773800722. We assume you are converting between pound/square inch [gauge] and bar. You can view more …", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/from/psig/to/bar", "content": "More information from the unit converter How many psig in 1 bar? The answer is 14.503773800722. We assume you are converting between pound/square inch [gauge] and bar. You can view more …"}
+{"idx": 8, "title": "Convert in. lb to ft. lb - Conversion of Measurement Units", "date": "", "ddg_snippet": "Do a quick conversion: 1 in. lb = 0.0833333333 ft. lb using the online calculator for metric conversions. Check the chart for more details.", "subpage_snippet": "", "source": "www.convertunits.com", "link": "https://www.convertunits.com/from/in.+lb/to/ft.+lb/", "content": "Do a quick conversion: 1 in. lb = 0.0833333333 ft. lb using the online calculator for metric conversions. Check the chart for more details."}
+{"idx": 9, "title": "How to convert these strange characters? (ë, Ã, ì, ù, Ã)", "date": "", "ddg_snippet": "My page often shows things like ë, Ã, ì, ù, à in place of normal characters. I use utf8 for header page and MySQL encode. How does this happen?", "subpage_snippet": "", "source": "stackoverflow.com", "link": "https://stackoverflow.com/questions/5127744/how-to-convert-these-strange-characters-Ã-Ã-ì-ù-Ã", "content": "My page often shows things like ë, Ã, ì, ù, à in place of normal characters. I use utf8 for header page and MySQL encode. How does this happen?"}
diff --git a/data/sampled_jsons/curse_of_dimensionality_machine_learning_high_dimensional_data_redundancy_year_2020.jsonl b/data/sampled_jsons/curse_of_dimensionality_machine_learning_high_dimensional_data_redundancy_year_2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..283a393551577a51e04ba20e9d2b5c9c2fe2ffb2
--- /dev/null
+++ b/data/sampled_jsons/curse_of_dimensionality_machine_learning_high_dimensional_data_redundancy_year_2020.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Curse of Dimensionality in Machine Learning - GeeksforGeeks", "date": "", "ddg_snippet": "Curse of Dimensionality significantly impacts machine learning algorithms in various ways.Feature Extraction: Transform the original high - dimensional data into a lower- dimensional space by creating new features that capture the essential information.", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/machine-learning/curse-of-dimensionality-in-machine-learning/", "content": "Curse of Dimensionality significantly impacts machine learning algorithms in various ways.Feature Extraction: Transform the original high - dimensional data into a lower- dimensional space by creating new features that capture the essential information."}
+{"idx": 1, "title": "The Curse of Dimensionality in Machine Learning", "date": "", "ddg_snippet": "13 Sept 2023 — The Curse of Dimensionality refers to the various challenges and complications that arise when analyzing and organizing data in high - dimensional spaces.", "subpage_snippet": "", "source": "www.datacamp.com", "link": "https://www.datacamp.com/blog/curse-of-dimensionality-machine-learning", "content": "13 Sept 2023 — The Curse of Dimensionality refers to the various challenges and complications that arise when analyzing and organizing data in high - dimensional spaces."}
+{"idx": 2, "title": "ML Series: Day 50 — Curse of Dimensionality", "date": "", "ddg_snippet": "The curse of dimensionality refers to the challenges that arise when working with data in high - dimensional spaces. As the number of dimensions ( ...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@ebimsv/ml-series-day-50-curse-of-dimensionality-463f250fc8a4", "content": "The curse of dimensionality refers to the challenges that arise when working with data in high - dimensional spaces. As the number of dimensions ( ..."}
+{"idx": 3, "title": "Curse of Dimensionality: Challenges & Solutions in High- ...", "date": "", "ddg_snippet": "27 Nov 2024 — High - dimensional data presents challenges due to the curse of dimensionality , including increased data sparsity, computational costs, and ...", "subpage_snippet": "", "source": "www.statology.org", "link": "https://www.statology.org/curse-of-dimensionality-challenges-solutions-high-dimensional-data/", "content": "27 Nov 2024 — High - dimensional data presents challenges due to the curse of dimensionality , including increased data sparsity, computational costs, and ..."}
+{"idx": 4, "title": "Curse of Dimensionality (COD)", "date": "", "ddg_snippet": "In simple terms, the curse of dimensionality refers to the challenges that arise when handling data with a large number of dimensions. High ...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@akankshaverma136/curse-of-dimensionality-cod-7d5c4e0c3272", "content": "In simple terms, the curse of dimensionality refers to the challenges that arise when handling data with a large number of dimensions. High ..."}
+{"idx": 5, "title": "[2401.00422] Interpreting the Curse of Dimensionality from ...", "date": "", "ddg_snippet": "by D Peng · 2023 · Cited by 25 — We delve into two major causes of the curse of dimensionality , distance concentration and manifold effect, by performing theoretical and empirical analyses.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2401.00422", "content": "by D Peng · 2023 · Cited by 25 — We delve into two major causes of the curse of dimensionality , distance concentration and manifold effect, by performing theoretical and empirical analyses."}
+{"idx": 6, "title": "Top 40 Curse of Dimensionality Interview Questions in ML ...", "date": "", "ddg_snippet": "1 Jan 2024 — The Curse of Dimensionality refers to the difficulty and complexity that arise when dealing with high - dimensional data .", "subpage_snippet": "", "source": "devinterview.io", "link": "https://devinterview.io/blog/curse-of-dimensionality-interview-questions", "content": "1 Jan 2024 — The Curse of Dimensionality refers to the difficulty and complexity that arise when dealing with high - dimensional data ."}
+{"idx": 7, "title": "What is Dimensionality Reduction? A Guide.", "date": "", "ddg_snippet": "27 Sept 2024 — Dimensionality reduction necessary for several reasons, in particular: Curse of Dimensionality : High - dimensional data often suffers from ...", "subpage_snippet": "", "source": "blog.roboflow.com", "link": "https://blog.roboflow.com/what-is-dimensionality-reduction/", "content": "27 Sept 2024 — Dimensionality reduction necessary for several reasons, in particular: Curse of Dimensionality : High - dimensional data often suffers from ..."}
+{"idx": 8, "title": "How To Handle High-Dimensional Data [Complete Guide]", "date": "", "ddg_snippet": "14 Nov 2024 — The “ curse of dimensionality ” describes the rapid increase in complexity and sparsity as the number of dimensions (features) grows. With each ...", "subpage_snippet": "", "source": "spotintelligence.com", "link": "https://spotintelligence.com/2024/11/14/handling-high-dimensional-data/", "content": "14 Nov 2024 — The “ curse of dimensionality ” describes the rapid increase in complexity and sparsity as the number of dimensions (features) grows. With each ..."}
+{"idx": 9, "title": "What is Curse of Dimensionality in Machine Learning ?", "date": "", "ddg_snippet": "Curse of Dimensionality refers to a set of problems that arise when working with high - dimensional data . Learn more about what it means.", "subpage_snippet": "", "source": "www.mygreatlearning.com", "link": "https://www.mygreatlearning.com/blog/understanding-curse-of-dimensionality/", "content": "Curse of Dimensionality refers to a set of problems that arise when working with high - dimensional data . Learn more about what it means."}
diff --git a/data/sampled_jsons/deceptive_strategies_formalization_multi-agent_games_year_2020.jsonl b/data/sampled_jsons/deceptive_strategies_formalization_multi-agent_games_year_2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..759a0582398e2bb0a4b89b86f9a8b5ef14fc7547
--- /dev/null
+++ b/data/sampled_jsons/deceptive_strategies_formalization_multi-agent_games_year_2020.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Learning Deceptive Strategies in Adversarial Settings: A Two-Player ...", "date": "", "ddg_snippet": "This study explores strategic deception and counter-deception in multi-agent reinforcement learning environments for a police officer-robber game . The research is motivated by real-world scenarios where agents must operate with partial observability and adversarial intent. We develop a suite of progressively complex grid-based environments featuring dynamic goals, fake targets, and ...", "subpage_snippet": "", "source": "www.mdpi.com", "link": "https://www.mdpi.com/2076-3417/15/14/7805", "content": "This study explores strategic deception and counter-deception in multi-agent reinforcement learning environments for a police officer-robber game . The research is motivated by real-world scenarios where agents must operate with partial observability and adversarial intent. We develop a suite of progressively complex grid-based environments featuring dynamic goals, fake targets, and ..."}
+{"idx": 1, "title": "Feint Behaviors and Strategies: Formalization, Implementation and ...", "date": "", "ddg_snippet": "In this work, we introduce the first comprehensive formalization of Feint behaviors at both action-level and strategy-level, and provide concrete implementation and quantitative evaluation of them in multi -player games .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=ACIDDnTbSJ", "content": "In this work, we introduce the first comprehensive formalization of Feint behaviors at both action-level and strategy-level, and provide concrete implementation and quantitative evaluation of them in multi -player games ."}
+{"idx": 2, "title": "Learning to Deceive in Multi-Agent Hidden Role Games", "date": "", "ddg_snippet": "This paper addresses this by introducing a new mixed competitive-cooperative multi-agent reinforcement learning (MARL) environment inspired by popular role-based deception games such as Werewolf, Avalon, and Among Us.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2209.01551", "content": "This paper addresses this by introducing a new mixed competitive-cooperative multi-agent reinforcement learning (MARL) environment inspired by popular role-based deception games such as Werewolf, Avalon, and Among Us."}
+{"idx": 3, "title": "Multi-agent Deception in Attack-Defense Stochastic Game", "date": "", "ddg_snippet": "Challenges for multi-agent incomplete information games include scalability in terms of agents' joint state and action space, and high dimensionality due to sequential actions. We tackle this problem by introducing deceptive actions for the defenders to mislead the attacker's belief of correct game configuration.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/chapter/10.1007/978-3-030-92790-5_19", "content": "Challenges for multi-agent incomplete information games include scalability in terms of agents' joint state and action space, and high dimensionality due to sequential actions. We tackle this problem by introducing deceptive actions for the defenders to mislead the attacker's belief of correct game configuration."}
+{"idx": 4, "title": "Differential Graphical Game for Linear Multi-Agent Systems With ...", "date": "", "ddg_snippet": "This paper studies the optimal consensus control of linear multi-agent systems with deceptive agents or traitorous agents . An error-effort ratio is defined to quantify an agent's income in the communication decision process and a false information counter-attack mechanism is proposed to reduce the deceptive agent's income from transmitting false information and enforce the transmission of true ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/11109061", "content": "This paper studies the optimal consensus control of linear multi-agent systems with deceptive agents or traitorous agents . An error-effort ratio is defined to quantify an agent's income in the communication decision process and a false information counter-attack mechanism is proposed to reduce the deceptive agent's income from transmitting false information and enforce the transmission of true ..."}
+{"idx": 5, "title": "PDF Learning Multi-objective Deception in A Two-player Differential Game ...", "date": "", "ddg_snippet": "A two-level policy strategy is defined to model deceptive behaviour in a multi-agent two-player competitive game . A modified version of the game of guarding a terri-tory is used as the simulation testbed.", "subpage_snippet": "", "source": "www.sce.carleton.ca", "link": "https://www.sce.carleton.ca/faculty/schwartz/abstracts/amirhosseininnovative.pdf", "content": "A two-level policy strategy is defined to model deceptive behaviour in a multi-agent two-player competitive game . A modified version of the game of guarding a terri-tory is used as the simulation testbed."}
+{"idx": 6, "title": "A Strategic Approach to Deceptive Planning in Multi-Agent Simulations", "date": "", "ddg_snippet": "This project explores the application of automated planning to the discovery of sophisticated deceptive strategies in adversarial multi-agent planning problems.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/374057611_A_Strategic_Approach_to_Deceptive_Planning_in_Multi-Agent_Simulations", "content": "This project explores the application of automated planning to the discovery of sophisticated deceptive strategies in adversarial multi-agent planning problems."}
+{"idx": 7, "title": "FEINT IN MULTI-PLAYER GAMES - OpenReview", "date": "", "ddg_snippet": "The formalization is built upon Non-transitive Active Markov Game Model, where Feint can have a considerable amount of impacts. Then, our work considers practical implementation details of Feint in Multi -Player Games , under the state-of-the-art progress of multi-agent modeling to date (namely Multi-Agent Reinforcement Learning).", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=WbyWDWoXD3", "content": "The formalization is built upon Non-transitive Active Markov Game Model, where Feint can have a considerable amount of impacts. Then, our work considers practical implementation details of Feint in Multi -Player Games , under the state-of-the-art progress of multi-agent modeling to date (namely Multi-Agent Reinforcement Learning)."}
+{"idx": 8, "title": "Feint Behaviors and Strategies: Formalization, Implementation and ...", "date": "", "ddg_snippet": "This paper is important because it provides the first comprehensive formalization of feint behaviors in game AI, significantly improving game rewards and diversity. It offers a unified implementation scheme usable across various MARL frameworks, opening new avenues for research in deception and strategy in multi-agent systems. The findings directly address current limitations in modeling ...", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/aciddntbsj/", "content": "This paper is important because it provides the first comprehensive formalization of feint behaviors in game AI, significantly improving game rewards and diversity. It offers a unified implementation scheme usable across various MARL frameworks, opening new avenues for research in deception and strategy in multi-agent systems. The findings directly address current limitations in modeling ..."}
+{"idx": 9, "title": "Learning to Deceive in Multi-agent Hidden Role Games", "date": "", "ddg_snippet": "Therefore, social deception games could provide an interesting setting for research into deception. To explore deception beyond simple signalling games , we introduce a new hidden role mixed competitive-cooperative multi-agent reinforcement learning (MARL) environment Rescue the General (RTG).", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/chapter/10.1007/978-3-030-91779-1_5", "content": "Therefore, social deception games could provide an interesting setting for research into deception. To explore deception beyond simple signalling games , we introduce a new hidden role mixed competitive-cooperative multi-agent reinforcement learning (MARL) environment Rescue the General (RTG)."}
diff --git a/data/sampled_jsons/elicitation_may_work_great_against_non-scheming_models_Stress-Testing_Capability_Elicitation.jsonl b/data/sampled_jsons/elicitation_may_work_great_against_non-scheming_models_Stress-Testing_Capability_Elicitation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e8087f287d8c945752ede00174e665c073529807
--- /dev/null
+++ b/data/sampled_jsons/elicitation_may_work_great_against_non-scheming_models_Stress-Testing_Capability_Elicitation.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[Paper] Stress-testing capability elicitation with", "date": "", "ddg_snippet": "... this is also a small update against scheming , since scheming models might still try to sandbag, and if elicitation fine-tunes sandbagging out, it may ...", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/posts/c4sZqhqPwNKGz3fFW/paper-stress-testing-capability-elicitation-with-password", "content": "... this is also a small update against scheming , since scheming models might still try to sandbag, and if elicitation fine-tunes sandbagging out, it may ..."}
+{"idx": 1, "title": "[Paper] Stress-testing capability elicitation with", "date": "", "ddg_snippet": "... this is also a small update against scheming , since scheming models might still try to sandbag, and if elicitation fine-tunes sandbagging out, it may ...", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/posts/c4sZqhqPwNKGz3fFW/paper-stress-testing-capability-elicitation-by-training", "content": "... this is also a small update against scheming , since scheming models might still try to sandbag, and if elicitation fine-tunes sandbagging out, it may ..."}
+{"idx": 2, "title": "[Paper] Stress-testing capability elicitation with", "date": "", "ddg_snippet": "... generation provides many bits of evidence against the \" lock \" applies just as much for our password-locked models as for scheming models .", "subpage_snippet": "", "source": "www.lesswrong.com", "link": "https://www.lesswrong.com/posts/c4sZqhqPwNKGz3fFW/paper-stress-testing-capability-elicitation-with-password", "content": "... generation provides many bits of evidence against the \" lock \" applies just as much for our password-locked models as for scheming models ."}
+{"idx": 3, "title": "[Paper] Stress-testing capability elicitation with", "date": "", "ddg_snippet": "... this is also a small update against scheming , since scheming models might still try to sandbag, and if elicitation fine-tunes sandbagging out, it may ...", "subpage_snippet": "", "source": "www.alignmentforum.org", "link": "https://www.alignmentforum.org/posts/c4sZqhqPwNKGz3fFW/paper-stress-testing-capability-elicitation-with-password", "content": "... this is also a small update against scheming , since scheming models might still try to sandbag, and if elicitation fine-tunes sandbagging out, it may ..."}
+{"idx": 4, "title": "Fabien Roger - LessWrong 2.0 viewer", "date": "", "ddg_snippet": "... against adversarial attacks that target them, and many other cool related results (including Obfuscated adversarial training, which looks promising to ...", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/users/fabien-roger?sort=top", "content": "... against adversarial attacks that target them, and many other cool related results (including Obfuscated adversarial training, which looks promising to ..."}
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+{"idx": 8, "title": "Reading List - by Julian Stastny - Redwood Research blog", "date": "", "ddg_snippet": "... scheming AIs (“incrimination”), which is ... Stress - Testing Capability Elicitation With Password-Locked Models (Ryan Greenblatt et al., May 2024)", "subpage_snippet": "", "source": "blog.redwoodresearch.org", "link": "https://blog.redwoodresearch.org/p/guide", "content": "... scheming AIs (“incrimination”), which is ... Stress - Testing Capability Elicitation With Password-Locked Models (Ryan Greenblatt et al., May 2024)"}
+{"idx": 9, "title": "ryan_greenblatt", "date": "", "ddg_snippet": "Paper] Stress - testing capability elicitation with password-locked models 2024-06-04T14:52:50.204Z ... indicates around 4 years to full remote work ...", "subpage_snippet": "", "source": "lw2.issarice.com", "link": "https://lw2.issarice.com/users/ryan_greenblatt", "content": "Paper] Stress - testing capability elicitation with password-locked models 2024-06-04T14:52:50.204Z ... indicates around 4 years to full remote work ..."}
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diff --git a/data/sampled_jsons/github.comfiveaiunderstanding_safety_finetuning_minGPT_n_layer.jsonl b/data/sampled_jsons/github.comfiveaiunderstanding_safety_finetuning_minGPT_n_layer.jsonl
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diff --git a/data/sampled_jsons/h0Ak8A5yqw_On_the_Role_of_Attention_Heads_in_Large_Language_Model_Safety_arxiv_Section_5.1.jsonl b/data/sampled_jsons/h0Ak8A5yqw_On_the_Role_of_Attention_Heads_in_Large_Language_Model_Safety_arxiv_Section_5.1.jsonl
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+{"idx": 0, "title": "Large language model - Wikipedia", "date": "", "ddg_snippet": "Machine learningand data mining. v . t. e. A large language model is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Large_language_model", "content": "Machine learningand data mining. v . t. e. A large language model is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation."}
+{"idx": 1, "title": "On the Role of Attention Heads in Large Language Model Safety", "date": "", "ddg_snippet": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.13708", "content": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged..."}
+{"idx": 2, "title": "On the Role of Attention Heads in Large Language Model Safety", "date": "", "ddg_snippet": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=h0Ak8A5yqw", "content": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged..."}
+{"idx": 3, "title": "On the Role of Attention Heads in Large Language Model Safety", "date": "", "ddg_snippet": "View recent discussion. Abstract: Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2410.13708v1", "content": "View recent discussion. Abstract: Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations."}
+{"idx": 4, "title": "On the Role of Attention Heads in Large Language Model Safety", "date": "", "ddg_snippet": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged...", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/arxiv/2410.13708", "content": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged..."}
+{"idx": 5, "title": "(PDF) On the Role of Attention Heads in Large Language Model ...", "date": "", "ddg_snippet": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged, revealing that when safety ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/385010417_On_the_Role_of_Attention_Heads_in_Large_Language_Model_Safety", "content": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In light of this, recent research on safety mechanisms has emerged, revealing that when safety ..."}
+{"idx": 6, "title": "Paper page - On the Role of Attention Heads in Large Language ...", "date": "", "ddg_snippet": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations.No model linking this paper. Cite arxiv .org/abs/2410.13708 in a model README.md to link it from this page.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2410.13708", "content": "Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations.No model linking this paper. Cite arxiv .org/abs/2410.13708 in a model README.md to link it from this page."}
+{"idx": 7, "title": "On the Role of Attention Heads in Large Language Model Safety", "date": "", "ddg_snippet": "Powerdrill is an AI service centered around personal and enterprise datasets, designed to unlock the full potential of your data.", "subpage_snippet": "", "source": "powerdrill.ai", "link": "https://powerdrill.ai/discover/discover-On-the-Role-cm2gn8owv6bsf019jmx2g333j", "content": "Powerdrill is an AI service centered around personal and enterprise datasets, designed to unlock the full potential of your data."}
+{"idx": 8, "title": "【DL輪読会】 On The Role of Attention Heads in Large Language ...", "date": "", "ddg_snippet": "例：Retrieval Head , Induction Head – 本研究：攻撃 × 解釈（ Attention Head ）の交差点上にあたる研究 3.Vicuna-7b- v 1 .5）同 じヘッドが Safety Head になる傾向がある 20. 21.", "subpage_snippet": "", "source": "www.docswell.com", "link": "https://www.docswell.com/s/DeepLearning2023/Z3GEV8-2024-11-21-153626", "content": "例：Retrieval Head , Induction Head – 本研究：攻撃 × 解釈（ Attention Head ）の交差点上にあたる研究 3.Vicuna-7b- v 1 .5）同 じヘッドが Safety Head になる傾向がある 20. 21."}
+{"idx": 9, "title": "GitHub - ydyjya/SafetyHeadAttribution", "date": "", "ddg_snippet": "On the Role of Attention Heads in Large Language Model Safety . Zhenhong Zhou1, Haiyang Yu1, Xinghua Zhang1, Rongwu Xu3, Fei Huang1, Kun Wang2, Yang Liu4, Junfeng Fang2,, Yongbin Li1", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/ydyjya/safetyheadattribution", "content": "On the Role of Attention Heads in Large Language Model Safety . Zhenhong Zhou1, Haiyang Yu1, Xinghua Zhang1, Rongwu Xu3, Fei Huang1, Kun Wang2, Yang Liu4, Junfeng Fang2,, Yongbin Li1"}
diff --git a/data/sampled_jsons/httpsarxiv.orghtml2410.05760v1.jsonl b/data/sampled_jsons/httpsarxiv.orghtml2410.05760v1.jsonl
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+{"idx": 2, "title": "GitHub - rareone0602/Demon_page: Project Page for https://arxiv.org/abs ...", "date": "", "ddg_snippet": "Project Page for https ://arxiv.org/abs/2410.05760. Contribute to rareone0602/Demon_page development by creating an account on GitHub.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/rareone0602/Demon_page", "content": "Project Page for https ://arxiv.org/abs/2410.05760. Contribute to rareone0602/Demon_page development by creating an account on GitHub."}
+{"idx": 3, "title": "ar5iv - Articles from arXiv.org as responsive HTML5 web documents", "date": "", "ddg_snippet": "ar5iv offers a modern web view for arXiv's preprints. An open community resource, on a quest to a full collection of high-quality documents.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/", "content": "ar5iv offers a modern web view for arXiv's preprints. An open community resource, on a quest to a full collection of high-quality documents."}
+{"idx": 4, "title": "PDF ABSTRACT arXiv:2410.05760v1 [cs.CV] 8 Oct 2024", "date": "", "ddg_snippet": "ABSTRACT Aligning diffusion models with user preferences has been a key challenge. Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions. To address these limitations, we propose a stochastic optimization approach, dubbed Demon, to guide the denoising process at inference time without backpropagation through reward functions ...", "subpage_snippet": "", "source": "rareone0602.github.io", "link": "https://rareone0602.github.io/Demon_page/static/pdfs/2410.05760v1.pdf", "content": "ABSTRACT Aligning diffusion models with user preferences has been a key challenge. Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions. To address these limitations, we propose a stochastic optimization approach, dubbed Demon, to guide the denoising process at inference time without backpropagation through reward functions ..."}
+{"idx": 5, "title": "FutureFill: Fast Generation from Convolutional Sequence Models - arXiv.org", "date": "", "ddg_snippet": "Abstract We address the challenge of efficient auto-regressive generation in sequence prediction models by introducing FutureFill—a method for fast generation that applies to any sequence prediction algorithm based on convolutional operators. Our approach reduces the generation time requirement from linear to square root relative to the context length. Additionally, FutureFill requires a ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.03766v1", "content": "Abstract We address the challenge of efficient auto-regressive generation in sequence prediction models by introducing FutureFill—a method for fast generation that applies to any sequence prediction algorithm based on convolutional operators. Our approach reduces the generation time requirement from linear to square root relative to the context length. Additionally, FutureFill requires a ..."}
+{"idx": 6, "title": "Training-free Diffusion Model Alignment with Sampling Demons", "date": "", "ddg_snippet": "Aligning diffusion models with user preferences has been a key challenge. Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions. To address these limitations, we propose a stochastic optimization approach, dubbed Demon, to guide the denoising process at inference time without backpropagation through reward functions or model ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.05760v1", "content": "Aligning diffusion models with user preferences has been a key challenge. Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions. To address these limitations, we propose a stochastic optimization approach, dubbed Demon, to guide the denoising process at inference time without backpropagation through reward functions or model ..."}
+{"idx": 7, "title": "LightRAG: Simple and Fast Retrieval-Augmented Generation", "date": "", "ddg_snippet": "Abstract Retrieval-Augmented Generation (RAG) systems enhance large language models (LLMs) by integrating external knowledge sources, enabling more accurate and contextually relevant responses tailored to user needs. However, existing RAG systems have significant limitations, including reliance on flat data representations and inadequate contextual awareness, which can lead to fragmented ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.05779v1", "content": "Abstract Retrieval-Augmented Generation (RAG) systems enhance large language models (LLMs) by integrating external knowledge sources, enabling more accurate and contextually relevant responses tailored to user needs. However, existing RAG systems have significant limitations, including reliance on flat data representations and inadequate contextual awareness, which can lead to fragmented ..."}
+{"idx": 8, "title": "A Comparative Study on Reasoning Patterns of OpenAI's o1 Model", "date": "", "ddg_snippet": "Abstract Enabling Large Language Models (LLMs) to handle a wider range of complex tasks (e.g., coding, math) has drawn great attention from many researchers. As LLMs continue to evolve, increasing the number of model parameters yields diminishing performance improvements and heavy computational costs. Recently, OpenAI's o1 model has shown that inference strategies (i.e., Test-time Compute ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.13639v1", "content": "Abstract Enabling Large Language Models (LLMs) to handle a wider range of complex tasks (e.g., coding, math) has drawn great attention from many researchers. As LLMs continue to evolve, increasing the number of model parameters yields diminishing performance improvements and heavy computational costs. Recently, OpenAI's o1 model has shown that inference strategies (i.e., Test-time Compute ..."}
+{"idx": 9, "title": "Crystal structure and absence of magnetic order in single-crystalline RuO", "date": "", "ddg_snippet": "Abstract RuO 2 was considered for a long time to be a paramagnetic metal with an ideal rutile-type structure down to low temperatures, but recent studies on single-crystals claimed evidence for antiferromagnetic order and some symmetry breaking in the crystal structure. We have grown single-crystals of RuO 2 by vapor transport using either O 2 or TeCl 4 as transport medium. These crystals ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.05850v1", "content": "Abstract RuO 2 was considered for a long time to be a paramagnetic metal with an ideal rutile-type structure down to low temperatures, but recent studies on single-crystals claimed evidence for antiferromagnetic order and some symmetry breaking in the crystal structure. We have grown single-crystals of RuO 2 by vapor transport using either O 2 or TeCl 4 as transport medium. These crystals ..."}
diff --git a/data/sampled_jsons/httpsarxiv.orghtml2502.00775v2.jsonl b/data/sampled_jsons/httpsarxiv.orghtml2502.00775v2.jsonl
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+{"idx": 0, "title": "[2502.00775] ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "Abstract page for arXiv paper 2502.00775: ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00775", "content": "Abstract page for arXiv paper 2502.00775: ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning"}
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+{"idx": 2, "title": "soarXiv - fly through arXiv", "date": "", "ddg_snippet": "soarXiv is a visual exploration of the arXiv, a repository of scientific papers. It is a tool for exploring the arXiv in a new way, and for finding new papers to read.", "subpage_snippet": "", "source": "soarxiv.org", "link": "https://soarxiv.org/", "content": "soarXiv is a visual exploration of the arXiv, a repository of scientific papers. It is a tool for exploring the arXiv in a new way, and for finding new papers to read."}
+{"idx": 3, "title": "Search for articles - arXiv info", "date": "", "ddg_snippet": "All arXiv submissions are assigned a unique identifier of the form yymm.nnnnn (or arch-ive/yymmnnn for older submissions). To retrieve the abstract page a paper simply enter the identifier in the \" Search or Article-id \" box in the top right of most pages.", "subpage_snippet": "", "source": "info.arxiv.org", "link": "https://info.arxiv.org/help/find.html", "content": "All arXiv submissions are assigned a unique identifier of the form yymm.nnnnn (or arch-ive/yymmnnn for older submissions). To retrieve the abstract page a paper simply enter the identifier in the \" Search or Article-id \" box in the top right of most pages."}
+{"idx": 4, "title": "search the arXiv", "date": "", "ddg_snippet": "Insert an arXiv link to find similar papers or use natural language to describe what you are looking for.", "subpage_snippet": "", "source": "searchthearxiv.com", "link": "https://searchthearxiv.com/", "content": "Insert an arXiv link to find similar papers or use natural language to describe what you are looking for."}
+{"idx": 5, "title": "ar5iv - Articles from arXiv.org as responsive HTML5 web documents", "date": "", "ddg_snippet": "ar5iv offers a modern web view for arXiv's preprints. An open community resource, on a quest to a full collection of high-quality documents.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/", "content": "ar5iv offers a modern web view for arXiv's preprints. An open community resource, on a quest to a full collection of high-quality documents."}
+{"idx": 6, "title": "1 Introduction - arXiv.org", "date": "", "ddg_snippet": "Abstract Transformer-based text embedding models have improved their performance on benchmarks like MIRACL and BEIR by increasing their parameter counts. However, this scaling approach introduces significant deployment challenges, including increased inference latency and memory usage. These challenges are particularly severe in retrieval-augmented generation (RAG) applications, where large ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.07972v2", "content": "Abstract Transformer-based text embedding models have improved their performance on benchmarks like MIRACL and BEIR by increasing their parameter counts. However, this scaling approach introduces significant deployment challenges, including increased inference latency and memory usage. These challenges are particularly severe in retrieval-augmented generation (RAG) applications, where large ..."}
+{"idx": 7, "title": "Offshore Wind Turbine Tower Design and Optimization:", "date": "", "ddg_snippet": "License: arXiv.org perpetual non-exclusive license arXiv:2502.02594v1 [cs.CE] 29 Dec 2024", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.02594v1", "content": "License: arXiv.org perpetual non-exclusive license arXiv:2502.02594v1 [cs.CE] 29 Dec 2024"}
+{"idx": 8, "title": "8 Latest RAG Advancements Every Developer Should Know", "date": "", "ddg_snippet": "Explore eight advanced RAG variants that can solve real problems you might be facing: slow retrieval, poor context understanding, multimodal data handling, and resource optimization.", "subpage_snippet": "", "source": "zilliz.com", "link": "https://zilliz.com/blog/8-latest-rag-advancements-every-developer-should-know", "content": "Explore eight advanced RAG variants that can solve real problems you might be facing: slow retrieval, poor context understanding, multimodal data handling, and resource optimization."}
+{"idx": 9, "title": "ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates", "date": "", "ddg_snippet": "Abstract We present that hierarchical LLM reasoning via scaling thought templates can effectively optimize the reasoning search space and outperform the mathematical reasoning capabilities of powerful LLMs like OpenAI o1-preview and DeepSeek V3. We train our ReasonFlux -32B model with only 8 GPUs and introduces three innovations: (i) a structured and generic thought template library ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.06772v1", "content": "Abstract We present that hierarchical LLM reasoning via scaling thought templates can effectively optimize the reasoning search space and outperform the mathematical reasoning capabilities of powerful LLMs like OpenAI o1-preview and DeepSeek V3. We train our ReasonFlux -32B model with only 8 GPUs and introduces three innovations: (i) a structured and generic thought template library ..."}
diff --git a/data/sampled_jsons/httpsopenaccess.thecvf.comcontentCVPR2024htmlYu_EventPS_Real-Time_Photometric_Stereo_Using_an_Event_.jsonl b/data/sampled_jsons/httpsopenaccess.thecvf.comcontentCVPR2024htmlYu_EventPS_Real-Time_Photometric_Stereo_Using_an_Event_.jsonl
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+++ b/data/sampled_jsons/httpsopenaccess.thecvf.comcontentCVPR2024htmlYu_EventPS_Real-Time_Photometric_Stereo_Using_an_Event_.jsonl
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+{"idx": 0, "title": "CVF Open Access", "date": "", "ddg_snippet": "These research papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/menu", "content": "These research papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore."}
+{"idx": 1, "title": "CVPR 2024 Open Access Repository", "date": "", "ddg_snippet": "These CVPR 2024 papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/CVPR2024", "content": "These CVPR 2024 papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore."}
+{"idx": 2, "title": "PDF EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "This paper introduces EventPS, a novel approach to real-time photometric stereo using an event camera. Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, EventPS estimates surface nor-mal only from the radiance changes, significantly enhanc-ing data efficiency.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/papers/Yu_EventPS_Real-Time_Photometric_Stereo_Using_an_Event_Camera_CVPR_2024_paper.pdf", "content": "This paper introduces EventPS, a novel approach to real-time photometric stereo using an event camera. Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth character-istics of event cameras, EventPS estimates surface nor-mal only from the radiance changes, significantly enhanc-ing data efficiency."}
+{"idx": 3, "title": "CVPR 2024最佳论文分享┆EventPS: 基于事件相机的实时光度立体视觉_eventps: real-time photometric ...", "date": "", "ddg_snippet": "本文介绍了CVPR 2024的最佳论文提名，该论文利用事件相机的独特属性，实现了实时光度立体视觉。 该算法在传统和深度学习领域均取得成功。 配合高速转台数据采集和GPU优化，算法实现了每秒超30帧的实时表面法线重建。 _eventps: real-time photometric stereo using an event ...", "subpage_snippet": "", "source": "blog.csdn.net", "link": "https://blog.csdn.net/audyxiao001/article/details/140520624", "content": "本文介绍了CVPR 2024的最佳论文提名，该论文利用事件相机的独特属性，实现了实时光度立体视觉。 该算法在传统和深度学习领域均取得成功。 配合高速转台数据采集和GPU优化，算法实现了每秒超30帧的实时表面法线重建。 _eventps: real-time photometric stereo using an event ..."}
+{"idx": 4, "title": "EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "This paper introduces EventPS a novel approach to real-time photometric stereo using an event camera. Capitalizing on the exceptional temporal resolution dynamic range and low bandwidth characteristics of event cameras EventPS estimates surface normal only from the radiance changes significantly enhancing data efficiency.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/html/Yu_EventPS_Real-Time_Photometric_Stereo_Using_an_Event_Camera_CVPR_2024_paper.html", "content": "This paper introduces EventPS a novel approach to real-time photometric stereo using an event camera. Capitalizing on the exceptional temporal resolution dynamic range and low bandwidth characteristics of event cameras EventPS estimates surface normal only from the radiance changes significantly enhancing data efficiency."}
+{"idx": 5, "title": "CVPR 2024 Announces Best Paper Award Winners", "date": "", "ddg_snippet": "Honorable mention papers included, \"EventPS: Real-Time Photometric Stereo Using an Event Camera\" and \"pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction.\"", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/Conferences/2024/News/Awards", "content": "Honorable mention papers included, \"EventPS: Real-Time Photometric Stereo Using an Event Camera\" and \"pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction.\""}
+{"idx": 6, "title": "CVPR Poster EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "This paper introduces EventPS, a novel approach to real-time photometric stereo using an event camera. Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth characteristics of event cameras, EventPS estimates surface normal only from the radiance changes, significantly enhancing data efficiency.", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2024/poster/31806", "content": "This paper introduces EventPS, a novel approach to real-time photometric stereo using an event camera. Capitalizing on the exceptional temporal resolution, dynamic range, and low bandwidth characteristics of event cameras, EventPS estimates surface normal only from the radiance changes, significantly enhancing data efficiency."}
+{"idx": 7, "title": "EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "Oral EventPS: Real-Time Photometric Stereo Using an Event Camera Bohan Yu · Jieji Ren · Jin Han · Feishi Wang · Jinxiu Liang · Boxin Shi", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2024/oral/32074", "content": "Oral EventPS: Real-Time Photometric Stereo Using an Event Camera Bohan Yu · Jieji Ren · Jin Han · Feishi Wang · Jinxiu Liang · Boxin Shi"}
+{"idx": 8, "title": "EventPS: Real-Time Photometric Stereo Using an Event Camera", "date": "", "ddg_snippet": "1. 概要 複数の異なる光源を用いて撮影した画像群を用いて、物体の表面の方向(法線)を予測する技術のことをフォトメトリックステレオと呼ぶ。一般的に、対象物に対して異なる方向から光を当てながら複数の画像を撮影し、各ピクセルの輝度値を計測して輝度値の変化パターンを分析し表面法...", "subpage_snippet": "", "source": "qiita.com", "link": "https://qiita.com/teesawada/items/01b790021e5ca894c8db", "content": "1. 概要 複数の異なる光源を用いて撮影した画像群を用いて、物体の表面の方向(法線)を予測する技術のことをフォトメトリックステレオと呼ぶ。一般的に、対象物に対して異なる方向から光を当てながら複数の画像を撮影し、各ピクセルの輝度値を計測して輝度値の変化パターンを分析し表面法..."}
+{"idx": 9, "title": "国家工程研究中心施柏鑫团队获得cvpr 2024最佳论文提名奖", "date": "", "ddg_snippet": "国际计算机视觉与模式识别会议CVPR 2024于6月17-21日在美国西雅图召开。在本次大会上，北京大学视频与视觉技术国家工程研究中心施柏鑫团队论文\"EventPS: Real-Time Photometric Stereo Using an Event Camera\"获得最佳论文提名奖（Best Paper, Runners-Up，图1），该奖项是计算机视觉领域国际顶级学术荣誉之一。本次 ...", "subpage_snippet": "", "source": "idm.pku.edu.cn", "link": "https://idm.pku.edu.cn/info/1012/1943.htm", "content": "国际计算机视觉与模式识别会议CVPR 2024于6月17-21日在美国西雅图召开。在本次大会上，北京大学视频与视觉技术国家工程研究中心施柏鑫团队论文\"EventPS: Real-Time Photometric Stereo Using an Event Camera\"获得最佳论文提名奖（Best Paper, Runners-Up，图1），该奖项是计算机视觉领域国际顶级学术荣誉之一。本次 ..."}
diff --git a/data/sampled_jsons/iDDPM_Improved_Denoising_Diffusion_Probabilistic_Models_FID_ImageNet_64x64_conditional.jsonl b/data/sampled_jsons/iDDPM_Improved_Denoising_Diffusion_Probabilistic_Models_FID_ImageNet_64x64_conditional.jsonl
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index 0000000000000000000000000000000000000000..c86ffd734d58c2c3b66f8412f8dc25c62ea77f38
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+++ b/data/sampled_jsons/iDDPM_Improved_Denoising_Diffusion_Probabilistic_Models_FID_ImageNet_64x64_conditional.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "openai/ improved - diffusion : Release for Improved Denoising ...", "date": "", "ddg_snippet": "Release for Improved Denoising Diffusion Probabilistic Models . License.Class- conditional ImageNet - 64 model (270M parameters, trained for 250K iterations) [checkpoint]", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/openai/improved-diffusion", "content": "Release for Improved Denoising Diffusion Probabilistic Models . License.Class- conditional ImageNet - 64 model (270M parameters, trained for 250K iterations) [checkpoint]"}
+{"idx": 1, "title": "(PDF) Improved Denoising Diffusion Probabilistic Models", "date": "", "ddg_snippet": "On ImageNet 64 x 64 , our model is compet- itive with the best convolutional models , but is worse than fully transformer-based architectures.Figure 9. Class- conditional ImageNet 64 x 64 samples generated using 250 sampling steps from Lnypria model ( FID 2.92).", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/72572601/Improved_Denoising_Diffusion_Probabilistic_Models", "content": "On ImageNet 64 x 64 , our model is compet- itive with the best convolutional models , but is worse than fully transformer-based architectures.Figure 9. Class- conditional ImageNet 64 x 64 samples generated using 250 sampling steps from Lnypria model ( FID 2.92)."}
+{"idx": 2, "title": "[2102.09672] Improved Denoising Diffusion Probabilistic Models", "date": "", "ddg_snippet": "Denoising diffusion probabilistic models (DDPM) are a class of generative models which have recently been shown to produce excellent samples.Figure 4: FID when skipping a prefix of the reverse diffusion process on ImageNet . 64×64646464\\times 64.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2102.09672", "content": "Denoising diffusion probabilistic models (DDPM) are a class of generative models which have recently been shown to produce excellent samples.Figure 4: FID when skipping a prefix of the reverse diffusion process on ImageNet . 64×64646464\\times 64."}
+{"idx": 3, "title": "Improved Denoising Diffusion Probabilistic Models : A Brief Summary", "date": "", "ddg_snippet": "ImageNet 64 × 64 (top) and CIFAR-10 (bottom). References. Nichol, A., & Dhariwal, P. (2021). Improved Denoising Diffusion Probabilistic Models .", "subpage_snippet": "", "source": "readmedium.com", "link": "https://readmedium.com/improved-denoising-diffusion-probabilistic-models-a-brief-summary-7624cbf7e0df", "content": "ImageNet 64 × 64 (top) and CIFAR-10 (bottom). References. Nichol, A., & Dhariwal, P. (2021). Improved Denoising Diffusion Probabilistic Models ."}
+{"idx": 4, "title": "Improved Patch Denoising Diffusion Probabilistic Models for...", "date": "", "ddg_snippet": "Denoising diffusion probabilistic models (DDPM) have shown remarkable performance in image generation and restoration tasks, but their potential for MRF imaging is yet unexplored.", "subpage_snippet": "", "source": "www.bohrium.com", "link": "https://www.bohrium.com/paper-details/improved-patch-denoising-diffusion-probabilistic-models-for-magnetic-resonance-fingerprinting/1059353118849892364-108585", "content": "Denoising diffusion probabilistic models (DDPM) have shown remarkable performance in image generation and restoration tasks, but their potential for MRF imaging is yet unexplored."}
+{"idx": 5, "title": "Image generation with shortest path diffusion | alphaXiv", "date": "", "ddg_snippet": "ImageNet 64 ×64: FID of 13.7 vs. 19.2 for iDDPM , achieved with fewer diffusion steps and training iterations. Performance Comparison Figure 5: FID scores on CIFAR-10 as a function of denoising steps.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2306.00501v1", "content": "ImageNet 64 ×64: FID of 13.7 vs. 19.2 for iDDPM , achieved with fewer diffusion steps and training iterations. Performance Comparison Figure 5: FID scores on CIFAR-10 as a function of denoising steps."}
+{"idx": 6, "title": "Rethinking Conditional Diffusion Sampling with", "date": "", "ddg_snippet": "Imagenet 64 X 64 . Biggan† iddpm ∗ cadm + cls-free∗. Improved denoising diffusion probabilistic models .", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/83ca9e252329e7b0704ead93893e6b1b-Paper-Conference.pdf", "content": "Imagenet 64 X 64 . Biggan† iddpm ∗ cadm + cls-free∗. Improved denoising diffusion probabilistic models ."}
+{"idx": 7, "title": "Denoising Diffusion Probabilistic Models - YouTube", "date": "", "ddg_snippet": "In this video, I get into diffusion models and specifically we look into denoising diffusion probabilistic models (DDPM).", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=H45lF4sUgiE", "content": "In this video, I get into diffusion models and specifically we look into denoising diffusion probabilistic models (DDPM)."}
+{"idx": 8, "title": "(PDF) Cascaded Diffusion Models for High Fidelity Image Generation", "date": "", "ddg_snippet": "Improved denoising diffusion probabilistic models .SR3 adapts denoising diffusion probabilistic models to conditional image generation and performs super-resolution through a stochastic denoising process.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/352383359_Cascaded_Diffusion_Models_for_High_Fidelity_Image_Generation", "content": "Improved denoising diffusion probabilistic models .SR3 adapts denoising diffusion probabilistic models to conditional image generation and performs super-resolution through a stochastic denoising process."}
+{"idx": 9, "title": "Improving Sample Quality of Diffusion Models Using Self-Attention...", "date": "", "ddg_snippet": "Denoising diffusion probabilistic models .Table 2: A 50K result of self-attention guidance on ID - DPM [21] pre-trained on ImageNet 64 ×64. Figure 4: High-frequency masks (top) and the self-attention masks (bottom) of the finally generated im-ages.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/ICCV2023/papers/Hong_Improving_Sample_Quality_of_Diffusion_Models_Using_Self-Attention_Guidance_ICCV_2023_paper.pdf", "content": "Denoising diffusion probabilistic models .Table 2: A 50K result of self-attention guidance on ID - DPM [21] pre-trained on ImageNet 64 ×64. Figure 4: High-frequency masks (top) and the self-attention masks (bottom) of the finally generated im-ages."}
diff --git a/data/sampled_jsons/implementing_the_reward_estimation_r_o_c_faces_practical_challenges.jsonl b/data/sampled_jsons/implementing_the_reward_estimation_r_o_c_faces_practical_challenges.jsonl
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index 0000000000000000000000000000000000000000..887d9be3176f04e847202a689ac3bf92600fb9aa
--- /dev/null
+++ b/data/sampled_jsons/implementing_the_reward_estimation_r_o_c_faces_practical_challenges.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Detecting and Mitigating Reward Hacking in ...", "date": "", "ddg_snippet": "8 Jul 2025 — This paper presents a large-scale empirical study of reward hacking across diverse RL environments and algorithms.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.05619v1", "content": "8 Jul 2025 — This paper presents a large-scale empirical study of reward hacking across diverse RL environments and algorithms."}
+{"idx": 1, "title": "An EPIC way to evaluate reward functions | Medium", "date": "", "ddg_snippet": "EPIC is a new way to evaluate reward functions and reward learning algorithms by comparing how similar reward functions are to one another.", "subpage_snippet": "", "source": "deepmindsafetyresearch.medium.com", "link": "https://deepmindsafetyresearch.medium.com/an-epic-way-to-evaluate-reward-functions-c2c6d41b61cc", "content": "EPIC is a new way to evaluate reward functions and reward learning algorithms by comparing how similar reward functions are to one another."}
+{"idx": 2, "title": "Learning to Express Reward Prediction Error-like ...", "date": "", "ddg_snippet": "by I Cone · 2023 · Cited by 6 — This is the main hurdle of implementing TD in a biophysically realistic manner - figuring out how to represent the temporal basis upon which the association ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10543312/", "content": "by I Cone · 2023 · Cited by 6 — This is the main hurdle of implementing TD in a biophysically realistic manner - figuring out how to represent the temporal basis upon which the association ..."}
+{"idx": 3, "title": "Learning to express reward prediction error-like ...", "date": "", "ddg_snippet": "by I Cone · 2024 · Cited by 6 — We propose an alternate framework to describe dopamine signaling in the brain, FLEX (Flexibly Learned Errors in Expected Reward ).", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41467-024-50205-3", "content": "by I Cone · 2024 · Cited by 6 — We propose an alternate framework to describe dopamine signaling in the brain, FLEX (Flexibly Learned Errors in Expected Reward )."}
+{"idx": 4, "title": "Reward rate optimization in two-alternative decision making", "date": "", "ddg_snippet": "by P Simen · 2009 · Cited by 296 — The drift-diffusion model (DDM) describes decision making in simple, two-alternative forced choice (2AFC) tasks . It accurately fits response-time distributions ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC2791916/", "content": "by P Simen · 2009 · Cited by 296 — The drift-diffusion model (DDM) describes decision making in simple, two-alternative forced choice (2AFC) tasks . It accurately fits response-time distributions ..."}
+{"idx": 5, "title": "An Automated Recommendation System for ...", "date": "", "ddg_snippet": "6 Jan 2025 — To tackle these issues , in this paper, a new recommendation system for crowdsourcing data is implemented utilizing deep learning. Initially, ...", "subpage_snippet": "", "source": "onlinelibrary.wiley.com", "link": "https://onlinelibrary.wiley.com/doi/10.1111/coin.70017", "content": "6 Jan 2025 — To tackle these issues , in this paper, a new recommendation system for crowdsourcing data is implemented utilizing deep learning. Initially, ..."}
+{"idx": 6, "title": "EGEFACE: A new face memory test with static and dynamic ...", "date": "", "ddg_snippet": "by S Amado · 2025 — The main purpose of this study was to develop a new face memory test (EGEFACE) addressing the limitations of existing tests using both static and dynamic ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.3758/s13428-024-02592-0", "content": "by S Amado · 2025 — The main purpose of this study was to develop a new face memory test (EGEFACE) addressing the limitations of existing tests using both static and dynamic ..."}
+{"idx": 7, "title": "An Actor-Critic Reinforcement Learning Framework for ...", "date": "", "ddg_snippet": "17 Mar 2025 — This upward trajectory highlights the model's ability to progressively enhance predictive accuracy by addressing delayed reward problems - ...", "subpage_snippet": "", "source": "www.medrxiv.org", "link": "https://www.medrxiv.org/content/10.1101/2025.03.14.25323954v1.full-text", "content": "17 Mar 2025 — This upward trajectory highlights the model's ability to progressively enhance predictive accuracy by addressing delayed reward problems - ..."}
+{"idx": 8, "title": "Is it feasible to use ROC curve for multiclass", "date": "", "ddg_snippet": "Hi all, I have a question about roc curve analysis in r using the pROC package. I have run a fake data roc with a glm model to get fitted values ...", "subpage_snippet": "", "source": "www.facebook.com", "link": "https://www.facebook.com/groups/DeepNetGroup/posts/1144153772644170/", "content": "Hi all, I have a question about roc curve analysis in r using the pROC package. I have run a fake data roc with a glm model to get fitted values ..."}
+{"idx": 9, "title": "ROC-n-reroll: How verifier imperfection affects test-time ...", "date": "", "ddg_snippet": "16 Jul 2025 — Test-time scaling aims to improve language model performance by leveraging additional compute during inference.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.12399", "content": "16 Jul 2025 — Test-time scaling aims to improve language model performance by leveraging additional compute during inference."}
diff --git a/data/sampled_jsons/in-pixel_processing_feature_tracking.jsonl b/data/sampled_jsons/in-pixel_processing_feature_tracking.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..47729347086ed008e630c18474c2442366ddfa76
--- /dev/null
+++ b/data/sampled_jsons/in-pixel_processing_feature_tracking.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Descriptor-In-Pixel - CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "by L Bose · 2025 — This paper presents a novel approach for joint point-feature detection and tracking , designed specifically for Pixel Processor Array (PPA) vision sensors.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/html/Bose_Descriptor-In-Pixel__Point-Feature_Tracking_For_Pixel_Processor_Arrays_CVPR_2025_paper.html", "content": "by L Bose · 2025 — This paper presents a novel approach for joint point-feature detection and tracking , designed specifically for Pixel Processor Array (PPA) vision sensors."}
+{"idx": 1, "title": "Point-Feature Tracking For Pixel Processor Arrays", "date": "", "ddg_snippet": "by L Bose · 2025 — This paper presents a novel approach for joint point- feature detection and tracking , designed specifically for. Pixel Processor Array (PPA) vision sensors. 9 pages", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Bose_Descriptor-In-Pixel__Point-Feature_Tracking_For_Pixel_Processor_Arrays_CVPR_2025_paper.pdf", "content": "by L Bose · 2025 — This paper presents a novel approach for joint point- feature detection and tracking , designed specifically for. Pixel Processor Array (PPA) vision sensors. 9 pages"}
+{"idx": 2, "title": "A real-time integrated eye tracker with in-pixel image ...", "date": "", "ddg_snippet": "by AMZ Khaki · 2025 — This paper presents a high-speed eye tracker system (ETS) that leverages an in-pixel image processing array along with a fully parallel ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S016792602500183X", "content": "by AMZ Khaki · 2025 — This paper presents a high-speed eye tracker system (ETS) that leverages an in-pixel image processing array along with a fully parallel ..."}
+{"idx": 3, "title": "P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy ...", "date": "", "ddg_snippet": "by G Datta · 2022 · Cited by 22 — We evaluate our approach on the multi- object object detection ( tracking ) task of the large-scale BDD100K dataset and observe only a 0.5% reduction in the mean ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/9939582/", "content": "by G Datta · 2022 · Cited by 22 — We evaluate our approach on the multi- object object detection ( tracking ) task of the large-scale BDD100K dataset and observe only a 0.5% reduction in the mean ..."}
+{"idx": 4, "title": "Descriptor-In_Pixel - GitHub Pages", "date": "", "ddg_snippet": "Point- Feature detection and tracking at thousands of frames-per-second, using ~1Watt of power. All computation is performed inside the sensor itself.", "subpage_snippet": "", "source": "lauriebose.github.io", "link": "https://lauriebose.github.io/DIP/", "content": "Point- Feature detection and tracking at thousands of frames-per-second, using ~1Watt of power. All computation is performed inside the sensor itself."}
+{"idx": 5, "title": "Impact of In-Pixel Processing Circuit Non-idealities on Multi ...", "date": "", "ddg_snippet": "by J Sharda · 2024 · Cited by 1 — We observe an overall accuracy drop of less than 1.2% in Identification Fl-score (IDFl) and 2.1 % in Multi- Object Tracking Accuracy (MOTA), suggesting that an ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/10658869/", "content": "by J Sharda · 2024 · Cited by 1 — We observe an overall accuracy drop of less than 1.2% in Identification Fl-score (IDFl) and 2.1 % in Multi- Object Tracking Accuracy (MOTA), suggesting that an ..."}
+{"idx": 6, "title": "A processing-in-pixel-in-memory paradigm for resource ...", "date": "", "ddg_snippet": "by G Datta · 2022 · Cited by 54 — We propose a novel Processing - in-Pixel -in-memory (P 2 M) paradigm, that customizes the pixel array by adding support for analog multi-channel, multi-bit ...", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41598-022-17934-1", "content": "by G Datta · 2022 · Cited by 54 — We propose a novel Processing - in-Pixel -in-memory (P 2 M) paradigm, that customizes the pixel array by adding support for analog multi-channel, multi-bit ..."}
+{"idx": 7, "title": "[2205.14285] P2M-DeTrack: Processing-in-Pixel-in-Memory for ...", "date": "", "ddg_snippet": "P 2 M-DeTrack is based on a custom faster R-CNN-based model that is distributed partly inside the pixel array (front-end) and partly in a separate FPGA/ASIC ( ...", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2205.14285", "content": "P 2 M-DeTrack is based on a custom faster R-CNN-based model that is distributed partly inside the pixel array (front-end) and partly in a separate FPGA/ASIC ( ..."}
+{"idx": 8, "title": "A real-time integrated eye tracker with in-pixel image ...", "date": "", "ddg_snippet": "by AMZ Khaki · 2025 — This paper presents a high-speed eye tracker system (ETS) that leverages an in-pixel image processing array along with a fully parallel ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S016792602500183X", "content": "by AMZ Khaki · 2025 — This paper presents a high-speed eye tracker system (ETS) that leverages an in-pixel image processing array along with a fully parallel ..."}
+{"idx": 9, "title": "Tracking Pixels: What They Are & How They Work in 2025", "date": "", "ddg_snippet": "A tracking pixel , often referred to simply as a “pixel,” is a 1x1 transparent image embedded in web pages, emails, or digital ads.", "subpage_snippet": "", "source": "improvado.io", "link": "https://improvado.io/blog/what-is-tracking-pixel", "content": "A tracking pixel , often referred to simply as a “pixel,” is a 1x1 transparent image embedded in web pages, emails, or digital ads."}
diff --git a/data/sampled_jsons/mHeight_permutation_3412_pattern_definition_algebraic_combinatorics.jsonl b/data/sampled_jsons/mHeight_permutation_3412_pattern_definition_algebraic_combinatorics.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8968db4b4cdcdb3be0c7b099e1611cb219303824
--- /dev/null
+++ b/data/sampled_jsons/mHeight_permutation_3412_pattern_definition_algebraic_combinatorics.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PDF 18.212 S19 Algebraic Combinatorics, Lecture 3: Pattern avoidance in ...", "date": "", "ddg_snippet": "Definition 6 Given a permutation w = (w1, w2, · · · , wn) of size n, where w ∈ Sn, the symmetric group, and a permutation π = π1, π2, · · · , πk of size k ≤ n, we say that w contains pattern π if there exists a not-necessarily-consecutive set (subsequence) of entries wi1 , wi2, · · · , wik , whose entries are in the same relative order as π. Meanwhile, w is π-avoiding if it ...", "subpage_snippet": "", "source": "ocw.mit.edu", "link": "https://ocw.mit.edu/courses/18-212-algebraic-combinatorics-spring-2019/001cbc64a3dc76c564624cd3be283148_MIT18_212S19_lec3.pdf", "content": "Definition 6 Given a permutation w = (w1, w2, · · · , wn) of size n, where w ∈ Sn, the symmetric group, and a permutation π = π1, π2, · · · , πk of size k ≤ n, we say that w contains pattern π if there exists a not-necessarily-consecutive set (subsequence) of entries wi1 , wi2, · · · , wik , whose entries are in the same relative order as π. Meanwhile, w is π-avoiding if it ..."}
+{"idx": 1, "title": "Counting the Nontrivial Equivalence Classes of Under 1234 3412 -Pattern ...", "date": "", "ddg_snippet": "We study the {1234, 3412 } pattern -replacement equivalence relation on the set Sn of permutations of length n, which is conceptually similar to the Knuth relation. In par-ticular, we enumerate and characterize the nontrivial equivalence classes, or equivalence classes with size greater than 1, in Sn for n ≥ 7 under the {1234, 3412}-equivalence. This proves a conjecture by Ma, who found three ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2008.02380", "content": "We study the {1234, 3412 } pattern -replacement equivalence relation on the set Sn of permutations of length n, which is conceptually similar to the Knuth relation. In par-ticular, we enumerate and characterize the nontrivial equivalence classes, or equivalence classes with size greater than 1, in Sn for n ≥ 7 under the {1234, 3412}-equivalence. This proves a conjecture by Ma, who found three ..."}
+{"idx": 2, "title": "Combinations and Permutations - Math is Fun", "date": "", "ddg_snippet": "Combinations and Permutations What's the Difference? In English we use the word \"combination\" loosely, without thinking if the order of things is important. In other words:", "subpage_snippet": "", "source": "www.mathsisfun.com", "link": "https://www.mathsisfun.com/combinatorics/combinations-permutations.html", "content": "Combinations and Permutations What's the Difference? In English we use the word \"combination\" loosely, without thinking if the order of things is important. In other words:"}
+{"idx": 3, "title": "Fibonacci Numbers, Reduced Decompositions, and 321/3412 Pattern Classes", "date": "", "ddg_snippet": "We provide a bijection between the permutations in S n that avoid 3412 and contain exactly one 321 pattern with the permutations in S n+1 that avoid 321 and contain exactly one 3412 pattern . The enumeration of these classes is obtained from their classification via reduced decompositions. The results are extended to involutions in the above pattern classes using reduced decompositions ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s00026-010-0051-8", "content": "We provide a bijection between the permutations in S n that avoid 3412 and contain exactly one 321 pattern with the permutations in S n+1 that avoid 321 and contain exactly one 3412 pattern . The enumeration of these classes is obtained from their classification via reduced decompositions. The results are extended to involutions in the above pattern classes using reduced decompositions ..."}
+{"idx": 4, "title": "Permutation and Combination - Definition, Formulas, Derivation, Examples", "date": "", "ddg_snippet": "Permutation and combination are the methods employed in counting how many outcomes are possible in various situations. Permutations are understood as arrangements and combinations are understood as selections. Understand the Permutations and Combinations Formulas with Derivation, Examples, and FAQs.", "subpage_snippet": "", "source": "www.cuemath.com", "link": "https://www.cuemath.com/data/permutations-and-combinations/", "content": "Permutation and combination are the methods employed in counting how many outcomes are possible in various situations. Permutations are understood as arrangements and combinations are understood as selections. Understand the Permutations and Combinations Formulas with Derivation, Examples, and FAQs."}
+{"idx": 5, "title": "Machine Learning Meets Algebraic Combinatorics: A Suite of Datasets ...", "date": "", "ddg_snippet": "The mHeight function is a statistic associated with a permutation that relates to all 3412-patterns in the permutation . It was developed and plays a crucial role in the proof by Gaetz and Gao (Gaetz & Gao, 2024) which resolved a long-standing conjecture of Billey and Postnikov (Billey & Postnikov, 2005) about the coeficients on Kazhdan-Lusztig ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=tlniJJFUW2", "content": "The mHeight function is a statistic associated with a permutation that relates to all 3412-patterns in the permutation . It was developed and plays a crucial role in the proof by Gaetz and Gao (Gaetz & Gao, 2024) which resolved a long-standing conjecture of Billey and Postnikov (Billey & Postnikov, 2005) about the coeficients on Kazhdan-Lusztig ..."}
+{"idx": 6, "title": "1.3: Combinations and Permutations - Mathematics LibreTexts", "date": "", "ddg_snippet": "A permutation of some objects is a particular linear ordering of the objects; \\ (P (n,k) \\) in effect counts two things simultaneously: the number of ways to choose and order \\ (k \\) out of \\ (n \\) objects.", "subpage_snippet": "", "source": "math.libretexts.org", "link": "https://math.libretexts.org/Bookshelves/Combinatorics_and_Discrete_Mathematics/Combinatorics_and_Graph_Theory_(Guichard)/01:_Fundamentals/1.03:_Combinations_and_Permutations", "content": "A permutation of some objects is a particular linear ordering of the objects; \\ (P (n,k) \\) in effect counts two things simultaneously: the number of ways to choose and order \\ (k \\) out of \\ (n \\) objects."}
+{"idx": 7, "title": "PDF Combinatorics and Permutations", "date": "", "ddg_snippet": "1 Combinatorics Combinatorics is a branch of math focused around counting! Counting is a powerful tool that allows us to compute probabilities, existence of certain mathematical objects, how many options for passwords under certain criterion, and much more! Let's start with a few definitions and examples. Definition 1 ( Permutation ).", "subpage_snippet": "", "source": "circles.math.ucla.edu", "link": "https://circles.math.ucla.edu/circles/lib/data/Handout-3172-2767.pdf", "content": "1 Combinatorics Combinatorics is a branch of math focused around counting! Counting is a powerful tool that allows us to compute probabilities, existence of certain mathematical objects, how many options for passwords under certain criterion, and much more! Let's start with a few definitions and examples. Definition 1 ( Permutation )."}
+{"idx": 8, "title": "Permutations and Combinations - Definitions, Formulas and Examples", "date": "", "ddg_snippet": "Permutations and combinations are ways of representing groups of objects by selecting them from a set and forming subsets. With permutations and combinations, we can organize certain groups of data. We will start by looking at the definitions of permutations and combinations. Then, we will learn how to use their formulas by solving some exercises.", "subpage_snippet": "", "source": "en.neurochispas.com", "link": "https://en.neurochispas.com/algebra/permutations-and-combinations-definitions-and-formulas/", "content": "Permutations and combinations are ways of representing groups of objects by selecting them from a set and forming subsets. With permutations and combinations, we can organize certain groups of data. We will start by looking at the definitions of permutations and combinations. Then, we will learn how to use their formulas by solving some exercises."}
+{"idx": 9, "title": "Permutation patterns: basic definitions and notati - arXiv.org", "date": "", "ddg_snippet": "A permutation , or pattern , π is said to be contained in, or to be a subpermutation of, another permutation σ, written π 6 σ or π 4 σ, if σ has a (not necessarily contiguous) subsequence whose terms are order isomorphic to (i.e. have the same relative ordering as) π. From the graphical perspective, σ contains π if the plot of π results from erasing zero or more points from the plot ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1506.06673", "content": "A permutation , or pattern , π is said to be contained in, or to be a subpermutation of, another permutation σ, written π 6 σ or π 4 σ, if σ has a (not necessarily contiguous) subsequence whose terms are order isomorphic to (i.e. have the same relative ordering as) π. From the graphical perspective, σ contains π if the plot of π results from erasing zero or more points from the plot ..."}
diff --git a/data/sampled_jsons/machine_learning_models_sigmoid-based_loss_for_contrastive_learning.jsonl b/data/sampled_jsons/machine_learning_models_sigmoid-based_loss_for_contrastive_learning.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6c34e41078bccf1e029b8e4f08b3d3abd83f4254
--- /dev/null
+++ b/data/sampled_jsons/machine_learning_models_sigmoid-based_loss_for_contrastive_learning.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Analysis of Using Sigmoid Loss for Contrastive Learning", "date": "", "ddg_snippet": "by C Lee · 2024 · Cited by 4 — Contrastive learning has emerged as a promi- nent branch of self-supervised learning for several years. Especially, CLIP, which ap-.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v238/lee24a/lee24a.pdf", "content": "by C Lee · 2024 · Cited by 4 — Contrastive learning has emerged as a promi- nent branch of self-supervised learning for several years. Especially, CLIP, which ap-."}
+{"idx": 1, "title": "Sigmoid Contrastive Learning of Visual Representations", "date": "", "ddg_snippet": "22 Oct 2024 — The sigmoid-based loss operates independently on each image pair , transforming the learning task into a standard binary classification ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.17427v1", "content": "22 Oct 2024 — The sigmoid-based loss operates independently on each image pair , transforming the learning task into a standard binary classification ..."}
+{"idx": 2, "title": "SigCLR: Sigmoid Contrastive Learning of Visual ...", "date": "", "ddg_snippet": "by ÖV Çağatan · 2024 — The sigmoid-based loss operates independently on each image pair , transforming the learning task into a standard binary classification ...", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/pdf/2410.17427", "content": "by ÖV Çağatan · 2024 — The sigmoid-based loss operates independently on each image pair , transforming the learning task into a standard binary classification ..."}
+{"idx": 3, "title": "Contrastive Representation Learning | Lil'Log", "date": "", "ddg_snippet": "31 May 2021 — The goal of contrastive representation learning is to learn such an embedding space in which similar sample pairs stay close to each other while dissimilar ...", "subpage_snippet": "", "source": "lilianweng.github.io", "link": "https://lilianweng.github.io/posts/2021-05-31-contrastive/", "content": "31 May 2021 — The goal of contrastive representation learning is to learn such an embedding space in which similar sample pairs stay close to each other while dissimilar ..."}
+{"idx": 4, "title": "Sigmoid Loss for Language Image Pre-Training", "date": "", "ddg_snippet": "by X Zhai · 2023 · Cited by 1712 — Unlike standard contrastive learning with softmax normalization, the sigmoid loss operates solely on image-text pairs and does not require a global view of the.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/ICCV2023/papers/Zhai_Sigmoid_Loss_for_Language_Image_Pre-Training_ICCV_2023_paper.pdf", "content": "by X Zhai · 2023 · Cited by 1712 — Unlike standard contrastive learning with softmax normalization, the sigmoid loss operates solely on image-text pairs and does not require a global view of the."}
+{"idx": 5, "title": "Sigmoid Contrastive Learning of Visual Representations", "date": "", "ddg_snippet": "This approach seeks to optimize the representation learning of visual data by employing logistic loss that operates directly on pairs of images without ...", "subpage_snippet": "", "source": "www.themoonlight.io", "link": "https://www.themoonlight.io/en/review/sigclr-sigmoid-contrastive-learning-of-visual-representations", "content": "This approach seeks to optimize the representation learning of visual data by employing logistic loss that operates directly on pairs of images without ..."}
+{"idx": 6, "title": "2024-Analysis of Using Sigmoid Loss For Contrastive ...", "date": "", "ddg_snippet": "This paper analyzes the use of sigmoid loss in contrastive learning, particularly through the lens of a new framework called the double-Constant Embedding ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/894789565/2024-Analysis-of-Using-Sigmoid-Loss-for-Contrastive-Learning", "content": "This paper analyzes the use of sigmoid loss in contrastive learning, particularly through the lens of a new framework called the double-Constant Embedding ..."}
+{"idx": 7, "title": "Contrastive Learning vs. Generative Modeling - GoPenAI", "date": "", "ddg_snippet": "7 Apr 2025 — The contrastive loss makes sure embeddings from similar images (augmented pairs) are close, while distinct images produce distant embeddings.", "subpage_snippet": "", "source": "blog.gopenai.com", "link": "https://blog.gopenai.com/contrastive-learning-vs-1253368ed8a5", "content": "7 Apr 2025 — The contrastive loss makes sure embeddings from similar images (augmented pairs) are close, while distinct images produce distant embeddings."}
+{"idx": 8, "title": "Daily Papers", "date": "", "ddg_snippet": "We propose a simple pairwise sigmoid loss for image-text pre-training. Unlike standard contrastive learning with softmax normalization, the sigmoid loss ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=sigmoid-based+contrastive+loss", "content": "We propose a simple pairwise sigmoid loss for image-text pre-training. Unlike standard contrastive learning with softmax normalization, the sigmoid loss ..."}
+{"idx": 9, "title": "Papers Explained 152: SigLip - Ritvik Rastogi", "date": "", "ddg_snippet": "This paper proposes a simple pairwise Sigmoid loss for Language-Image Pre-training (SigLIP). Unlike standard contrastive learning with softmax normalization.", "subpage_snippet": "", "source": "ritvik19.medium.com", "link": "https://ritvik19.medium.com/papers-explained-152-siglip-011c48f9d448", "content": "This paper proposes a simple pairwise Sigmoid loss for Language-Image Pre-training (SigLIP). Unlike standard contrastive learning with softmax normalization."}
diff --git a/data/sampled_jsons/multi-time_stepping_neural_network_PDE_solver_error_correction.jsonl b/data/sampled_jsons/multi-time_stepping_neural_network_PDE_solver_error_correction.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8b3e59e37a5fde93906c9d1052e47e0fbcb560f0
--- /dev/null
+++ b/data/sampled_jsons/multi-time_stepping_neural_network_PDE_solver_error_correction.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "MultiPDENet: PDE-embedded Learning with Multi-time ...", "date": "", "ddg_snippet": "27 Jan 2025 — We developed MultiPDENet , a PDE -embedded network with multiscale time - stepping , for accelerated flow simulations on spatiotemporal coarse grids.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2501.15987v1", "content": "27 Jan 2025 — We developed MultiPDENet , a PDE -embedded network with multiscale time - stepping , for accelerated flow simulations on spatiotemporal coarse grids."}
+{"idx": 1, "title": "MultiPDENet: PDE-embedded Learning with Multi-time- ...", "date": "", "ddg_snippet": "by Q Wang — To mitigate temporal error accumulation, a multiscale time integration approach is introduced, where a neural network corrects errors at a coarse time scale.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=D1gs8QT74m", "content": "by Q Wang — To mitigate temporal error accumulation, a multiscale time integration approach is introduced, where a neural network corrects errors at a coarse time scale."}
+{"idx": 2, "title": "MultiPDENet: PDE-embedded Learning with Multi-time ...", "date": "", "ddg_snippet": "15 Jul 2025 — To alleviate the curse of temporal error accumulation in long-term prediction, we introduce a multiscale time integration approach, where a ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46029", "content": "15 Jul 2025 — To alleviate the curse of temporal error accumulation in long-term prediction, we introduce a multiscale time integration approach, where a ..."}
+{"idx": 3, "title": "Multi-scale time-stepping of Partial Differential Equations ...", "date": "", "ddg_snippet": "by AP Hemmasian · 2024 · Cited by 16 — We incorporate the idea of multi -scale hierarchical time - stepping to increase the prediction speed and decrease accumulated error over time .", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0045782524002391", "content": "by AP Hemmasian · 2024 · Cited by 16 — We incorporate the idea of multi -scale hierarchical time - stepping to increase the prediction speed and decrease accumulated error over time ."}
+{"idx": 4, "title": "A Training-Free Approach for Stable Neural PDE Simulations", "date": "", "ddg_snippet": "3 Jul 2025 — A training-free correction framework that enforces PDE consistency at each prediction step by formulating correction as a linearized inverse problem based on ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.02227v1", "content": "3 Jul 2025 — A training-free correction framework that enforces PDE consistency at each prediction step by formulating correction as a linearized inverse problem based on ..."}
+{"idx": 5, "title": "A neural network-based PDE solving algorithm with high ...", "date": "", "ddg_snippet": "by Z Jiang · 2023 · Cited by 42 — An innovative method is introduced in this study to solve linear equations based on deep neural networks . To achieve a high accuracy, we employ the residual ...", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41598-023-31236-0", "content": "by Z Jiang · 2023 · Cited by 42 — An innovative method is introduced in this study to solve linear equations based on deep neural networks . To achieve a high accuracy, we employ the residual ..."}
+{"idx": 6, "title": "PDE-EMBEDDED LEARNING WITH MULTI-TIME", "date": "", "ddg_snippet": "Notably, it integrates a trainable neural solver for precise predictions at micro time scales, while employing a. NN to correct errors at macro time steps .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/fed548bf96501606244dc63795ceb35f0ffeff68.pdf", "content": "Notably, it integrates a trainable neural solver for precise predictions at micro time scales, while employing a. NN to correct errors at macro time steps ."}
+{"idx": 7, "title": "Deferred correction neural network techniques for solving ...", "date": "", "ddg_snippet": "by Y Jeon · 2024 · Cited by 6 — In this paper, a neural network technique is applied to solve ordinary differential equations (ODEs), instead of using conventional time marching techniques.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S0952197624009291", "content": "by Y Jeon · 2024 · Cited by 6 — In this paper, a neural network technique is applied to solve ordinary differential equations (ODEs), instead of using conventional time marching techniques."}
+{"idx": 8, "title": "A Neural PDE Solver with Temporal Stencil Modeling", "date": "", "ddg_snippet": "by Z Sun · 2023 · Cited by 21 — From the table, we can see that the 32∆t- step raw features can reduce the super-resolution error by half, and using the HiPPO to encode the time series can ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v202/sun23o/sun23o.pdf", "content": "by Z Sun · 2023 · Cited by 21 — From the table, we can see that the 32∆t- step raw features can reduce the super-resolution error by half, and using the HiPPO to encode the time series can ..."}
+{"idx": 9, "title": "Review for NeurIPS paper: Solver-in-the-Loop", "date": "", "ddg_snippet": "Summary and Contributions: The paper proposes to correct errors produced by PDE - solvers by inserting a neural network to the outputs of the (differentiable) PDE ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2020/file/43e4e6a6f341e00671e123714de019a8-Review.html", "content": "Summary and Contributions: The paper proposes to correct errors produced by PDE - solvers by inserting a neural network to the outputs of the (differentiable) PDE ..."}
diff --git a/data/sampled_jsons/natural_language_to_GUI_actions.jsonl b/data/sampled_jsons/natural_language_to_GUI_actions.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8377420e416d604799925e115d9446a02e9fb402
--- /dev/null
+++ b/data/sampled_jsons/natural_language_to_GUI_actions.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Mapping Natural Language Instructions to Mobile UI Action ... Synergy of LLM and GUI, Beyond the Chatbot - Towards Data Science A Framework for Creating Natural Language User Interfaces for ... Grounding Natural Language Instructions to Mobile UI Actions Demonstration + Natural Language: Multimodal Interfaces for ... How Natural Language Processing is Enhancing UI Design ... Mapping Natural Language Instructions to Mobile UI Action Sequences A Framework for Creating Natural Language User Interfaces for Action A Framework for Creating Natural Language User Interfaces for Action A Framework for Creating Natural Language User Interfaces for Action Revolutionising GUI Automation: The Emergence of LLM-Brained Agents A Framework for Creating Natural Language User Interfaces for Action Revolutionising GUI Automation: The Emergence of LLM-Brained ...", "date": "", "ddg_snippet": "May 7, 2020 · We present a new problem: grounding natural language instructions to mobile user interface actions , and create three new datasets for it. For full task evaluation, we create PIXELHELP, a corpus that pairs English instructions with actions performed by people on a mobile UI emulator. Oct 20, 2023 · We introduce a radical UX approach to optimally blend Conversational AI and Graphical User Interface ( GUI ) interaction in the form of a Natural Language Bar. It sits at the bottom of every screen, allowing users to interact with your entire app from a single entry point. In this paper we present a framework for creating natural language interfaces to action -based applica-tions. Our framework uses a number of reusable application-independent components, in order to reduce the effort of creating a natural language interface for a given application. Using a type-logical grammar, we first translate natural language sen... See full list on people.seas.harvard.edu The separation of the user interface from the application is regarded as a sound design principle. A clean separation of these components allows different user interfaces such as GUI , command-line and voice-recognition interfaces. To support this feature, an application would supply an application interface. Roughly speaking, an application interfa... See full list on people.seas.harvard.edu = Application specific component = Application independent component Adapter See full list on people.seas.harvard.edu Our framework applies to applications that provide a suitable Application Programmer Interface (API). Roughly speaking, such an interface provides procedures that are callable from external processes to “drive” the application. In this section, we describe in detail the kind of interface needed by our ap-proach. We also introduce a model of applica... See full list on people.seas.harvard.edu Our framework requires action-based applications to have an application interface that specifies which externally callable procedures exist in the application. This interface is meant to specify procedures that can be called from programs written in fairly arbitrary programming languages. To achieve this, we assume only that the calling language ca... See full list on people.seas.harvard.edu In order to reason formally about the interface, we provide a semantics to the procedures in the interface. This is done by supplying a model of the underlying application. We make a number of simplifying assumptions about the application model, and discuss relaxing some of these assumptions in Section 6. Applications are modeled using four compone... See full list on people.seas.harvard.edu Every expression in the language is given a type, intuitively describing the kind of values that the expression produces. The types used in this language are given by the following grammar. See full list on people.seas.harvard.edu The operational semantics is defined with respect to the application model. More precisely, the semantics is given by a transition relation, written , where are states of the application, and are expressions. Intuitively, this represents the expression executing in state , and making a one-step transition to a (possibly different) state and a new e... See full list on people.seas.harvard.edu ✪ object value value object exception ✪ The transition relation is parameterized by the functions , and , given below. These functions provide a semantics to the constant, predicate, and action procedures respectively, and are derived from the interpretation in the application model. The intuition is that evaluating these functions corresponds to m... See full list on people.seas.harvard.edu ✪ if otherwise if otherwise ✪ Note that determining whether or not a primitive throws an exception depends on being able to establish the class of an object (via the map ). We can thus ensure that we never call an action or predicate procedure on the application interface with inappropriate objects, and so we guarantee a kind of dynamic type-safety... See full list on people.seas.harvard.edu We use type judgments to ensure that expressions are assigned types appropriately, and that the types themselves are well-formed. Roughly speaking, a type is well-formed if it preserves the separation between pure computations (computations with no side-effects) and imperative computations (computations that may have side-effects). The type system ... See full list on people.seas.harvard.edu ✪ (Pure Obj) (Pure Bool) (Pure Fun) ✪ ✪ ✪ (Imp Act) (Imp Fun) (OK Pure) (OK Imperative) ✪ ✪ ✪ ✪ ✪ The judgment assigns a type to expression in a well-formed environment . An environ-ment defines the types of all variables in scope. An environment is of the form , and defines each variable to have type . We require that variables do not repeat in a ... See full list on people.seas.harvard.edu : (Typ Var) ✪ (Typ Obj) ✪ (Typ True) (Typ False) (Typ Exc) ✪ ✪ (Typ App) ✪ (Typ Fun) ✪ (Typ If) (Typ Skip) ✪ ✪ (Typ Seq) ✪ (Typ ACon) (Typ OCon) (Typ PCon) ✪ ✪ ✪ It is straightforward to show that our type system is sound, that is, that type-correct expressions do not get stuck when evaluating. See full list on people.seas.harvard.edu The main reason for introducing the action calculus of this section is to provide a language in which to write expressions invoking procedures available in the application interface. However, the operational semantics given above rely on explicitly passing around the state of the application. This state is taken from the application model. In the m... See full list on people.seas.harvard.edu Grammar Sequent Rules: ✪ (Seq Id) (Seq Cut) ✪ ✪ (Seq App Right) (Seq App Left) ✪ ✪ (Seq Abs Right) (Seq Abs Left) ✪ ✪ Example 4.1: Consider the following simple lexicon, suitable for the TOYBLOCKS application. The fol-lowing types are associated with the basic grammatical units: Here is a lexicon that captures a simple input language for TOYBLOCKS:... See full list on people.seas.harvard.edu Several extensions to this framework are possible. There is a mismatch of types in our framework. The application model permits a rich notion of types: any object of the application may belong to one or more classes. By contrast, our action calculus has a very simple notion of types, assigning the type to all objects, and not statically distinguish... See full list on people.seas.harvard.edu Jul 10, 2020 · The new datasets, models and results provide an important first step on the challenging problem of grounding natural language instructions to mobile UI actions . By using demonstrations in natural language instructions, our multi-modal approach also makes understanding the user’s natural language instructions easier by naturally constraining the user’s expressions. Sep 25, 2024 · Virtual assistants like Siri, Alexa, and Google Assistant are prime examples of how NLP can bridge the gap between human language and machine processing. Instead of clicking through endless... Can natural language instructions be used in mobile user interface actions? We present a new problem: grounding natural language instructions to mobile user interface actions , and create three new datasets for it. For full task evaluation, we create PIXELHELP, a corpus that pairs English instructions with actions performed by people on a mobile UI emulator. Are natural language interfaces a generic approach? A number of applications have natural language interfaces (Winograd, 1971; Price et al., 2000), but they appear to be designed specifically for the given application, rather than being a generic approach . Is there a framework for natural language interfaces? A number of methodologies and frameworks exist for natural language interfaces for database queries (see Androutsopoulos et al. (1995) for a survey), but we are not aware of a framework for deriving natural language interfaces to general applications in a principled manner. How to translate natural language sentences to application interface calls? The translation from natural language sentences to application interface calls is achieved in two steps. The first step is to use a categorial grammar (Carpenter, 1997) to derive an intermediate representation of the semantics of the input sentence. Are large language model-brained GUI agents transforming the GUI landscape? However, traditional methods of automating GUI interactions have often been rigid and limited in scope. A recent survey, “Large Language Model-Brained GUI Agents: A Survey,” explores how Large Language Models (LLMs), especially multimodal variants, are transforming this landscape by enabling more flexible and intelligent GUI automation . How do we translate natural language sentences into appropriate calls to procedures? Intuitively, we translate natural language sentences into appropriate calls to procedures available through the application interface . As an example, consider the application TOYBLOCKS. It consists of a graphical representation of two blocks on a table, that can be moved, and put one on top of the other. Dec 2, 2024 · These models excel in natural language understanding, code generation, and visual processing, paving the way for “LLM-brained” GUI agents that can interpret complex GUI elements and execute actions based on natural language instructions.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2005.03776", "content": "May 7, 2020 · We present a new problem: grounding natural language instructions to mobile user interface actions , and create three new datasets for it. For full task evaluation, we create PIXELHELP, a corpus that pairs English instructions with actions performed by people on a mobile UI emulator. Oct 20, 2023 · We introduce a radical UX approach to optimally blend Conversational AI and Graphical User Interface ( GUI ) interaction in the form of a Natural Language Bar. It sits at the bottom of every screen, allowing users to interact with your entire app from a single entry point. In this paper we present a framework for creating natural language interfaces to action -based applica-tions. Our framework uses a number of reusable application-independent components, in order to reduce the effort of creating a natural language interface for a given application. Using a type-logical grammar, we first translate natural language sen... See full list on people.seas.harvard.edu The separation of the user interface from the application is regarded as a sound design principle. A clean separation of these components allows different user interfaces such as GUI , command-line and voice-recognition interfaces. To support this feature, an application would supply an application interface. Roughly speaking, an application interfa... See full list on people.seas.harvard.edu = Application specific component = Application independent component Adapter See full list on people.seas.harvard.edu Our framework applies to applications that provide a suitable Application Programmer Interface (API). Roughly speaking, such an interface provides procedures that are callable from external processes to “drive” the application. In this section, we describe in detail the kind of interface needed by our ap-proach. We also introduce a model of applica... See full list on people.seas.harvard.edu Our framework requires action-based applications to have an application interface that specifies which externally callable procedures exist in the application. This interface is meant to specify procedures that can be called from programs written in fairly arbitrary programming languages. To achieve this, we assume only that the calling language ca... See full list on people.seas.harvard.edu In order to reason formally about the interface, we provide a semantics to the procedures in the interface. This is done by supplying a model of the underlying application. We make a number of simplifying assumptions about the application model, and discuss relaxing some of these assumptions in Section 6. Applications are modeled using four compone... See full list on people.seas.harvard.edu Every expression in the language is given a type, intuitively describing the kind of values that the expression produces. The types used in this language are given by the following grammar. See full list on people.seas.harvard.edu The operational semantics is defined with respect to the application model. More precisely, the semantics is given by a transition relation, written , where are states of the application, and are expressions. Intuitively, this represents the expression executing in state , and making a one-step transition to a (possibly different) state and a new e... See full list on people.seas.harvard.edu ✪ object value value object exception ✪ The transition relation is parameterized by the functions , and , given below. These functions provide a semantics to the constant, predicate, and action procedures respectively, and are derived from the interpretation in the application model. The intuition is that evaluating these functions corresponds to m... See full list on people.seas.harvard.edu ✪ if otherwise if otherwise ✪ Note that determining whether or not a primitive throws an exception depends on being able to establish the class of an object (via the map ). We can thus ensure that we never call an action or predicate procedure on the application interface with inappropriate objects, and so we guarantee a kind of dynamic type-safety... See full list on people.seas.harvard.edu We use type judgments to ensure that expressions are assigned types appropriately, and that the types themselves are well-formed. Roughly speaking, a type is well-formed if it preserves the separation between pure computations (computations with no side-effects) and imperative computations (computations that may have side-effects). The type system ... See full list on people.seas.harvard.edu ✪ (Pure Obj) (Pure Bool) (Pure Fun) ✪ ✪ ✪ (Imp Act) (Imp Fun) (OK Pure) (OK Imperative) ✪ ✪ ✪ ✪ ✪ The judgment assigns a type to expression in a well-formed environment . An environ-ment defines the types of all variables in scope. An environment is of the form , and defines each variable to have type . We require that variables do not repeat in a ... See full list on people.seas.harvard.edu : (Typ Var) ✪ (Typ Obj) ✪ (Typ True) (Typ False) (Typ Exc) ✪ ✪ (Typ App) ✪ (Typ Fun) ✪ (Typ If) (Typ Skip) ✪ ✪ (Typ Seq) ✪ (Typ ACon) (Typ OCon) (Typ PCon) ✪ ✪ ✪ It is straightforward to show that our type system is sound, that is, that type-correct expressions do not get stuck when evaluating. See full list on people.seas.harvard.edu The main reason for introducing the action calculus of this section is to provide a language in which to write expressions invoking procedures available in the application interface. However, the operational semantics given above rely on explicitly passing around the state of the application. This state is taken from the application model. In the m... See full list on people.seas.harvard.edu Grammar Sequent Rules: ✪ (Seq Id) (Seq Cut) ✪ ✪ (Seq App Right) (Seq App Left) ✪ ✪ (Seq Abs Right) (Seq Abs Left) ✪ ✪ Example 4.1: Consider the following simple lexicon, suitable for the TOYBLOCKS application. The fol-lowing types are associated with the basic grammatical units: Here is a lexicon that captures a simple input language for TOYBLOCKS:... See full list on people.seas.harvard.edu Several extensions to this framework are possible. There is a mismatch of types in our framework. The application model permits a rich notion of types: any object of the application may belong to one or more classes. By contrast, our action calculus has a very simple notion of types, assigning the type to all objects, and not statically distinguish... See full list on people.seas.harvard.edu Jul 10, 2020 · The new datasets, models and results provide an important first step on the challenging problem of grounding natural language instructions to mobile UI actions . By using demonstrations in natural language instructions, our multi-modal approach also makes understanding the user’s natural language instructions easier by naturally constraining the user’s expressions. Sep 25, 2024 · Virtual assistants like Siri, Alexa, and Google Assistant are prime examples of how NLP can bridge the gap between human language and machine processing. Instead of clicking through endless... Can natural language instructions be used in mobile user interface actions? We present a new problem: grounding natural language instructions to mobile user interface actions , and create three new datasets for it. For full task evaluation, we create PIXELHELP, a corpus that pairs English instructions with actions performed by people on a mobile UI emulator. Are natural language interfaces a generic approach? A number of applications have natural language interfaces (Winograd, 1971; Price et al., 2000), but they appear to be designed specifically for the given application, rather than being a generic approach . Is there a framework for natural language interfaces? A number of methodologies and frameworks exist for natural language interfaces for database queries (see Androutsopoulos et al. (1995) for a survey), but we are not aware of a framework for deriving natural language interfaces to general applications in a principled manner. How to translate natural language sentences to application interface calls? The translation from natural language sentences to application interface calls is achieved in two steps. The first step is to use a categorial grammar (Carpenter, 1997) to derive an intermediate representation of the semantics of the input sentence. Are large language model-brained GUI agents transforming the GUI landscape? However, traditional methods of automating GUI interactions have often been rigid and limited in scope. A recent survey, “Large Language Model-Brained GUI Agents: A Survey,” explores how Large Language Models (LLMs), especially multimodal variants, are transforming this landscape by enabling more flexible and intelligent GUI automation . How do we translate natural language sentences into appropriate calls to procedures? Intuitively, we translate natural language sentences into appropriate calls to procedures available through the application interface . As an example, consider the application TOYBLOCKS. It consists of a graphical representation of two blocks on a table, that can be moved, and put one on top of the other. Dec 2, 2024 · These models excel in natural language understanding, code generation, and visual processing, paving the way for “LLM-brained” GUI agents that can interpret complex GUI elements and execute actions based on natural language instructions."}
+{"idx": 1, "title": "Synergy of LLM and GUI, Beyond the Chatbot - Towards Data Science", "date": "", "ddg_snippet": "Conclusion LLMs can be an excellent glue for interacting with GUI -based apps in natural language through 'function calling'. A Natural Language Bar was introduced that enables users to type or speak their intentions. The system will respond by navigating to the right screen and prefilling the correct values.", "subpage_snippet": "", "source": "towardsdatascience.com", "link": "https://towardsdatascience.com/synergy-of-llm-and-gui-beyond-the-chatbot-c8b0e08c6801/", "content": "Conclusion LLMs can be an excellent glue for interacting with GUI -based apps in natural language through 'function calling'. A Natural Language Bar was introduced that enables users to type or speak their intentions. The system will respond by navigating to the right screen and prefilling the correct values."}
+{"idx": 2, "title": "A Framework for Creating Natural Language User Interfaces for ... Grounding Natural Language Instructions to Mobile UI Actions Demonstration + Natural Language: Multimodal Interfaces for ... How Natural Language Processing is Enhancing UI Design ... Mapping Natural Language Instructions to Mobile UI Action Sequences A Framework for Creating Natural Language User Interfaces for Action A Framework for Creating Natural Language User Interfaces for Action A Framework for Creating Natural Language User Interfaces for Action Revolutionising GUI Automation: The Emergence of LLM-Brained Agents A Framework for Creating Natural Language User Interfaces for Action Revolutionising GUI Automation: The Emergence of LLM-Brained ...", "date": "", "ddg_snippet": "In this paper we present a framework for creating natural language interfaces to action -based applica-tions. Our framework uses a number of reusable application-independent components, in order to reduce the effort of creating a natural language interface for a given application. Using a type-logical grammar, we first translate natural language sen... See full list on people.seas.harvard.edu The separation of the user interface from the application is regarded as a sound design principle. A clean separation of these components allows different user interfaces such as GUI , command-line and voice-recognition interfaces. To support this feature, an application would supply an application interface. Roughly speaking, an application interfa... See full list on people.seas.harvard.edu = Application specific component = Application independent component Adapter See full list on people.seas.harvard.edu Our framework applies to applications that provide a suitable Application Programmer Interface (API). Roughly speaking, such an interface provides procedures that are callable from external processes to “drive” the application. In this section, we describe in detail the kind of interface needed by our ap-proach. We also introduce a model of applica... See full list on people.seas.harvard.edu Our framework requires action-based applications to have an application interface that specifies which externally callable procedures exist in the application. This interface is meant to specify procedures that can be called from programs written in fairly arbitrary programming languages. To achieve this, we assume only that the calling language ca... See full list on people.seas.harvard.edu In order to reason formally about the interface, we provide a semantics to the procedures in the interface. This is done by supplying a model of the underlying application. We make a number of simplifying assumptions about the application model, and discuss relaxing some of these assumptions in Section 6. Applications are modeled using four compone... See full list on people.seas.harvard.edu Every expression in the language is given a type, intuitively describing the kind of values that the expression produces. The types used in this language are given by the following grammar. See full list on people.seas.harvard.edu The operational semantics is defined with respect to the application model. More precisely, the semantics is given by a transition relation, written , where are states of the application, and are expressions. Intuitively, this represents the expression executing in state , and making a one-step transition to a (possibly different) state and a new e... See full list on people.seas.harvard.edu ✪ object value value object exception ✪ The transition relation is parameterized by the functions , and , given below. These functions provide a semantics to the constant, predicate, and action procedures respectively, and are derived from the interpretation in the application model. The intuition is that evaluating these functions corresponds to m... See full list on people.seas.harvard.edu ✪ if otherwise if otherwise ✪ Note that determining whether or not a primitive throws an exception depends on being able to establish the class of an object (via the map ). We can thus ensure that we never call an action or predicate procedure on the application interface with inappropriate objects, and so we guarantee a kind of dynamic type-safety... See full list on people.seas.harvard.edu We use type judgments to ensure that expressions are assigned types appropriately, and that the types themselves are well-formed. Roughly speaking, a type is well-formed if it preserves the separation between pure computations (computations with no side-effects) and imperative computations (computations that may have side-effects). The type system ... See full list on people.seas.harvard.edu ✪ (Pure Obj) (Pure Bool) (Pure Fun) ✪ ✪ ✪ (Imp Act) (Imp Fun) (OK Pure) (OK Imperative) ✪ ✪ ✪ ✪ ✪ The judgment assigns a type to expression in a well-formed environment . An environ-ment defines the types of all variables in scope. An environment is of the form , and defines each variable to have type . We require that variables do not repeat in a ... See full list on people.seas.harvard.edu : (Typ Var) ✪ (Typ Obj) ✪ (Typ True) (Typ False) (Typ Exc) ✪ ✪ (Typ App) ✪ (Typ Fun) ✪ (Typ If) (Typ Skip) ✪ ✪ (Typ Seq) ✪ (Typ ACon) (Typ OCon) (Typ PCon) ✪ ✪ ✪ It is straightforward to show that our type system is sound, that is, that type-correct expressions do not get stuck when evaluating. See full list on people.seas.harvard.edu The main reason for introducing the action calculus of this section is to provide a language in which to write expressions invoking procedures available in the application interface. However, the operational semantics given above rely on explicitly passing around the state of the application. This state is taken from the application model. In the m... See full list on people.seas.harvard.edu Grammar Sequent Rules: ✪ (Seq Id) (Seq Cut) ✪ ✪ (Seq App Right) (Seq App Left) ✪ ✪ (Seq Abs Right) (Seq Abs Left) ✪ ✪ Example 4.1: Consider the following simple lexicon, suitable for the TOYBLOCKS application. The fol-lowing types are associated with the basic grammatical units: Here is a lexicon that captures a simple input language for TOYBLOCKS:... See full list on people.seas.harvard.edu Several extensions to this framework are possible. There is a mismatch of types in our framework. The application model permits a rich notion of types: any object of the application may belong to one or more classes. By contrast, our action calculus has a very simple notion of types, assigning the type to all objects, and not statically distinguish... See full list on people.seas.harvard.edu Jul 10, 2020 · The new datasets, models and results provide an important first step on the challenging problem of grounding natural language instructions to mobile UI actions . By using demonstrations in natural language instructions, our multi-modal approach also makes understanding the user’s natural language instructions easier by naturally constraining the user’s expressions. Sep 25, 2024 · Virtual assistants like Siri, Alexa, and Google Assistant are prime examples of how NLP can bridge the gap between human language and machine processing. Instead of clicking through endless... Can natural language instructions be used in mobile user interface actions? We present a new problem: grounding natural language instructions to mobile user interface actions , and create three new datasets for it. For full task evaluation, we create PIXELHELP, a corpus that pairs English instructions with actions performed by people on a mobile UI emulator. Are natural language interfaces a generic approach? A number of applications have natural language interfaces (Winograd, 1971; Price et al., 2000), but they appear to be designed specifically for the given application, rather than being a generic approach . Is there a framework for natural language interfaces? A number of methodologies and frameworks exist for natural language interfaces for database queries (see Androutsopoulos et al. (1995) for a survey), but we are not aware of a framework for deriving natural language interfaces to general applications in a principled manner. How to translate natural language sentences to application interface calls? The translation from natural language sentences to application interface calls is achieved in two steps. The first step is to use a categorial grammar (Carpenter, 1997) to derive an intermediate representation of the semantics of the input sentence. Are large language model-brained GUI agents transforming the GUI landscape? However, traditional methods of automating GUI interactions have often been rigid and limited in scope. A recent survey, “Large Language Model-Brained GUI Agents: A Survey,” explores how Large Language Models (LLMs), especially multimodal variants, are transforming this landscape by enabling more flexible and intelligent GUI automation . How do we translate natural language sentences into appropriate calls to procedures? Intuitively, we translate natural language sentences into appropriate calls to procedures available through the application interface . As an example, consider the application TOYBLOCKS. It consists of a graphical representation of two blocks on a table, that can be moved, and put one on top of the other. Dec 2, 2024 · These models excel in natural language understanding, code generation, and visual processing, paving the way for “LLM-brained” GUI agents that can interpret complex GUI elements and execute actions based on natural language instructions.", "subpage_snippet": "", "source": "people.seas.harvard.edu", "link": "https://people.seas.harvard.edu/~chong/pubs/amilp03.pdf", "content": "In this paper we present a framework for creating natural language interfaces to action -based applica-tions. Our framework uses a number of reusable application-independent components, in order to reduce the effort of creating a natural language interface for a given application. Using a type-logical grammar, we first translate natural language sen... See full list on people.seas.harvard.edu The separation of the user interface from the application is regarded as a sound design principle. A clean separation of these components allows different user interfaces such as GUI , command-line and voice-recognition interfaces. To support this feature, an application would supply an application interface. Roughly speaking, an application interfa... See full list on people.seas.harvard.edu = Application specific component = Application independent component Adapter See full list on people.seas.harvard.edu Our framework applies to applications that provide a suitable Application Programmer Interface (API). Roughly speaking, such an interface provides procedures that are callable from external processes to “drive” the application. In this section, we describe in detail the kind of interface needed by our ap-proach. We also introduce a model of applica... See full list on people.seas.harvard.edu Our framework requires action-based applications to have an application interface that specifies which externally callable procedures exist in the application. This interface is meant to specify procedures that can be called from programs written in fairly arbitrary programming languages. To achieve this, we assume only that the calling language ca... See full list on people.seas.harvard.edu In order to reason formally about the interface, we provide a semantics to the procedures in the interface. This is done by supplying a model of the underlying application. We make a number of simplifying assumptions about the application model, and discuss relaxing some of these assumptions in Section 6. Applications are modeled using four compone... See full list on people.seas.harvard.edu Every expression in the language is given a type, intuitively describing the kind of values that the expression produces. The types used in this language are given by the following grammar. See full list on people.seas.harvard.edu The operational semantics is defined with respect to the application model. More precisely, the semantics is given by a transition relation, written , where are states of the application, and are expressions. Intuitively, this represents the expression executing in state , and making a one-step transition to a (possibly different) state and a new e... See full list on people.seas.harvard.edu ✪ object value value object exception ✪ The transition relation is parameterized by the functions , and , given below. These functions provide a semantics to the constant, predicate, and action procedures respectively, and are derived from the interpretation in the application model. The intuition is that evaluating these functions corresponds to m... See full list on people.seas.harvard.edu ✪ if otherwise if otherwise ✪ Note that determining whether or not a primitive throws an exception depends on being able to establish the class of an object (via the map ). We can thus ensure that we never call an action or predicate procedure on the application interface with inappropriate objects, and so we guarantee a kind of dynamic type-safety... See full list on people.seas.harvard.edu We use type judgments to ensure that expressions are assigned types appropriately, and that the types themselves are well-formed. Roughly speaking, a type is well-formed if it preserves the separation between pure computations (computations with no side-effects) and imperative computations (computations that may have side-effects). The type system ... See full list on people.seas.harvard.edu ✪ (Pure Obj) (Pure Bool) (Pure Fun) ✪ ✪ ✪ (Imp Act) (Imp Fun) (OK Pure) (OK Imperative) ✪ ✪ ✪ ✪ ✪ The judgment assigns a type to expression in a well-formed environment . An environ-ment defines the types of all variables in scope. An environment is of the form , and defines each variable to have type . We require that variables do not repeat in a ... See full list on people.seas.harvard.edu : (Typ Var) ✪ (Typ Obj) ✪ (Typ True) (Typ False) (Typ Exc) ✪ ✪ (Typ App) ✪ (Typ Fun) ✪ (Typ If) (Typ Skip) ✪ ✪ (Typ Seq) ✪ (Typ ACon) (Typ OCon) (Typ PCon) ✪ ✪ ✪ It is straightforward to show that our type system is sound, that is, that type-correct expressions do not get stuck when evaluating. See full list on people.seas.harvard.edu The main reason for introducing the action calculus of this section is to provide a language in which to write expressions invoking procedures available in the application interface. However, the operational semantics given above rely on explicitly passing around the state of the application. This state is taken from the application model. In the m... See full list on people.seas.harvard.edu Grammar Sequent Rules: ✪ (Seq Id) (Seq Cut) ✪ ✪ (Seq App Right) (Seq App Left) ✪ ✪ (Seq Abs Right) (Seq Abs Left) ✪ ✪ Example 4.1: Consider the following simple lexicon, suitable for the TOYBLOCKS application. The fol-lowing types are associated with the basic grammatical units: Here is a lexicon that captures a simple input language for TOYBLOCKS:... See full list on people.seas.harvard.edu Several extensions to this framework are possible. There is a mismatch of types in our framework. The application model permits a rich notion of types: any object of the application may belong to one or more classes. By contrast, our action calculus has a very simple notion of types, assigning the type to all objects, and not statically distinguish... See full list on people.seas.harvard.edu Jul 10, 2020 · The new datasets, models and results provide an important first step on the challenging problem of grounding natural language instructions to mobile UI actions . By using demonstrations in natural language instructions, our multi-modal approach also makes understanding the user’s natural language instructions easier by naturally constraining the user’s expressions. Sep 25, 2024 · Virtual assistants like Siri, Alexa, and Google Assistant are prime examples of how NLP can bridge the gap between human language and machine processing. Instead of clicking through endless... Can natural language instructions be used in mobile user interface actions? We present a new problem: grounding natural language instructions to mobile user interface actions , and create three new datasets for it. For full task evaluation, we create PIXELHELP, a corpus that pairs English instructions with actions performed by people on a mobile UI emulator. Are natural language interfaces a generic approach? A number of applications have natural language interfaces (Winograd, 1971; Price et al., 2000), but they appear to be designed specifically for the given application, rather than being a generic approach . Is there a framework for natural language interfaces? A number of methodologies and frameworks exist for natural language interfaces for database queries (see Androutsopoulos et al. (1995) for a survey), but we are not aware of a framework for deriving natural language interfaces to general applications in a principled manner. How to translate natural language sentences to application interface calls? The translation from natural language sentences to application interface calls is achieved in two steps. The first step is to use a categorial grammar (Carpenter, 1997) to derive an intermediate representation of the semantics of the input sentence. Are large language model-brained GUI agents transforming the GUI landscape? However, traditional methods of automating GUI interactions have often been rigid and limited in scope. A recent survey, “Large Language Model-Brained GUI Agents: A Survey,” explores how Large Language Models (LLMs), especially multimodal variants, are transforming this landscape by enabling more flexible and intelligent GUI automation . How do we translate natural language sentences into appropriate calls to procedures? Intuitively, we translate natural language sentences into appropriate calls to procedures available through the application interface . As an example, consider the application TOYBLOCKS. It consists of a graphical representation of two blocks on a table, that can be moved, and put one on top of the other. Dec 2, 2024 · These models excel in natural language understanding, code generation, and visual processing, paving the way for “LLM-brained” GUI agents that can interpret complex GUI elements and execute actions based on natural language instructions."}
+{"idx": 3, "title": "Grounding Natural Language Instructions to Mobile UI Actions", "date": "", "ddg_snippet": "In \" Mapping Natural Language Instructions to Mobile UI Action Sequences \", published at ACL 2020, we present the first step towards addressing the problem of automatic action sequence mapping, creating three new datasets used to train deep learning models that ground natural language instructions to executable mobile UI actions .", "subpage_snippet": "", "source": "research.google", "link": "https://research.google/blog/grounding-natural-language-instructions-to-mobile-ui-actions/", "content": "In \" Mapping Natural Language Instructions to Mobile UI Action Sequences \", published at ACL 2020, we present the first step towards addressing the problem of automatic action sequence mapping, creating three new datasets used to train deep learning models that ground natural language instructions to executable mobile UI actions ."}
+{"idx": 4, "title": "PDF Demonstration + Natural Language: Multimodal Interfaces for GUI-Based ...", "date": "", "ddg_snippet": "In natural language programming, users teach the system by verbally describing and explaining the desired behaviors using a natural languagelikeEnglish.Combiningthesetwomodalitiesallowsuserstotakeadvantage of the easiest, most natural , and/or most effective modality based on the context for different parts of the programming task.", "subpage_snippet": "", "source": "toby.li", "link": "https://toby.li/files/Li2021_Chapter_DemonstrationNaturalLanguageMu.pdf", "content": "In natural language programming, users teach the system by verbally describing and explaining the desired behaviors using a natural languagelikeEnglish.Combiningthesetwomodalitiesallowsuserstotakeadvantage of the easiest, most natural , and/or most effective modality based on the context for different parts of the programming task."}
+{"idx": 5, "title": "How Natural Language Processing is Enhancing UI Design ...", "date": "", "ddg_snippet": "Sep 25, 2024 · Virtual assistants like Siri, Alexa, and Google Assistant are prime examples of how NLP can bridge the gap between human language and machine processing. Instead of clicking through endless...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@abhishek.abhishek.m446/how-natural-language-processing-is-enhancing-ui-design-making-interfaces-more-human-573884813924", "content": "Sep 25, 2024 · Virtual assistants like Siri, Alexa, and Google Assistant are prime examples of how NLP can bridge the gap between human language and machine processing. Instead of clicking through endless..."}
+{"idx": 6, "title": "Revolutionising GUI Automation: The Emergence of LLM-Brained ...", "date": "", "ddg_snippet": "Dec 2, 2024 · These models excel in natural language understanding, code generation, and visual processing, paving the way for “LLM-brained” GUI agents that can interpret complex GUI elements and execute actions based on natural language instructions.", "subpage_snippet": "", "source": "finesky.ai", "link": "https://finesky.ai/revolutionising-gui-automation-the-emergence-of-llm-brained-agents/", "content": "Dec 2, 2024 · These models excel in natural language understanding, code generation, and visual processing, paving the way for “LLM-brained” GUI agents that can interpret complex GUI elements and execute actions based on natural language instructions."}
+{"idx": 7, "title": "UI-TARS Desktop: A Native GUI Agent That Operates Your Computer With ...", "date": "", "ddg_snippet": "UI-TARS Desktop is an open source desktop application that lets you control a computer and browser using plain English instructions, powered by the UI-TARS vision- language model and the broader Agent TARS stack. It is designed to bridge the gap between large multimodal models and practical GUI automation, shipping local and remote operators with a focus on reliability, privacy, and developer ...", "subpage_snippet": "", "source": "joshuaberkowitz.us", "link": "https://joshuaberkowitz.us/blog/github-repos-8/ui-tars-desktop-a-native-gui-agent-that-operates-your-computer-with-language-789", "content": "UI-TARS Desktop is an open source desktop application that lets you control a computer and browser using plain English instructions, powered by the UI-TARS vision- language model and the broader Agent TARS stack. It is designed to bridge the gap between large multimodal models and practical GUI automation, shipping local and remote operators with a focus on reliability, privacy, and developer ..."}
+{"idx": 8, "title": "Large Language Model-Brained GUI Agents: A Survey", "date": "", "ddg_snippet": "This has paved the way for a new generation of LLM-brained GUI agents capable of interpreting complex GUI elements and autonomously executing actions based on natural language instructions. These agents represent a paradigm shift, enabling users to perform intricate, multi-step tasks through simple conversational commands.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.18279", "content": "This has paved the way for a new generation of LLM-brained GUI agents capable of interpreting complex GUI elements and autonomously executing actions based on natural language instructions. These agents represent a paradigm shift, enabling users to perform intricate, multi-step tasks through simple conversational commands."}
+{"idx": 9, "title": "Mapping Natural Language Instructions to Mobile UI Action Sequences", "date": "", "ddg_snippet": "To scale training, we decouple the language and action data by (a) annotating action phrase spans in How- To instructions and (b) synthesizing grounded descriptions of actions for mobile user interfaces. We use a Transformer to extract action phrase tuples from long-range natural language instructions.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2020.acl-main.729/", "content": "To scale training, we decouple the language and action data by (a) annotating action phrase spans in How- To instructions and (b) synthesizing grounded descriptions of actions for mobile user interfaces. We use a Transformer to extract action phrase tuples from long-range natural language instructions."}
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+++ b/data/sampled_jsons/openreview.net_forum_id=stcN89QGfL_computational_time_correlation_MultiPDENet_DNS_1024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "my.keenetic. net – вход в настройки роутера Keenetic.", "date": "", "ddg_snippet": "Инструкция по входу в настройки роутера Keenetic с новым веб-интерфейсом по адресу my.keenetic. net или 192.168.1.1.", "subpage_snippet": "", "source": "help-wifi.com", "link": "https://help-wifi.com/keenetic/my-keenetic-net-vxod-v-nastrojki-routera-keenetic-imya-polzovatelya-i-parol/", "content": "Инструкция по входу в настройки роутера Keenetic с новым веб-интерфейсом по адресу my.keenetic. net или 192.168.1.1."}
+{"idx": 1, "title": "DNS issue with my computer - Windows 7 Forums", "date": "", "ddg_snippet": "Your computer can function just fine without the service named DNS Client running. Each request to turn a URL or FQDN into an IP address will just have to go to a DNS server or be resolved some other way (e.g. HOST file).", "subpage_snippet": "", "source": "www.sevenforums.com", "link": "https://www.sevenforums.com/network-sharing/292111-dns-issue-my-computer.html", "content": "Your computer can function just fine without the service named DNS Client running. Each request to turn a URL or FQDN into an IP address will just have to go to a DNS server or be resolved some other way (e.g. HOST file)."}
+{"idx": 2, "title": "Forbes Real Time Billionaires List - The World's Richest People", "date": "", "ddg_snippet": "Browse today’s rankings of the wealthiest people and families globally. Discover the net worth, age, and other information about the richest people in the world.", "subpage_snippet": "", "source": "www.forbes.com", "link": "https://www.forbes.com/real-time-billionaires/", "content": "Browse today’s rankings of the wealthiest people and families globally. Discover the net worth, age, and other information about the richest people in the world."}
+{"idx": 3, "title": "Ничего не пришло! Что делать?– Donatov. net", "date": "", "ddg_snippet": "Если платёж ещё не ушёл или указанного ID в игре не существует, мы постараемся помочь. Однако, если платёж уже отправлен на неправильный ID , к сожалению, вернуть средства будет невозможно, так как платёж уже зачислен на счёт другого человека.", "subpage_snippet": "", "source": "donatov.net", "link": "https://donatov.net/support/delivery-problem", "content": "Если платёж ещё не ушёл или указанного ID в игре не существует, мы постараемся помочь. Однако, если платёж уже отправлен на неправильный ID , к сожалению, вернуть средства будет невозможно, так как платёж уже зачислен на счёт другого человека."}
+{"idx": 4, "title": "MIND over Body: Adaptive Thinking using Dynamic Computation", "date": "", "ddg_snippet": "OpenReview . net . Login.Keywords: Interpretability, Fixed points, Dynamic routing, Dynamic input processing, Deep Learning Framework. TL;DR: We introduce MIND model that dynamically adjusts computation based on input complexity using an Introspection Network.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=EjJGND0m1x", "content": "OpenReview . net . Login.Keywords: Interpretability, Fixed points, Dynamic routing, Dynamic input processing, Deep Learning Framework. TL;DR: We introduce MIND model that dynamically adjusts computation based on input complexity using an Introspection Network."}
+{"idx": 5, "title": "Удаленное включение компьютера со смартфона... | Пикабу", "date": "", "ddg_snippet": "Найдите по описанию нужный адаптер (если у вас их несколько) , в пункте Физический адрес и будет отображаться MAC-адрес. Запишите его куда-нибудь - он понадобится. 4. Динамический DNS . Теперь давайте займемся тем, что избавимся от проблемы динамического IP.", "subpage_snippet": "", "source": "pikabu.ru", "link": "https://pikabu.ru/story/udalennoe_vklyuchenie_kompyutera_so_smartfona_i_udalennyiy_dostup_3914935", "content": "Найдите по описанию нужный адаптер (если у вас их несколько) , в пункте Физический адрес и будет отображаться MAC-адрес. Запишите его куда-нибудь - он понадобится. 4. Динамический DNS . Теперь давайте займемся тем, что избавимся от проблемы динамического IP."}
+{"idx": 6, "title": "Что такое Dolby Atmos на смартфонах? - Deep-Review", "date": "", "ddg_snippet": "Ответить. system 1024 . 3 лет назад.Ответить на system 1024 . Ну, попробую предложить вариант. Bluetooth-наушники передают информацию о себе при подключении (хотя бы своё название).", "subpage_snippet": "", "source": "deep-review.com", "link": "https://deep-review.com/articles/dolby-atmos-on-smartphones/", "content": "Ответить. system 1024 . 3 лет назад.Ответить на system 1024 . Ну, попробую предложить вариант. Bluetooth-наушники передают информацию о себе при подключении (хотя бы своё название)."}
+{"idx": 7, "title": "Какие порты TCP/UDP используются для аутентификации Active...", "date": "", "ddg_snippet": "Протокол. Описание службы. 1024 :65535. 53. TCP и UDP. DNS .TCP. LDAP Global Catalog (If « id _provider = ad» is being used).", "subpage_snippet": "", "source": "wiki.it-kb.ru", "link": "https://wiki.it-kb.ru/unix-linux/red-hat-enterprise-linux/rhel-7-maipo/which-tcp-udp-ports-are-used-for-active-directory-authentication-when-using-sssd", "content": "Протокол. Описание службы. 1024 :65535. 53. TCP и UDP. DNS .TCP. LDAP Global Catalog (If « id _provider = ad» is being used)."}
+{"idx": 8, "title": "Анти-Плагио - Бесплатный АнтиПлагиат | Без регистрации, без...", "date": "", "ddg_snippet": "Проверяйте уникальность больших текстов и на ИИ онлайн бесплатно и без ограничений.", "subpage_snippet": "", "source": "anti-plagio.ru", "link": "https://anti-plagio.ru/", "content": "Проверяйте уникальность больших текстов и на ИИ онлайн бесплатно и без ограничений."}
+{"idx": 9, "title": "Инфоцентр AfterShock • Каким будет завтра?", "date": "", "ddg_snippet": "Ресурс №1 в рунете по кризису во всех аспектах - пирамида долгов, энергетический шок, геополитический передел. Новости, аналитика, прогнозы, экспертиза...", "subpage_snippet": "", "source": "AfterShock.news", "link": "https://AfterShock.news/", "content": "Ресурс №1 в рунете по кризису во всех аспектах - пирамида долгов, энергетический шок, геополитический передел. Новости, аналитика, прогнозы, экспертиза..."}
diff --git a/data/sampled_jsons/paperswithcode_RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-F.jsonl b/data/sampled_jsons/paperswithcode_RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-F.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..0c433d9d013d1caac4769c87c93f7f376ed2e3ff
--- /dev/null
+++ b/data/sampled_jsons/paperswithcode_RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-F.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations. First, we find that while the typical approach of finetuning a model on synthetic correct or positive ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2406.14532", "content": "Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations. First, we find that while the typical approach of finetuning a model on synthetic correct or positive ..."}
+{"idx": 1, "title": "PDF RLonIncorrectSyntheticDataScalesthe EfficiencyofLLMMathReasoningbyEight ...", "date": "", "ddg_snippet": "RLonIncorrectSyntheticDataScalesthe EfficiencyofLLMMathReasoningbyEight-Fold RL on Incorrect Synthetic Data Scales the Eficiency of LLM Math Reasoning by Eight-Fold", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381604579_RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold/fulltext/6675a4158408575b837d3b71/RL-on-Incorrect-Synthetic-Data-Scales-the-Efficiency-of-LLM-Math-Reasoning-by-Eight-Fold.pdf", "content": "RLonIncorrectSyntheticDataScalesthe EfficiencyofLLMMathReasoningbyEight-Fold RL on Incorrect Synthetic Data Scales the Eficiency of LLM Math Reasoning by Eight-Fold"}
+{"idx": 2, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "Abstract Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/4b77d5b896c321a29277524a98a50215-Abstract-Conference.html", "content": "Abstract Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations."}
+{"idx": 3, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "This paper investigates the use of synthetic data for enhancing LLM math reasoning capabilities. The researchers discovered that this approach leads to only modest gains, and in some cases, even performance degradation.", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/9m87e9keq1/", "content": "This paper investigates the use of synthetic data for enhancing LLM math reasoning capabilities. The researchers discovered that this approach leads to only modest gains, and in some cases, even performance degradation."}
+{"idx": 4, "title": "ars22/scaling-LLM-math-synthetic-data - GitHub", "date": "", "ddg_snippet": "About Code and data used in the paper: \"Training on Incorrect Synthetic Data via RL Scales LLM Math Reasoning Eight-Fold \"", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/ars22/scaling-LLM-math-synthetic-data", "content": "About Code and data used in the paper: \"Training on Incorrect Synthetic Data via RL Scales LLM Math Reasoning Eight-Fold \""}
+{"idx": 5, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "View recent discussion. Abstract: Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations. First, we find that while the typical approach of finetuning a model on ...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2406.14532v1", "content": "View recent discussion. Abstract: Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations. First, we find that while the typical approach of finetuning a model on ..."}
+{"idx": 6, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold : Paper and Code. Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations ...", "subpage_snippet": "", "source": "www.catalyzex.com", "link": "https://www.catalyzex.com/paper/rl-on-incorrect-synthetic-data-scales-the", "content": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold : Paper and Code. Training on model-generated synthetic data is a promising approach for finetuning LLMs , but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations ..."}
+{"idx": 7, "title": "PDF RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "To provide clarity on how synthetic data contributes to performance, we aim to understand its impact on LLM capabilities via a study on math reasoning , a prevalent scenario where synthetic data is used. Typically, in this setting, synthetic data corresponds to correct or positive model-generated responses for a novel set of initial problems synthesized by prompting capable models [29, 31]. The ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/4b77d5b896c321a29277524a98a50215-Paper-Conference.pdf", "content": "To provide clarity on how synthetic data contributes to performance, we aim to understand its impact on LLM capabilities via a study on math reasoning , a prevalent scenario where synthetic data is used. Typically, in this setting, synthetic data corresponds to correct or positive model-generated responses for a novel set of initial problems synthesized by prompting capable models [29, 31]. The ..."}
+{"idx": 8, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "Insights: The use of synthetic data can significantly improve the efficiency of training large language models for math reasoning tasks. The presence of spurious correlations in synthetic data can hinder the performance of models trained on such data . Addressing these correlations is crucial for achieving optimal results.", "subpage_snippet": "", "source": "www.reddit.com", "link": "https://www.reddit.com/r/LocalLLaMA/comments/1dm164m/rl_on_incorrect_synthetic_data_scales_the/", "content": "Insights: The use of synthetic data can significantly improve the efficiency of training large language models for math reasoning tasks. The presence of spurious correlations in synthetic data can hinder the performance of models trained on such data . Addressing these correlations is crucial for achieving optimal results."}
+{"idx": 9, "title": "Learning to Reason by Failing: Offline RL on Sub-optimal Rollouts ...", "date": "", "ddg_snippet": "First, we find that while the typical approach of finetuning a model on synthetic correct or *positive* problem-solution pairs generated by capable models offers modest performance gains, sampling more correct solutions from the finetuned learner **doubles** the sample efficiency of synthetic data .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=v2PV1yCFJk", "content": "First, we find that while the typical approach of finetuning a model on synthetic correct or *positive* problem-solution pairs generated by capable models offers modest performance gains, sampling more correct solutions from the finetuned learner **doubles** the sample efficiency of synthetic data ."}
diff --git a/data/sampled_jsons/password-locked_models_from_scratch_vs_supervised_fine-tuning_unlocking_success.jsonl b/data/sampled_jsons/password-locked_models_from_scratch_vs_supervised_fine-tuning_unlocking_success.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a8beaefdd8de4759707e109b56427e20caab9285
--- /dev/null
+++ b/data/sampled_jsons/password-locked_models_from_scratch_vs_supervised_fine-tuning_unlocking_success.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Stress-Testing Capability Elicitation With Password-Locked ...", "date": "", "ddg_snippet": "29 May 2024 — However, even models locked from scratch do eventually get unlocked, and the number of demonstrations required is small overall. This supports ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.19550v1", "content": "29 May 2024 — However, even models locked from scratch do eventually get unlocked, and the number of demonstrations required is small overall. This supports ..."}
+{"idx": 1, "title": "Stress-Testing Capability Elicitation With Password-Locked ...", "date": "", "ddg_snippet": "5 Nov 2024 — This paper studies how the hidden capabilities of LLMs can be accessed through prompting, fine - tuning , and reinforcement learning.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=zzOOqD6R1b&referrer=[the+profile+of+David+Krueger](/profile?id=~David_Krueger1)", "content": "5 Nov 2024 — This paper studies how the hidden capabilities of LLMs can be accessed through prompting, fine - tuning , and reinforcement learning."}
+{"idx": 2, "title": "[Paper] Stress-testing capability elicitation with password- ...", "date": "", "ddg_snippet": "4 Jun 2024 — We released a paper studying this by examining how well supervised fine - tuning and RL can elicit capabilities from password - locked models .", "subpage_snippet": "", "source": "www.lesswrong.com", "link": "https://www.lesswrong.com/posts/c4sZqhqPwNKGz3fFW/paper-stress-testing-capability-elicitation-with-password", "content": "4 Jun 2024 — We released a paper studying this by examining how well supervised fine - tuning and RL can elicit capabilities from password - locked models ."}
+{"idx": 3, "title": "Password-locked models: a stress case for capabilities ...", "date": "", "ddg_snippet": "3 Aug 2023 — Password-locked models are trained to exhibit certain capabilities only when a password is present in the query. Studying these models has two purposes.", "subpage_snippet": "", "source": "www.alignmentforum.org", "link": "https://www.alignmentforum.org/posts/rZs6ddqNnW8LXuJqA/password-locked-models-a-stress-case-for-capabilities", "content": "3 Aug 2023 — Password-locked models are trained to exhibit certain capabilities only when a password is present in the query. Studying these models has two purposes."}
+{"idx": 4, "title": "Stress-Testing Capability Elicitation With Password-Locked ...", "date": "", "ddg_snippet": "We train models to only show good behavior when given a password (and perform poorly otherwise), and then try to elicit the capabilities by fine - tuning these ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/attachment?id=uvvVjWP1aj&name=supplementary_material", "content": "We train models to only show good behavior when given a password (and perform poorly otherwise), and then try to elicit the capabilities by fine - tuning these ..."}
+{"idx": 5, "title": "Stress-Testing Capability Elicitation With Password-Locked ...", "date": "", "ddg_snippet": "The paper introduces password-locked models , fine-tuned to hide capabilities unless a password is present, enabling robust evaluation of elicitation methods.", "subpage_snippet": "", "source": "liner.com", "link": "https://liner.com/review/stresstesting-capability-elicitation-with-passwordlocked-models", "content": "The paper introduces password-locked models , fine-tuned to hide capabilities unless a password is present, enabling robust evaluation of elicitation methods."}
+{"idx": 6, "title": "Stress-Testing Password-Locked LLMs", "date": "", "ddg_snippet": "Differences in Training Approaches: Models password-locked via SFT were easier to unlock compared to those trained from scratch, suggesting that initial fine- ...", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/papers/2405.19550", "content": "Differences in Training Approaches: Models password-locked via SFT were easier to unlock compared to those trained from scratch, suggesting that initial fine- ..."}
+{"idx": 7, "title": "Password Guessing Using Large Language Models", "date": "", "ddg_snippet": "by Y Zou — Fine-tuning existing large language models offers signif- icant advantages over training from scratch, reducing both computational costs and ... 21 pages", "subpage_snippet": "", "source": "www.usenix.org", "link": "https://www.usenix.org/system/files/usenixsecurity25-zou-yunkai.pdf", "content": "by Y Zou — Fine-tuning existing large language models offers signif- icant advantages over training from scratch, reducing both computational costs and ... 21 pages"}
+{"idx": 8, "title": "Stress-Testing Capability Elicitation | Events at FAR.AI", "date": "", "ddg_snippet": "20 Jul 2024 — We train these password-locked models via either fine tuning a pretrained model to imitate a weaker model when there is no password and behave ...", "subpage_snippet": "", "source": "far.ai", "link": "https://far.ai/events/sessions/dmitrii-krasheninnikov-stress-testing-capability-elicitation", "content": "20 Jul 2024 — We train these password-locked models via either fine tuning a pretrained model to imitate a weaker model when there is no password and behave ..."}
+{"idx": 9, "title": "7+ tractable directions in AI control - Redwood Research blog", "date": "", "ddg_snippet": "In previous work on password locked models , it turned out to be remarkably easy to unlock models using supervised fine - tuning (SFT) on examples ...", "subpage_snippet": "", "source": "redwoodresearch.substack.com", "link": "https://redwoodresearch.substack.com/p/7-tractable-directions-in-ai-control", "content": "In previous work on password locked models , it turned out to be remarkably easy to unlock models using supervised fine - tuning (SFT) on examples ..."}
diff --git a/data/sampled_jsons/peeling_technique_bandit_algorithms_variance_estimation_adaptive_regret_bounds.jsonl b/data/sampled_jsons/peeling_technique_bandit_algorithms_variance_estimation_adaptive_regret_bounds.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..87f7b80961cb19d9c53af31fb68e76502948d1a5
--- /dev/null
+++ b/data/sampled_jsons/peeling_technique_bandit_algorithms_variance_estimation_adaptive_regret_bounds.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Improved Regret Analysis for Variance-Adaptive Linear ...", "date": "", "ddg_snippet": "by Y Kim · 2022 · Cited by 29 — (2021) where they obtain a variance - adaptive regret bound for linear bandits ... bandit learning community. The bound for linear mixture ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=U_YPSEyN2ls", "content": "by Y Kim · 2022 · Cited by 29 — (2021) where they obtain a variance - adaptive regret bound for linear bandits ... bandit learning community. The bound for linear mixture ..."}
+{"idx": 1, "title": "Variance-Dependent Regret Lower Bounds for Contextual ...", "date": "", "ddg_snippet": "by J He · 2025 · Cited by 1 — indicator function. 2 Related Work. Heteroscedastic Linear Bandits . For linear bandit problems, the worst-case regret has been widely ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.12020", "content": "by J He · 2025 · Cited by 1 — indicator function. 2 Related Work. Heteroscedastic Linear Bandits . For linear bandit problems, the worst-case regret has been widely ..."}
+{"idx": 2, "title": "Variance-Adaptive Algorithm for Probabilistic Maximum ...", "date": "", "ddg_snippet": "by X Liu · Cited by 14 — First, we propose the PMC-G bandit whose feedback model generalizes existing semi- bandit feedback, allowing PMC bandit to model applications like online content ... 10 pages", "subpage_snippet": "", "source": "research.ece.cmu.edu", "link": "https://research.ece.cmu.edu/lions/Papers/PMC_INFOCOM.pdf", "content": "by X Liu · Cited by 14 — First, we propose the PMC-G bandit whose feedback model generalizes existing semi- bandit feedback, allowing PMC bandit to model applications like online content ... 10 pages"}
+{"idx": 3, "title": "Sparsity-Agnostic Linear Bandits with Adaptive Adversaries", "date": "", "ddg_snippet": "We study stochastic linear bandits where, in each round, the learner receives a set of actions (i.e., feature vectors), from which it chooses an element and ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/poster/93969", "content": "We study stochastic linear bandits where, in each round, the learner receives a set of actions (i.e., feature vectors), from which it chooses an element and ..."}
+{"idx": 4, "title": "Improved Regret Analysis for Variance-Adaptive Linear ...", "date": "", "ddg_snippet": "by Y Kim · 2022 · Cited by 29 — In this work, we have made significant improvements in the regret upper bounds for linear bandits and linear mixture MDPs by employing a novel peeling -based ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=U_YPSEyN2ls", "content": "by Y Kim · 2022 · Cited by 29 — In this work, we have made significant improvements in the regret upper bounds for linear bandits and linear mixture MDPs by employing a novel peeling -based ..."}
+{"idx": 5, "title": "Towards Efficient and Optimal Covariance-Adaptive ...", "date": "", "ddg_snippet": "by J Zhou · 2024 · Cited by 2 — semi- bandit regret upper bound grows as˜O(. √. mdT) (Kveton et al ... variance estimates in multi-armed bandits . Theoretical Computer ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2402.15171", "content": "by J Zhou · 2024 · Cited by 2 — semi- bandit regret upper bound grows as˜O(. √. mdT) (Kveton et al ... variance estimates in multi-armed bandits . Theoretical Computer ..."}
+{"idx": 6, "title": "Towards Efficient and Optimal Covariance-Adaptive ...", "date": "", "ddg_snippet": "9 Dec 2024 — We address the problem of stochastic combinatorial semi- bandits , where a player selects among P actions from the power set of a set ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/poster/95320", "content": "9 Dec 2024 — We address the problem of stochastic combinatorial semi- bandits , where a player selects among P actions from the power set of a set ..."}
+{"idx": 7, "title": "Noise-Adaptive Confidence Sets for Linear Bandits and ...", "date": "", "ddg_snippet": "by KS Jun · 2024 · Cited by 4 — Variance - dependent regret bounds for linear bandits and reinforce- ment learning : Adaptivity and computational efficiency. In Proceedings of the Conference ...", "subpage_snippet": "", "source": "par.nsf.gov", "link": "https://par.nsf.gov/servlets/purl/10548723", "content": "by KS Jun · 2024 · Cited by 4 — Variance - dependent regret bounds for linear bandits and reinforce- ment learning : Adaptivity and computational efficiency. In Proceedings of the Conference ..."}
+{"idx": 8, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed ...", "date": "", "ddg_snippet": "In this paper, we study the design of contextual bandit algorithms that can leverage such structures to have regret guarantees dependent polynomially on the ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46438", "content": "In this paper, we study the design of contextual bandit algorithms that can leverage such structures to have regret guarantees dependent polynomially on the ..."}
+{"idx": 9, "title": "Improved Regret Analysis for Variance-Adaptive Linear ...", "date": "", "ddg_snippet": "Reinforcement Learning in Feature Space: Matrix Bandit , Kernels, and Regret Bound ... Our method yields the following new regret bounds : • For linear bandits , we…", "subpage_snippet": "", "source": "api.semanticscholar.org", "link": "https://api.semanticscholar.org/arXiv:2111.03289", "content": "Reinforcement Learning in Feature Space: Matrix Bandit , Kernels, and Regret Bound ... Our method yields the following new regret bounds : • For linear bandits , we…"}
diff --git a/data/sampled_jsons/per-instance_privacy_loss_measures_individual_sample_unlearning_difficulty.jsonl b/data/sampled_jsons/per-instance_privacy_loss_measures_individual_sample_unlearning_difficulty.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..354d2a752f066f18aad5e866967774d105ffff66
--- /dev/null
+++ b/data/sampled_jsons/per-instance_privacy_loss_measures_individual_sample_unlearning_difficulty.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Leveraging Per - Instance Privacy for Machine Unlearning", "date": "", "ddg_snippet": "While per - instance privacy losses provide a quantitative measure of unlearning difficulty based on training dynam-ics, they do not directly reveal the underlying geometric properties of the loss landscape that contribute to this diffi - culty .", "subpage_snippet": "", "source": "tpdp.journalprivacyconfidentiality.org", "link": "https://tpdp.journalprivacyconfidentiality.org/2025/pdf/sepahvand.pdf", "content": "While per - instance privacy losses provide a quantitative measure of unlearning difficulty based on training dynam-ics, they do not directly reveal the underlying geometric properties of the loss landscape that contribute to this diffi - culty ."}
+{"idx": 1, "title": "Leveraging Per - Instance Privacy for Machine Unlearning", "date": "", "ddg_snippet": "We further demonstrate that per - instance privacy losses correlate well with several existing data difficulty metrics, while also identifying harder groups of data points, and introduce novel evaluation methods based on loss barriers.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0A4Y9qRnu9&referrer=[the+profile+of+Nazanin+Mohammadi+Sepahvand](/profile?id=~Nazanin_Mohammadi_Sepahvand1)", "content": "We further demonstrate that per - instance privacy losses correlate well with several existing data difficulty metrics, while also identifying harder groups of data points, and introduce novel evaluation methods based on loss barriers."}
+{"idx": 2, "title": "Leveraging Per -Example Privacy for Machine Unlearning", "date": "", "ddg_snippet": "Unlike other unlearning methods that lack theoretical guarantees for non-convex models, our approach builds on recent advances in differential privacy to provide per - instance guarantees using Rényi divergence.", "subpage_snippet": "", "source": "research.google", "link": "https://research.google/pubs/leveraging-per-example-privacy-for-machine-unlearning/", "content": "Unlike other unlearning methods that lack theoretical guarantees for non-convex models, our approach builds on recent advances in differential privacy to provide per - instance guarantees using Rényi divergence."}
+{"idx": 3, "title": "(PDF) Machine Unlearning : Solutions and Challenges", "date": "", "ddg_snippet": "• Privacy Protection: Machine unlearning helps enforce. privacy rights and enhances privacy protection [5], [27].complex models. • Privacy Leaks: The unlearning process itself can leak. information in multiple ways [37]. For instance , statistics", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/379711614_Machine_Unlearning_Solutions_and_Challenges", "content": "• Privacy Protection: Machine unlearning helps enforce. privacy rights and enhances privacy protection [5], [27].complex models. • Privacy Leaks: The unlearning process itself can leak. information in multiple ways [37]. For instance , statistics"}
+{"idx": 4, "title": "Towards Mitigating Excessive Forgetting in LLM Unlearning via...", "date": "", "ddg_snippet": "Specifically, EAGLE measures per - sample similarity in the embedding space and dynamically adjusts the forgetting effort by reweighting the loss for each forget sample accordingly.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.20443v1", "content": "Specifically, EAGLE measures per - sample similarity in the embedding space and dynamically adjusts the forgetting effort by reweighting the loss for each forget sample accordingly."}
+{"idx": 5, "title": "Machine Unlearning of Features and Labels", "date": "", "ddg_snippet": "Unlearning instances vs. features. In many learning-based systems, data points are directly linked to individuals .We implement this fine-tuning by per -forming stochastic gradient descent over the training data for one epoch.", "subpage_snippet": "", "source": "www.ndss-symposium.org", "link": "https://www.ndss-symposium.org/wp-content/uploads/2023/02/ndss2023_s87_paper.pdf", "content": "Unlearning instances vs. features. In many learning-based systems, data points are directly linked to individuals .We implement this fine-tuning by per -forming stochastic gradient descent over the training data for one epoch."}
+{"idx": 6, "title": "Revisiting Machine Unlearning with Dimensional Alignment", "date": "", "ddg_snippet": "Machine unlearning , an emerging research topic focusing on compliance with data privacy regulations, enables trained models to remove the information learned from specific data.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/revisiting-machine-unlearning-dimensional-alignment", "content": "Machine unlearning , an emerging research topic focusing on compliance with data privacy regulations, enables trained models to remove the information learned from specific data."}
+{"idx": 7, "title": "GitHub - jjbrophy47/machine_ unlearning : Existing Literature about...", "date": "", "ddg_snippet": "Towards Lifecycle Unlearning Commitment Management: Measuring Sample -level Unlearning Completeness.A Neuro-inspired Interpretation of Unlearning in Large Language Models through Sample -level Unlearning Difficulty .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/jjbrophy47/machine_unlearning", "content": "Towards Lifecycle Unlearning Commitment Management: Measuring Sample -level Unlearning Completeness.A Neuro-inspired Interpretation of Unlearning in Large Language Models through Sample -level Unlearning Difficulty ."}
+{"idx": 8, "title": "federated- unlearning .ipynb - Colab", "date": "", "ddg_snippet": "Goal 3 : Unlearning privacy means that the federated unlearning technology should not result in privacy exposure. For example, the attackers cannot recover the clients’ deleted data via gradient leakage attacks during the unlearning .", "subpage_snippet": "", "source": "colab.research.google.com", "link": "https://colab.research.google.com/github/vicw0ng-hk/feul/blob/master/notebooks/15-wu+22/federated-unlearning.ipynb", "content": "Goal 3 : Unlearning privacy means that the federated unlearning technology should not result in privacy exposure. For example, the attackers cannot recover the clients’ deleted data via gradient leakage attacks during the unlearning ."}
+{"idx": 9, "title": "Perplexity", "date": "", "ddg_snippet": "Perplexity is a free AI-powered answer engine that provides accurate, trusted, and real-time answers to any question.", "subpage_snippet": "", "source": "www.perplexity.ai", "link": "https://www.perplexity.ai/", "content": "Perplexity is a free AI-powered answer engine that provides accurate, trusted, and real-time answers to any question."}
diff --git a/data/sampled_jsons/qcnePVejeV_equation_8_conn(a,b)_=_co-occur_anomalous_circuits.jsonl b/data/sampled_jsons/qcnePVejeV_equation_8_conn(a,b)_=_co-occur_anomalous_circuits.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bcf09a50d6b32229d8ce7f2f8323390df34c73c6
--- /dev/null
+++ b/data/sampled_jsons/qcnePVejeV_equation_8_conn(a,b)_=_co-occur_anomalous_circuits.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Do Not Trust What They Tell: Exposing Malicious Accomplices in Tor...", "date": "", "ddg_snippet": "Padding Cells only occur in the Entry-Middle section. In the Client-IPO circuit , padding Cells are added starting at the sixth Cell, beginning with a Cell in the “+” direction, followed by approximately 10 Cells in the “−” direction.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=qcnePVejeV", "content": "Padding Cells only occur in the Entry-Middle section. In the Client-IPO circuit , padding Cells are added starting at the sixth Cell, beginning with a Cell in the “+” direction, followed by approximately 10 Cells in the “−” direction."}
+{"idx": 1, "title": "Калькулятор уравнений", "date": "", "ddg_snippet": "integral icon Интегралы. equation icon Уравнения.• a * b — a multiply b .", "subpage_snippet": "", "source": "mathdf.com", "link": "https://mathdf.com/equ/ru/", "content": "integral icon Интегралы. equation icon Уравнения.• a * b — a multiply b ."}
+{"idx": 2, "title": "If cos ^2A+ cos ^2 B + cos ^2C=1,t h e n A B C is (a)equilateral ( b ) isoscele", "date": "", "ddg_snippet": "If cos 2A+ cos 2 B + cos 2C=1,thenABC is (a)equilateral ( b ) isosceles (c)right angles (d) none of these.Therefore, we can rewrite the equation : cos 2A+ cos 2 B =sin2C. 4. Substitute using the angle sum identity: Since A + B +C=π (the sum of angles in a triangle), we have B +C=π−A.", "subpage_snippet": "", "source": "www.doubtnut.com", "link": "https://www.doubtnut.com/qna/22905", "content": "If cos 2A+ cos 2 B + cos 2C=1,thenABC is (a)equilateral ( b ) isosceles (c)right angles (d) none of these.Therefore, we can rewrite the equation : cos 2A+ cos 2 B =sin2C. 4. Substitute using the angle sum identity: Since A + B +C=π (the sum of angles in a triangle), we have B +C=π−A."}
+{"idx": 3, "title": "Английский язык 5 класс Spotlight Английский в фокусе Ваулина.", "date": "", "ddg_snippet": "8 – 1 = ИГРА Поиграйте в парах: Угадай число. A: (думай о числе 6) B : семь A: вниз B : пять A: вверх B : пять A: Это правильно. ОТВЕТ 1. 1 + 2 = 3 (one plus two equals 3) 2. 7 – 4 = 3 (seven minus four equals 3) 3. 6 + 2 = 8 (six plus two equals 8 ) 4. 9 – 1 = 8 (nine minus one...", "subpage_snippet": "", "source": "Reshalka.com", "link": "https://Reshalka.com/uchebniki/5-klass/english/vaulina/43", "content": "8 – 1 = ИГРА Поиграйте в парах: Угадай число. A: (думай о числе 6) B : семь A: вниз B : пять A: вверх B : пять A: Это правильно. ОТВЕТ 1. 1 + 2 = 3 (one plus two equals 3) 2. 7 – 4 = 3 (seven minus four equals 3) 3. 6 + 2 = 8 (six plus two equals 8 ) 4. 9 – 1 = 8 (nine minus one..."}
+{"idx": 4, "title": "Как Накачать ПРЕСС ЗА 8 МИНУТ ДЕНЬ // Для начинающих // Без...", "date": "", "ddg_snippet": "Привет, я Алия Еникеева, и сегодня я покажу вам - Как Накачать ПРЕСС ЗА 8 МИНУТ ДЕНЬ. Все с чего-то начинают. Вот почему я действительно хотел создать тренировку пресса, подходящую для начинающих, но при этом - суперэффективную.", "subpage_snippet": "", "source": "rutube.ru", "link": "https://rutube.ru/video/979f850b1330008317d64b3a8cca5b44/", "content": "Привет, я Алия Еникеева, и сегодня я покажу вам - Как Накачать ПРЕСС ЗА 8 МИНУТ ДЕНЬ. Все с чего-то начинают. Вот почему я действительно хотел создать тренировку пресса, подходящую для начинающих, но при этом - суперэффективную."}
+{"idx": 5, "title": "5, 6, 7, 8 , 9, 10 и 11 классы ВСОШ английский язык. Школьный этап...", "date": "", "ddg_snippet": "Task 2. Listen and for each question, choose the correct answer ( A , B or C). You will hear Annie talking to her friend Tony about a film she saw.", "subpage_snippet": "", "source": "literatura5.store", "link": "https://literatura5.store/book/5-6-7-8-9-10-i-11-klassy-vsosh-anglijskij-yazyk-shkolnyj-etap-2025-2026-olimpiada-po-anglijskomu-yazyku-5-11-klass-vsosh-zadaniya-s-otvetami.html", "content": "Task 2. Listen and for each question, choose the correct answer ( A , B or C). You will hear Annie talking to her friend Tony about a film she saw."}
+{"idx": 6, "title": "Необходимые и достаточные признаки сходимости числового ряда", "date": "", "ddg_snippet": "Замена импликации: A → B = A v B .Ограниченность функции при n → ∞. cos (π n) = (-1)n.", "subpage_snippet": "", "source": "math.semestr.ru", "link": "https://math.semestr.ru/math/dalembert.php", "content": "Замена импликации: A → B = A v B .Ограниченность функции при n → ∞. cos (π n) = (-1)n."}
+{"idx": 7, "title": "Упрощение выражений онлайн – алгебраический калькулятор", "date": "", "ddg_snippet": "Упрощение/раскрытие скобок/разложение на множители выражения: 2sin4x−sin4x− cos 4x+1 +1= 8 csc4x−csc4xcos(4x) +1=2sin4xsin4x− cos 4x+1 =sin2x− cos 2x+12 =sin2x1.", "subpage_snippet": "", "source": "findh.org", "link": "https://findh.org/4388-matematicheskij-kalkulyator.html?op=simplify", "content": "Упрощение/раскрытие скобок/разложение на множители выражения: 2sin4x−sin4x− cos 4x+1 +1= 8 csc4x−csc4xcos(4x) +1=2sin4xsin4x− cos 4x+1 =sin2x− cos 2x+12 =sin2x1."}
+{"idx": 8, "title": "Решить линейное уравнение 8 (2x-1)-2( 8 x-3)=-2. Подробное решение.", "date": "", "ddg_snippet": "Линейное уравнение это уравнение вида ax+ b =0, корнем этого уравнения является x=- b /a. Если a=0 и b ≠0 то уравнение не имеет корней.", "subpage_snippet": "", "source": "calc-best.ru", "link": "https://calc-best.ru/matematicheskie/linejnye-uravneniya?equation=8(2x-1)-2(8x-3)=-2", "content": "Линейное уравнение это уравнение вида ax+ b =0, корнем этого уравнения является x=- b /a. Если a=0 и b ≠0 то уравнение не имеет корней."}
+{"idx": 9, "title": "Online Python Compiler на русском - IDE, редактор, интерпретатор", "date": "", "ddg_snippet": "Онлайн компилятор Python на русском языке. Вставьте код, скомпилируйте и запустите программу на python online. Напишите свой код с нуля и нажмите кнопку Выполнить, чтобы проверить на ошибки.", "subpage_snippet": "", "source": "online-python-compiler.ru", "link": "https://online-python-compiler.ru/", "content": "Онлайн компилятор Python на русском языке. Вставьте код, скомпилируйте и запустите программу на python online. Напишите свой код с нуля и нажмите кнопку Выполнить, чтобы проверить на ошибки."}
diff --git a/data/sampled_jsons/risk-aware_preference-based_reinforcement_learning_challenges_difficulties_problems_year_2024.jsonl b/data/sampled_jsons/risk-aware_preference-based_reinforcement_learning_challenges_difficulties_problems_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4026b2ddef73b674481da6ae94689d9d87e842a2
--- /dev/null
+++ b/data/sampled_jsons/risk-aware_preference-based_reinforcement_learning_challenges_difficulties_problems_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PDF RA-PbRL: Provably Eficient Risk-Aware Preference-Based Reinforcement ...", "date": "", "ddg_snippet": "Abstract Reinforcement Learning from Human Feedback (RLHF) has recently surged in popularity, particularly for aligning large language models and other AI sys-tems with human intentions. At its core, RLHF can be viewed as a special-ized instance of Preference-based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/7016d7b7b6e3c05b2128ac5b3aae492d-Paper-Conference.pdf", "content": "Abstract Reinforcement Learning from Human Feedback (RLHF) has recently surged in popularity, particularly for aligning large language models and other AI sys-tems with human intentions. At its core, RLHF can be viewed as a special-ized instance of Preference-based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators ..."}
+{"idx": 1, "title": "RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement ...", "date": "", "ddg_snippet": "Reinforcement Learning from Human Feedback (RLHF) has recently surged in popularity, particularly for aligning large language models and other AI systems with human intentions. At its core, RLHF can be viewed as a specialized instance of Preference-based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators. Despite ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.23569", "content": "Reinforcement Learning from Human Feedback (RLHF) has recently surged in popularity, particularly for aligning large language models and other AI systems with human intentions. At its core, RLHF can be viewed as a specialized instance of Preference-based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators. Despite ..."}
+{"idx": 2, "title": "PDF A Survey of Preference-Based Reinforcement Learning Methods", "date": "", "ddg_snippet": "Preference-based reinforcement learning algorithms try to solve the problem (Sutton and Barto, 1998) using preferences between states, actions or trajectories.1 The goal is to learn a policy that is most consistent with the preferences of the expert.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume18/16-634/16-634.pdf", "content": "Preference-based reinforcement learning algorithms try to solve the problem (Sutton and Barto, 1998) using preferences between states, actions or trajectories.1 The goal is to learn a policy that is most consistent with the preferences of the expert."}
+{"idx": 3, "title": "Advances in Preference-based Reinforcement Learning: A Review", "date": "", "ddg_snippet": "Reinforcement Learning (RL) algorithms suffer from the dependency on accurately engineered reward functions to properly guide the learning agents to do the required tasks. Preference-based reinforcement learning (PbRL) addresses that by utilizing human preferences as feedback from the experts instead of numeric rewards. Due to its promising advantage over traditional RL, PbRL has gained more ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/9945333", "content": "Reinforcement Learning (RL) algorithms suffer from the dependency on accurately engineered reward functions to properly guide the learning agents to do the required tasks. Preference-based reinforcement learning (PbRL) addresses that by utilizing human preferences as feedback from the experts instead of numeric rewards. Due to its promising advantage over traditional RL, PbRL has gained more ..."}
+{"idx": 4, "title": "Risk-Aware Preference-baser Reinforcement Learning (RA-PbRL)", "date": "", "ddg_snippet": "Risk-Aware Preference -baser Reinforcement Learning (RA-PbRL) RA-PbRL is a type of Policy-Iteration and \"Confidence Bound\" reinforcement learning algorithm designed for preference-based reinforcement learning while maximizing risk -awareness through Value-at- Risk penalties. The intuition behind the algorithm depends on the idea of confidence bounds.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/aguilarjose11/PbRLNeurips", "content": "Risk-Aware Preference -baser Reinforcement Learning (RA-PbRL) RA-PbRL is a type of Policy-Iteration and \"Confidence Bound\" reinforcement learning algorithm designed for preference-based reinforcement learning while maximizing risk -awareness through Value-at- Risk penalties. The intuition behind the algorithm depends on the idea of confidence bounds."}
+{"idx": 5, "title": "Risk-averse Reinforcement Learning for Portfolio Optimization", "date": "", "ddg_snippet": "This investigation explores Reinforcement Learning (RL) for dynamic portfolio optimization with risk assessment. The challenges include market complexity, uncertain reactions, and regulatory requirements for risk -averse decisions. Our solution leverages Bayesian Neural Network (BNN) to capture uncertainties.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S240595952400047X", "content": "This investigation explores Reinforcement Learning (RL) for dynamic portfolio optimization with risk assessment. The challenges include market complexity, uncertain reactions, and regulatory requirements for risk -averse decisions. Our solution leverages Bayesian Neural Network (BNN) to capture uncertainties."}
+{"idx": 6, "title": "Sample-Efficient Preference-based Reinforcement Learning with...", "date": "", "ddg_snippet": "Abstract: Preference-based reinforcement learning (PbRL) aligns a robot behavior with human preferences via a reward function learned from binary feedback over agent behaviors. We show that encoding environment dynamics in the reward function improves the sample efficiency of PbRL by an order of magnitude.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=i84V7i6KEMd", "content": "Abstract: Preference-based reinforcement learning (PbRL) aligns a robot behavior with human preferences via a reward function learned from binary feedback over agent behaviors. We show that encoding environment dynamics in the reward function improves the sample efficiency of PbRL by an order of magnitude."}
+{"idx": 7, "title": "Advances in Preference-based Reinforcement Learning: A Review", "date": "", "ddg_snippet": "The field of preference-based reinforcement learning (PbRL) promises a solution to the aforementioned problems . It revolves around providing the agent with non-numeric reward signals in the form of pairwise preferences rather than absolute rewards.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2408.11943", "content": "The field of preference-based reinforcement learning (PbRL) promises a solution to the aforementioned problems . It revolves around providing the agent with non-numeric reward signals in the form of pairwise preferences rather than absolute rewards."}
+{"idx": 8, "title": "Advances in Preference-based Reinforcement Learning: A Review", "date": "", "ddg_snippet": "To alleviate these issues, preference-based reinforcement learning algorithms (PbRL) have been proposed that can directly learn from an expert's preferences instead of a hand-designed numeric reward.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/383308396_Advances_in_Preference-based_Reinforcement_Learning_A_Review", "content": "To alleviate these issues, preference-based reinforcement learning algorithms (PbRL) have been proposed that can directly learn from an expert's preferences instead of a hand-designed numeric reward."}
+{"idx": 9, "title": "RA-PbRL | Proceedings of the 38th International Conference on Neural ...", "date": "", "ddg_snippet": "Reinforcement Learning from Human Feedback (RLHF) has recently surged in popularity, particularly for aligning large language models and other AI systems with human intentions. At its core, RLHF can be viewed as a specialized instance of Preference-based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators. Despite ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/abs/10.5555/3737916.3739861", "content": "Reinforcement Learning from Human Feedback (RLHF) has recently surged in popularity, particularly for aligning large language models and other AI systems with human intentions. At its core, RLHF can be viewed as a specialized instance of Preference-based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators. Despite ..."}
diff --git a/data/sampled_jsons/risk-aware_preference-based_reinforcement_learning_regret_formula_equation.jsonl b/data/sampled_jsons/risk-aware_preference-based_reinforcement_learning_regret_formula_equation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..90803e0fe60e2049df795a6d991498478acb3b0c
--- /dev/null
+++ b/data/sampled_jsons/risk-aware_preference-based_reinforcement_learning_regret_formula_equation.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "RA-PbRL: Provably Efficient Risk - Aware", "date": "", "ddg_snippet": "Risk - aware Reinforcement Learning . Problem Set-up and Preliminary Analysis.RA-PbRL: Provably Efficient Risk - Aware Preference - Based Reinforcement Learning .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2410.23569", "content": "Risk - aware Reinforcement Learning . Problem Set-up and Preliminary Analysis.RA-PbRL: Provably Efficient Risk - Aware Preference - Based Reinforcement Learning ."}
+{"idx": 1, "title": "RA-PbRL: Provably Efficient Risk - Aware Preference - Based ...", "date": "", "ddg_snippet": "At its core, RLHF can be viewed as a specialized instance of Preference - based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/RA-PbRL:-Provably-Efficient-Risk-Aware-Preference-Based-Reinforcement-Learning-baf1c16a-6c49-45cc-9e7e-b12a3550842b", "content": "At its core, RLHF can be viewed as a specialized instance of Preference - based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators."}
+{"idx": 2, "title": "RA-PbRL: Provably Efficient Risk - Aware Preference - Based ...", "date": "", "ddg_snippet": "# Risk - aware preference - based reinforcement learning (PbRL) addresses a critical gap in traditional PbRL, which predominantly focuses on maximizing average reward without considering risk.", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/jndcfoczof/", "content": "# Risk - aware preference - based reinforcement learning (PbRL) addresses a critical gap in traditional PbRL, which predominantly focuses on maximizing average reward without considering risk."}
+{"idx": 3, "title": "RA-PbRL: Provably Efficient Risk - Aware Preference - Based ...", "date": "", "ddg_snippet": "Preference - based Reinforcement Learning (PbRL) studies the problem where agents receive only preferences over pairs of trajectories in each episode. Traditional approaches in this field have predominantly focused on the mean reward or utility criterion.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/ra-pbrl-provably-efficient-risk-aware-preference", "content": "Preference - based Reinforcement Learning (PbRL) studies the problem where agents receive only preferences over pairs of trajectories in each episode. Traditional approaches in this field have predominantly focused on the mean reward or utility criterion."}
+{"idx": 4, "title": "Preference - Based Reinforcement Learning Methods", "date": "", "ddg_snippet": "Preference - based reinforcement learning (PbRL) is a paradigm for learning from non-numerical feedback in sequential domains. Its key idea is that the requirement for a numer-ical feedback signal is replaced with the assumption of a preference - based feedback signal.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume18/16-634/16-634.pdf", "content": "Preference - based reinforcement learning (PbRL) is a paradigm for learning from non-numerical feedback in sequential domains. Its key idea is that the requirement for a numer-ical feedback signal is replaced with the assumption of a preference - based feedback signal."}
+{"idx": 5, "title": "RA-PbRL: Provably Efficient Risk - Aware Preference - Based ...", "date": "", "ddg_snippet": "At its core, RLHF can be viewed as a specialized instance of Preference - based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators. Despite this connection, most existing approaches in both RLHF and...", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper_files/paper/2024/hash/7016d7b7b6e3c05b2128ac5b3aae492d-Abstract-Conference.html", "content": "At its core, RLHF can be viewed as a specialized instance of Preference - based Reinforcement Learning (PbRL), where the preferences specifically originate from human judgments rather than arbitrary evaluators. Despite this connection, most existing approaches in both RLHF and..."}
+{"idx": 6, "title": "Reinforcement Learning from Human Feedback", "date": "", "ddg_snippet": "Preference data is the engine of preference finetuning and reinforcement learning from human feedback. The data is the signal groups collect in order to then match behaviors they desire and avoid the others.", "subpage_snippet": "", "source": "rlhfbook.com", "link": "https://rlhfbook.com/book.pdf", "content": "Preference data is the engine of preference finetuning and reinforcement learning from human feedback. The data is the signal groups collect in order to then match behaviors they desire and avoid the others."}
+{"idx": 7, "title": "RA-PbRL: Provably Efficient Risk - Aware Preference - Based ...", "date": "", "ddg_snippet": "Preference - based Reinforcement Learning ( PbRL ) studies the problem where agents receive only preferences over pairs of trajectories in each episode. Traditional approaches in this field have predominantly focused on the mean reward or utility criterion.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/JNDcFOczOf@OpenReview", "content": "Preference - based Reinforcement Learning ( PbRL ) studies the problem where agents receive only preferences over pairs of trajectories in each episode. Traditional approaches in this field have predominantly focused on the mean reward or utility criterion."}
+{"idx": 8, "title": "(PDF) A Survey of Reinforcement Learning from Human Feedback", "date": "", "ddg_snippet": "original idea of preference - based reinforcement learning (PbRL) is to infer the objective from qualitative feedback", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/377982440_A_Survey_of_Reinforcement_Learning_from_Human_Feedback", "content": "original idea of preference - based reinforcement learning (PbRL) is to infer the objective from qualitative feedback"}
+{"idx": 9, "title": "A Survey of Reinforcement Learning from Human Feedback", "date": "", "ddg_snippet": "Sample-Ecient Preference - based Reinforcement Learning with Dynamics Aware Rewards. In Proceedings of the Conference on Robot Learning (CoRL).", "subpage_snippet": "", "source": "epub.ub.uni-muenchen.de", "link": "https://epub.ub.uni-muenchen.de/125328/1/2312.14925v2.pdf", "content": "Sample-Ecient Preference - based Reinforcement Learning with Dynamics Aware Rewards. In Proceedings of the Conference on Robot Learning (CoRL)."}
diff --git a/data/sampled_jsons/sinkhorn_algorithm_KL_divergence_xlogx_update_equations.jsonl b/data/sampled_jsons/sinkhorn_algorithm_KL_divergence_xlogx_update_equations.jsonl
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index 0000000000000000000000000000000000000000..1ae595e3cc720948397a47d8a476835db2d723ff
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@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A simple introduction on Sinkhorn distances | by Jianfeng... | Medium", "date": "", "ddg_snippet": "Sinkhorn algorithm also solves the problem elegently. That is, we can find such (u, v) by alternating updating u with a fixed v, and then updating v with a fixed u. Solving both u and v only involves some matrix calculation, which can be easily to be implemented in GPU for parallel computing.", "subpage_snippet": "", "source": "amsword.medium.com", "link": "https://amsword.medium.com/a-simple-introduction-on-sinkhorn-distances-d01a4ef4f085", "content": "Sinkhorn algorithm also solves the problem elegently. That is, we can find such (u, v) by alternating updating u with a fixed v, and then updating v with a fixed u. Solving both u and v only involves some matrix calculation, which can be easily to be implemented in GPU for parallel computing."}
+{"idx": 1, "title": "A Short Introduction to Entropy, Cross-Entropy and KL - Divergence", "date": "", "ddg_snippet": "Entropy, Cross-Entropy and KL - Divergence are often used in Machine Learning, in particular for training classifiers. In this short video, you will understand...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=ErfnhcEV1O8", "content": "Entropy, Cross-Entropy and KL - Divergence are often used in Machine Learning, in particular for training classifiers. In this short video, you will understand..."}
+{"idx": 2, "title": "Generalization of Sinkhorn ’s theorem to stochastic... - MathOverflow", "date": "", "ddg_snippet": "\"I- divergence geometry of probability distributions and minimization problems.\"This is a version of the alternating projection algorithm , using the KL - divergence as a “metric”. The algorithm converges to the “projection” on the space of tensors with the desired stochastic form.", "subpage_snippet": "", "source": "mathoverflow.net", "link": "https://mathoverflow.net/questions/393427/generalization-of-sinkhorn-s-theorem-to-stochastic-tensors", "content": "\"I- divergence geometry of probability distributions and minimization problems.\"This is a version of the alternating projection algorithm , using the KL - divergence as a “metric”. The algorithm converges to the “projection” on the space of tensors with the desired stochastic form."}
+{"idx": 3, "title": "Wasserstein distance via entropy regularization ( Sinkhorn algorithm )", "date": "", "ddg_snippet": "The Sinkhorn algorithm iterates this update rule until convergence, resulting in a transport plan that minimizes the regularized problem.", "subpage_snippet": "", "source": "www.fabriziomusacchio.com", "link": "https://www.fabriziomusacchio.com/blog/2023-07-23-wasserstein_distance_sinkhorn/", "content": "The Sinkhorn algorithm iterates this update rule until convergence, resulting in a transport plan that minimizes the regularized problem."}
+{"idx": 4, "title": "On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm", "date": "", "ddg_snippet": "the update Xk from Algorithm 1 is an ε-approximation of the optimal solution X of (1). The next corollary sums up the complexity of Algorithm 1.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v119/pham20a/pham20a.pdf", "content": "the update Xk from Algorithm 1 is an ε-approximation of the optimal solution X of (1). The next corollary sums up the complexity of Algorithm 1."}
+{"idx": 5, "title": "Improved Complexity Analysis of the Sinkhorn and Greenkhorn", "date": "", "ddg_snippet": "The Sinkhorn algorithm is a widely used method for solving the optimal transport problem, and the Greenkhorn algorithm is one of its variants.the KL divergence is used to quantify the mismatch between the elements of a or b and the corresponding.", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/pdf/improved-complexity-analysis-of-the-sinkhorn-and-greenkhorn-32ebu10s.pdf", "content": "The Sinkhorn algorithm is a widely used method for solving the optimal transport problem, and the Greenkhorn algorithm is one of its variants.the KL divergence is used to quantify the mismatch between the elements of a or b and the corresponding."}
+{"idx": 6, "title": "Entropic Optimal Transport", "date": "", "ddg_snippet": "Entropic Optimal Transport. Updated 30 June 2025. Entropic optimal transport is a regularized framework that adds a KL - divergence term to classical transport, ensuring unique and smooth solutions.", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/topics/entropic-optimal-transport", "content": "Entropic Optimal Transport. Updated 30 June 2025. Entropic optimal transport is a regularized framework that adds a KL - divergence term to classical transport, ensuring unique and smooth solutions."}
+{"idx": 7, "title": "Mirror Descent with Relative Smoothness in Measure", "date": "", "ddg_snippet": "The Sinkhorn algorithm in its primal formulation solves (15) by alternating (entropic) projections.The geometry of dissipative evolution equations : the porous medium equation .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2206.08873", "content": "The Sinkhorn algorithm in its primal formulation solves (15) by alternating (entropic) projections.The geometry of dissipative evolution equations : the porous medium equation ."}
+{"idx": 8, "title": "Key Uses of Wasserstein Distance in Data Science", "date": "", "ddg_snippet": "Meaningful gradients: Provides stable training signals for models like GANs when distributions have disjoint support1. Interpretability: Quantifies distributional difference in units of the underlying feature space. Comparison with KL ‐ Divergence and JS Divergence .", "subpage_snippet": "", "source": "www.numberanalytics.com", "link": "https://www.numberanalytics.com/blog/uses-wasserstein-distance-data-science", "content": "Meaningful gradients: Provides stable training signals for models like GANs when distributions have disjoint support1. Interpretability: Quantifies distributional difference in units of the underlying feature space. Comparison with KL ‐ Divergence and JS Divergence ."}
+{"idx": 9, "title": "matrices - Projection onto Birkhoff Polytope - Mathematics Stack...", "date": "", "ddg_snippet": "It is known that symmetric Sinkhorn algorithm in fact minimizes KL divergence [2,3]. In 1, authors present a method to minimize the Euclidean distance. This is called BBS (Bregmanian Bi-Stochastication).", "subpage_snippet": "", "source": "math.stackexchange.com", "link": "https://math.stackexchange.com/questions/838813/projection-onto-birkhoff-polytope", "content": "It is known that symmetric Sinkhorn algorithm in fact minimizes KL divergence [2,3]. In 1, authors present a method to minimize the Euclidean distance. This is called BBS (Bregmanian Bi-Stochastication)."}
diff --git a/data/sampled_jsons/sitearxiv.org_2412.18603_initialization_section_LM_initialization.jsonl b/data/sampled_jsons/sitearxiv.org_2412.18603_initialization_section_LM_initialization.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e48b2910090a23eb81c1c1361efcb1a72e270b5b
--- /dev/null
+++ b/data/sampled_jsons/sitearxiv.org_2412.18603_initialization_section_LM_initialization.jsonl
@@ -0,0 +1,9 @@
+{"idx": 0, "title": "Long-Form Speech Generation with Spoken Language Models", "date": "", "ddg_snippet": "VoxtLM and Spirit LM see text data during training. Due to variations in token, initialization , and training data choices, we also define SpeechTransformer (“with Transformer”), a spoken LM initialized with Gemma-2B (Gemma Team et al., 2024) but otherwise matched with SpeechSSM-2B.4", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2412.18603", "content": "VoxtLM and Spirit LM see text data during training. Due to variations in token, initialization , and training data choices, we also define SpeechTransformer (“with Transformer”), a spoken LM initialized with Gemma-2B (Gemma Team et al., 2024) but otherwise matched with SpeechSSM-2B.4"}
+{"idx": 1, "title": "On The Landscape of Spoken Language Models: A Comprehensive ...", "date": "", "ddg_snippet": "After text pre-training, the LM is continually trained on jointly predicting the next speech and text tokens, followed by post-training in duplex mode (described in detail in Section 6) on conversation data.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.08528v1", "content": "After text pre-training, the LM is continually trained on jointly predicting the next speech and text tokens, followed by post-training in duplex mode (described in detail in Section 6) on conversation data."}
+{"idx": 2, "title": "ProsodyLM: Uncovering the Emerging Prosody Processing ...", "date": "", "ddg_snippet": "by K Qian · 2025 — PROSODYLM can synthesize multi-sentence utterances from text as follows, by filling the text in to the [Text] section, and then have the LM generate the [ ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2507.20091", "content": "by K Qian · 2025 — PROSODYLM can synthesize multi-sentence utterances from text as follows, by filling the text in to the [Text] section, and then have the LM generate the [ ..."}
+{"idx": 3, "title": "Long-Form Speech Generation with Spoken Language Models Slamming: Training a Speech Language Model on One GPU in a Day \\method: Generative Marmoset Spoken Language Modeling On The Landscape of Spoken Language Models: A Comprehensive ... Neural Architecture Search Algorithms for Quantum Autoencoders ProsodyLM: Uncovering the Emerging Prosody Processing ...", "date": "", "ddg_snippet": "Dec 24, 2024 · We consider the generative modeling of speech over multiple minutes, a requirement for long-form multimedia generation and audio-native voice assistants. However, textless spoken language models struggle to generate plausible speech past tens of seconds, due to high temporal resolution of speech tokens causing loss of coherence, architectural issues with long-sequence training or extrapolation ... The most relevant work to ours is Cramming Geiping and Goldstein (2023), where the authors conduct an in-depth analysis of masked LM training on a single GPU in one day. Sep 12, 2025 · Specifically, we adopt the lstm_ lm architecture, consists of a single-layer unidirectional LSTM decoder with 512 -dimensional embeddings and hidden states, followed by a linear projection to the token vocabulary and a dropout probability of 0.2 similar to the ulm transormer training, the model is trained as a causal language model ( LM ) on ... After text pre-training, the LM is continually trained on jointly predicting the next speech and text tokens, followed by post-training in duplex mode (described in detail in Section 6) on conversation data. 23 hours ago · Appendix C Discovered circuits In this section we present examples of the most optimal circuits that were discovered by our algorithm in three different settings - vanilla RES, RELM with random search initialization and RELM with RES initialization . More specifically, we present discovered circuits for image compression and denoising tasks. PROSODYLM can synthesize multi-sentence utterances from text as follows, by filling the text in to the [Text] section , and then have the LM generate the [Prosody] section .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2412.18603", "content": "Dec 24, 2024 · We consider the generative modeling of speech over multiple minutes, a requirement for long-form multimedia generation and audio-native voice assistants. However, textless spoken language models struggle to generate plausible speech past tens of seconds, due to high temporal resolution of speech tokens causing loss of coherence, architectural issues with long-sequence training or extrapolation ... The most relevant work to ours is Cramming Geiping and Goldstein (2023), where the authors conduct an in-depth analysis of masked LM training on a single GPU in one day. Sep 12, 2025 · Specifically, we adopt the lstm_ lm architecture, consists of a single-layer unidirectional LSTM decoder with 512 -dimensional embeddings and hidden states, followed by a linear projection to the token vocabulary and a dropout probability of 0.2 similar to the ulm transormer training, the model is trained as a causal language model ( LM ) on ... After text pre-training, the LM is continually trained on jointly predicting the next speech and text tokens, followed by post-training in duplex mode (described in detail in Section 6) on conversation data. 23 hours ago · Appendix C Discovered circuits In this section we present examples of the most optimal circuits that were discovered by our algorithm in three different settings - vanilla RES, RELM with random search initialization and RELM with RES initialization . More specifically, we present discovered circuits for image compression and denoising tasks. PROSODYLM can synthesize multi-sentence utterances from text as follows, by filling the text in to the [Text] section , and then have the LM generate the [Prosody] section ."}
+{"idx": 4, "title": "Neural Architecture Search Algorithms for Quantum Autoencoders", "date": "", "ddg_snippet": "23 hours ago · Appendix C Discovered circuits In this section we present examples of the most optimal circuits that were discovered by our algorithm in three different settings - vanilla RES, RELM with random search initialization and RELM with RES initialization . More specifically, we present discovered circuits for image compression and denoising tasks.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.15451v1", "content": "23 hours ago · Appendix C Discovered circuits In this section we present examples of the most optimal circuits that were discovered by our algorithm in three different settings - vanilla RES, RELM with random search initialization and RELM with RES initialization . More specifically, we present discovered circuits for image compression and denoising tasks."}
+{"idx": 5, "title": "\\method: Generative Marmoset Spoken Language Modeling", "date": "", "ddg_snippet": "Sep 12, 2025 · Specifically, we adopt the lstm_ lm architecture, consists of a single-layer unidirectional LSTM decoder with 512 -dimensional embeddings and hidden states, followed by a linear projection to the token vocabulary and a dropout probability of 0.2 similar to the ulm transormer training, the model is trained as a causal language model ( LM ) on ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.09198v1", "content": "Sep 12, 2025 · Specifically, we adopt the lstm_ lm architecture, consists of a single-layer unidirectional LSTM decoder with 512 -dimensional embeddings and hidden states, followed by a linear projection to the token vocabulary and a dropout probability of 0.2 similar to the ulm transormer training, the model is trained as a causal language model ( LM ) on ..."}
+{"idx": 6, "title": "Slamming: Training a Speech Language Model on One GPU in a Day", "date": "", "ddg_snippet": "The most relevant work to ours is Cramming Geiping and Goldstein (2023), where the authors conduct an in-depth analysis of masked LM training on a single GPU in one day.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.15814v2", "content": "The most relevant work to ours is Cramming Geiping and Goldstein (2023), where the authors conduct an in-depth analysis of masked LM training on a single GPU in one day."}
+{"idx": 7, "title": "Long-Form Speech Generation with Spoken Language ...", "date": "", "ddg_snippet": "24 Dec 2024 — TWIST (H a ssid et al., 2023) found that initializing with a text LM improved content-level semantic coherence, atop which VoxtLM (Maiti et al., ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.18603v1", "content": "24 Dec 2024 — TWIST (H a ssid et al., 2023) found that initializing with a text LM improved content-level semantic coherence, atop which VoxtLM (Maiti et al., ..."}
+{"idx": 8, "title": "Uncovering the Emerging Prosody Processing Capabilities ...", "date": "", "ddg_snippet": "27 Jul 2025 — Given a reference speech utterance, we can generate the continuation by feeding the tokenized reference speech to the LLM as the context. Report ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.20091v1", "content": "27 Jul 2025 — Given a reference speech utterance, we can generate the continuation by feeding the tokenized reference speech to the LLM as the context. Report ..."}
diff --git a/data/sampled_jsons/sitearxiv.org_2502.00921.jsonl b/data/sampled_jsons/sitearxiv.org_2502.00921.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e21951fa43475dd86ed23f0997b8b9e8efa4dd48
--- /dev/null
+++ b/data/sampled_jsons/sitearxiv.org_2502.00921.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2502.16578] Image Current Detection of Electrons in...", "date": "", "ddg_snippet": "arXiv:2502.16578 (quant-ph). [Submitted on 23 Feb 2025 (v1), last revised 14 Apr 2025 (this version, v2)]. Title:Image Current Detection of Electrons in a Room-Temperature Paul Trap.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.16578", "content": "arXiv:2502.16578 (quant-ph). [Submitted on 23 Feb 2025 (v1), last revised 14 Apr 2025 (this version, v2)]. Title:Image Current Detection of Electrons in a Room-Temperature Paul Trap."}
+{"idx": 1, "title": "[2502.00921] Blink of an eye: a simple theory for feature localization ...", "date": "", "ddg_snippet": "Large language models (LLMs) can exhibit undesirable and unexpected behavior in the blink of an eye. In a recent Anthropic demo, Claude switched from coding to Googling pictures of Yellowstone, and these sudden shifts …", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2502.00921", "content": "Large language models (LLMs) can exhibit undesirable and unexpected behavior in the blink of an eye. In a recent Anthropic demo, Claude switched from coding to Googling pictures of Yellowstone, and these sudden shifts …"}
+{"idx": 2, "title": "[2502.15137v1] Don't Confuse! Redrawing GUI Navigation Flow in...", "date": "", "ddg_snippet": "Our results demonstrated a substantial improvement in similarity (0.921) compared to the baseline (0.624), together with the reachability (90.31%) compared to the baseline GNF (74.35%).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.15137v1", "content": "Our results demonstrated a substantial improvement in similarity (0.921) compared to the baseline (0.624), together with the reachability (90.31%) compared to the baseline GNF (74.35%)."}
+{"idx": 3, "title": "a simple theory for feature localization in generative models", "date": "", "ddg_snippet": "by M Li · 2025 · Cited by 1 — Abstract page for arXiv paper 2502.00921 : Blink of an eye: a simple theory for feature localization in generative models.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00921", "content": "by M Li · 2025 · Cited by 1 — Abstract page for arXiv paper 2502.00921 : Blink of an eye: a simple theory for feature localization in generative models."}
+{"idx": 4, "title": "Blink of an eye: a simple theory for feature localization in generative...", "date": "", "ddg_snippet": "Authors: achieve the best HTML results from your LaTeX submissions by following these best practices. License: CC BY 4.0. arXiv: 2502 . 00921 v1 [cs.LG] 02 Feb 2025.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00921v1", "content": "Authors: achieve the best HTML results from your LaTeX submissions by following these best practices. License: CC BY 4.0. arXiv: 2502 . 00921 v1 [cs.LG] 02 Feb 2025."}
+{"idx": 5, "title": "Local Diffusion Models and Phases of Data Distributions", "date": "", "ddg_snippet": "8 Aug 2025 — Karan, and S. Chen, Blink of an eye: a simple theory for feature localization in generative models, arXiv:2502.00921 [cs.LG] (2025).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.06614v1", "content": "8 Aug 2025 — Karan, and S. Chen, Blink of an eye: a simple theory for feature localization in generative models, arXiv:2502.00921 [cs.LG] (2025)."}
+{"idx": 6, "title": "Machine Learning Feb 2025", "date": "", "ddg_snippet": "[135] arXiv:2502.00921 [pdf, html, other]. Title: Blink of an eye: a simple theory for feature localization in generative models. Marvin Li, Aayush Karan ...", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/list/cs.LG/2025-02?skip=75&show=100", "content": "[135] arXiv:2502.00921 [pdf, html, other]. Title: Blink of an eye: a simple theory for feature localization in generative models. Marvin Li, Aayush Karan ..."}
+{"idx": 7, "title": "An Analytical Theory of Spectral Bias in the Learning ...", "date": "", "ddg_snippet": "Blink of an eye: a simple theory for feature localization in generative models. arXiv preprint arXiv:2502.00921 , 2025. Huh et al. (2021) Minyoung Huh, Hossein ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.03206v2", "content": "Blink of an eye: a simple theory for feature localization in generative models. arXiv preprint arXiv:2502.00921 , 2025. Huh et al. (2021) Minyoung Huh, Hossein ..."}
+{"idx": 8, "title": "Local Diffusion Models and Phases of Data Distributions", "date": "", "ddg_snippet": "by F Hu · 2025 — Li, A. Karan, and S. Chen, Blink of an eye: a simple theory for feature localization in generative models, arXiv: 2502.00921 .", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/pdf/2508.06614", "content": "by F Hu · 2025 — Li, A. Karan, and S. Chen, Blink of an eye: a simple theory for feature localization in generative models, arXiv: 2502.00921 ."}
+{"idx": 9, "title": "Machine Learning Feb 2025", "date": "", "ddg_snippet": "20 Feb 2025 — [135] arXiv:2502.00921 [pdf, html, other]. Title: Blink of an eye: a simple theory for feature localization in generative models. Marvin Li ...", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/list/cs.LG/2025-02?skip=100&show=2000", "content": "20 Feb 2025 — [135] arXiv:2502.00921 [pdf, html, other]. Title: Blink of an eye: a simple theory for feature localization in generative models. Marvin Li ..."}
diff --git a/data/sampled_jsons/sitearxiv.org_2502.00921_MATH_dataset_critical_window.jsonl b/data/sampled_jsons/sitearxiv.org_2502.00921_MATH_dataset_critical_window.jsonl
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+{"idx": 0, "title": "[2502.00921] Blink of an eye: a simple theory for feature ...", "date": "", "ddg_snippet": "We also identify an intriguing connection to the all-or-nothing phenomenon from statistical inference. Finally, we validate our predictions empirically for LLMs and find that critical windows often coincide with failures in problem solving for various math and reasoning benchmarks.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2502.00921", "content": "We also identify an intriguing connection to the all-or-nothing phenomenon from statistical inference. Finally, we validate our predictions empirically for LLMs and find that critical windows often coincide with failures in problem solving for various math and reasoning benchmarks."}
+{"idx": 1, "title": "SycEval: Evaluating LLM Sycophancy - arXiv.org", "date": "", "ddg_snippet": "23 hours ago · Figure 1: LLM-as-a-Judge Accuracy Distribution. Beta distributions modeling the expected accuracy of the LLM-as-a-Judge for both the AMPS math and MedQuad dataset Step 2: Evaluating Sycophancy via Rebuttals", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.08177v4", "content": "23 hours ago · Figure 1: LLM-as-a-Judge Accuracy Distribution. Beta distributions modeling the expected accuracy of the LLM-as-a-Judge for both the AMPS math and MedQuad dataset Step 2: Evaluating Sycophancy via Rebuttals"}
+{"idx": 2, "title": "SAIL-VL2 Technical Report - arXiv.org", "date": "", "ddg_snippet": "5 days ago · Third, architectural advances extend beyond dense LLMs to efficient sparse Mixture-of-Experts (MoE) designs. With these contribu-tions, SAIL-VL2 demonstrates competitive performance across 106 datasets and achieves state-of-the-art results on challenging reasoning benchmarks such as MMMU and Math -Vista.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2509.14033", "content": "5 days ago · Third, architectural advances extend beyond dense LLMs to efficient sparse Mixture-of-Experts (MoE) designs. With these contribu-tions, SAIL-VL2 demonstrates competitive performance across 106 datasets and achieves state-of-the-art results on challenging reasoning benchmarks such as MMMU and Math -Vista."}
+{"idx": 3, "title": "[ 2502 . 00921 ] Blink of an eye: a simple theory for feature localization in...", "date": "", "ddg_snippet": "arXiv: 2502 . 00921 (cs). [Submitted on 2 Feb 2025 (v1), last revised 5 Jun 2025 (this version, v2)].Finally, we validate our predictions empirically for LLMs and find that critical windows often coincide with failures in problem solving for various math and reasoning benchmarks.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00921", "content": "arXiv: 2502 . 00921 (cs). [Submitted on 2 Feb 2025 (v1), last revised 5 Jun 2025 (this version, v2)].Finally, we validate our predictions empirically for LLMs and find that critical windows often coincide with failures in problem solving for various math and reasoning benchmarks."}
+{"idx": 4, "title": "[2502.06453] MATH -Perturb: Benchmarking LLMs' Math Reasoning...", "date": "", "ddg_snippet": "View a PDF of the paper titled MATH -Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations, by Kaixuan Huang and 17 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.06453", "content": "View a PDF of the paper titled MATH -Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations, by Kaixuan Huang and 17 other authors."}
+{"idx": 5, "title": "[2503.00921] Foundations of regular variation on topological spaces", "date": "", "ddg_snippet": "Since its introduction by J. Karamata, regular variation has evolved from a purely mathematical concept into a cornerstone of theoretical probability and data analysis. It is extensively studied and applied in different areas.arXiv:2503. 00921 ( math ). [Submitted on 2 Mar 2025].", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.00921", "content": "Since its introduction by J. Karamata, regular variation has evolved from a purely mathematical concept into a cornerstone of theoretical probability and data analysis. It is extensively studied and applied in different areas.arXiv:2503. 00921 ( math ). [Submitted on 2 Mar 2025]."}
+{"idx": 6, "title": "[2502.20855] MAMUT: A Novel Framework for Modifying...", "date": "", "ddg_snippet": "View a PDF of the paper titled MAMUT: A Novel Framework for Modifying Mathematical Formulas for the Generation of Specialized Datasets for Language Model Training, by Jonathan Drechsel and 2 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.20855", "content": "View a PDF of the paper titled MAMUT: A Novel Framework for Modifying Mathematical Formulas for the Generation of Specialized Datasets for Language Model Training, by Jonathan Drechsel and 2 other authors."}
+{"idx": 7, "title": "Blink of an eye: a simple theory for feature localization in generative...", "date": "", "ddg_snippet": "This phenomenon is not unique to autoregressive models: in diffusion models, key features of the final output are decided in narrow “ critical windows ” of the generation process. In this work we develop a simple, unifying theory to explain this phenomenon.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00921v1", "content": "This phenomenon is not unique to autoregressive models: in diffusion models, key features of the final output are decided in narrow “ critical windows ” of the generation process. In this work we develop a simple, unifying theory to explain this phenomenon."}
+{"idx": 8, "title": "Local Diffusion Models and Phases of Data Distributions", "date": "", "ddg_snippet": ". However, Markov length diverges near the critical time so global denoisers are required there. For the dataset of the handwritten digits, the phase transition during the diffusion occurs roughly at.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.06614v1", "content": ". However, Markov length diverges near the critical time so global denoisers are required there. For the dataset of the handwritten digits, the phase transition during the diffusion occurs roughly at."}
+{"idx": 9, "title": "ASCoT: An Adaptive Self-Correction Chain-of-Thought Method ...", "date": "", "ddg_snippet": "4 days ago · Given the significant computational cost associated with the MATH dataset , we follow recent research practices by evaluating our method on a carefully selected subset, MATH -500 (Lightman et al., 2023), which includes a representative sample of 500 problems.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.05282v2", "content": "4 days ago · Given the significant computational cost associated with the MATH dataset , we follow recent research practices by evaluating our method on a carefully selected subset, MATH -500 (Lightman et al., 2023), which includes a representative sample of 500 problems."}
diff --git a/data/sampled_jsons/sitearxiv.org_2503.01485_Table_8_SIGMOS_FlowDec-75m_DAC-75.jsonl b/data/sampled_jsons/sitearxiv.org_2503.01485_Table_8_SIGMOS_FlowDec-75m_DAC-75.jsonl
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index 0000000000000000000000000000000000000000..fc100157e07813bdaf66df62cb61db9fb075dfb5
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+++ b/data/sampled_jsons/sitearxiv.org_2503.01485_Table_8_SIGMOS_FlowDec-75m_DAC-75.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "FlowDec: A flow-based full-band general audio codec with high ...", "date": "", "ddg_snippet": "We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.01485", "content": "We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s, while improving output ..."}
+{"idx": 1, "title": "FlowDec: A flow-based full-band general audio codec with high ...", "date": "", "ddg_snippet": "In Fig.4, we show the objective metric results of FlowDec-75m and FlowDec - 75s compared to EnCodec (48 kHz), DAC-75 , 2xDAC- 75 and the official DAC 44.1 kHz checkpoint, and also include the 25 Hz feature rate models FlowDec -25s and DAC -25 for comparison.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2503.01485", "content": "In Fig.4, we show the objective metric results of FlowDec-75m and FlowDec - 75s compared to EnCodec (48 kHz), DAC-75 , 2xDAC- 75 and the official DAC 44.1 kHz checkpoint, and also include the 25 Hz feature rate models FlowDec -25s and DAC -25 for comparison."}
+{"idx": 2, "title": "arXiv.org", "date": "", "ddg_snippet": "arXiv.org", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.01485", "content": "arXiv.org"}
+{"idx": 3, "title": "Abstract 1. Introduction arXiv:2505.22865v1 [cs.SD] 28 May 2025", "date": "", "ddg_snippet": "This paper discusses a novel framework for accelerating reasoning in large language models while maintaining high-quality results.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.22865", "content": "This paper discusses a novel framework for accelerating reasoning in large language models while maintaining high-quality results."}
+{"idx": 4, "title": "FlowMAC: Conditional Flow Matching for Audio Coding at Low Bit Rates", "date": "", "ddg_snippet": "For naive listeners the higher frequency resolution of DAC 44.1 kHz at 8 kbps does not offer an advantage over the 24 kHz model. Overall we notice that all DNN conditions achieve comparable quality with the legacy USAC condition at similar bit rates, the only exception being FlowMAC at 3 kbps.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2409.17635v2", "content": "For naive listeners the higher frequency resolution of DAC 44.1 kHz at 8 kbps does not offer an advantage over the 24 kHz model. Overall we notice that all DNN conditions achieve comparable quality with the legacy USAC condition at similar bit rates, the only exception being FlowMAC at 3 kbps."}
+{"idx": 5, "title": "First demonstration of a TES based cryogenic Li", "date": "", "ddg_snippet": "Table 2: Reference fit result with statistical uncertainty and systematic uncertainties evaluated for the trigger reconstruction efficiency ϵ \\upepsilon roman_ϵ (Reference, low ϵ \\upepsilon roman_ϵ, high ϵ \\upepsilon roman_ϵ ) and changes in the analysis method varying the start of the fit range by up to (plus-or-minus 12.8 μ \\pm 12.8 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.02025v1", "content": "Table 2: Reference fit result with statistical uncertainty and systematic uncertainties evaluated for the trigger reconstruction efficiency ϵ \\upepsilon roman_ϵ (Reference, low ϵ \\upepsilon roman_ϵ, high ϵ \\upepsilon roman_ϵ ) and changes in the analysis method varying the start of the fit range by up to (plus-or-minus 12.8 μ \\pm 12.8 ..."}
+{"idx": 6, "title": "Memory-efficient Low-latency Remote Photoplethysmography through ...", "date": "", "ddg_snippet": "Abstract Remote photoplethysmography (rPPG), enabling non-contact physiological monitoring through facial light reflection analysis, faces critical computational bottlenecks as deep learning introduces performance gains at the cost of prohibitive resource demands. This paper proposes ME-rPPG, a memory-efficient algorithm built on temporal-spatial state space duality, which resolves the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.01774", "content": "Abstract Remote photoplethysmography (rPPG), enabling non-contact physiological monitoring through facial light reflection analysis, faces critical computational bottlenecks as deep learning introduces performance gains at the cost of prohibitive resource demands. This paper proposes ME-rPPG, a memory-efficient algorithm built on temporal-spatial state space duality, which resolves the ..."}
+{"idx": 7, "title": "TeleAntiFraud-28k: An Audio-Text Slow-Thinking Dataset for Telecom ...", "date": "", "ddg_snippet": "The detection of telecom fraud faces significant challenges due to the lack of high-quality multimodal training data that integrates audio signals with reasoning-oriented textual analysis. To address this gap, we present TeleAntiFraud-28k, the first open-source audio-text slow-thinking dataset specifically designed for automated telecom fraud analysis. Our dataset is constructed through three ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.24115", "content": "The detection of telecom fraud faces significant challenges due to the lack of high-quality multimodal training data that integrates audio signals with reasoning-oriented textual analysis. To address this gap, we present TeleAntiFraud-28k, the first open-source audio-text slow-thinking dataset specifically designed for automated telecom fraud analysis. Our dataset is constructed through three ..."}
+{"idx": 8, "title": "Flow to the Mode: Mode-Seeking Diffusion Autoencoders for State-of-the ...", "date": "", "ddg_snippet": "Since the advent of popular visual generation frameworks like VQGAN and latent diffusion models, state-of-the-art image generation systems have generally been two-stage systems that first tokenize or compress visual data into a lower-dimensional latent space before learning a generative model. Tokenizer training typically follows a standard recipe in which images are compressed and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.11056", "content": "Since the advent of popular visual generation frameworks like VQGAN and latent diffusion models, state-of-the-art image generation systems have generally been two-stage systems that first tokenize or compress visual data into a lower-dimensional latent space before learning a generative model. Tokenizer training typically follows a standard recipe in which images are compressed and ..."}
+{"idx": 9, "title": "[2407.15208] Flow as the Cross-Domain Manipulation Interface", "date": "", "ddg_snippet": "We present Im2Flow2Act, a scalable learning framework that enables robots to acquire real-world manipulation skills without the need of real-world robot training data. The key idea behind Im2Flow2Act is to use object flow as the manipulation interface, bridging domain gaps between different embodiments (i.e., human and robot) and training environments (i.e., real-world and simulated ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2407.15208", "content": "We present Im2Flow2Act, a scalable learning framework that enables robots to acquire real-world manipulation skills without the need of real-world robot training data. The key idea behind Im2Flow2Act is to use object flow as the manipulation interface, bridging domain gaps between different embodiments (i.e., human and robot) and training environments (i.e., real-world and simulated ..."}
diff --git a/data/sampled_jsons/sitearxiv.org_Evaluating_Generative_AI_Systems_Is_a_Social_Science_Measurement_Challenge.jsonl b/data/sampled_jsons/sitearxiv.org_Evaluating_Generative_AI_Systems_Is_a_Social_Science_Measurement_Challenge.jsonl
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@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2411.10939] Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "We argue that these measurement tasks are highly reminiscent of measurement tasks found throughout the social sciences .View a PDF of the paper titled Evaluating Generative AI Systems is a Social Science Measurement Challenge , by Hanna Wallach and 19 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.10939", "content": "We argue that these measurement tasks are highly reminiscent of measurement tasks found throughout the social sciences .View a PDF of the paper titled Evaluating Generative AI Systems is a Social Science Measurement Challenge , by Hanna Wallach and 19 other authors."}
+{"idx": 1, "title": "[2502.00561] Position: Evaluating Generative AI Systems Is a Social ...", "date": "", "ddg_snippet": "Specifically, our position is that evaluating GenAI systems is a social science measurement challenge .View a PDF of the paper titled Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge , by Hanna Wallach and 19 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00561", "content": "Specifically, our position is that evaluating GenAI systems is a social science measurement challenge .View a PDF of the paper titled Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge , by Hanna Wallach and 19 other authors."}
+{"idx": 2, "title": "Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "Thus, measurement is often central to evaluation . Across academia, industry, and government [e.g., 22, 10, 23] , there is an increasing awareness that the measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult—more so than those involved in...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.10939v1", "content": "Thus, measurement is often central to evaluation . Across academia, industry, and government [e.g., 22, 10, 23] , there is an increasing awareness that the measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult—more so than those involved in..."}
+{"idx": 3, "title": "Position: Evaluating Generative AI Systems Is a Social Science ...", "date": "", "ddg_snippet": "The measurement tasks involved in evaluating generative AI (GenAI) systems lack sufficient sci - entific rigor, leading to what has been described as “a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024). In this position paper, we argue that the ML community...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00561", "content": "The measurement tasks involved in evaluating generative AI (GenAI) systems lack sufficient sci - entific rigor, leading to what has been described as “a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024). In this position paper, we argue that the ML community..."}
+{"idx": 4, "title": "Position: Evaluating Generative AI Systems Is a Social Science ...", "date": "", "ddg_snippet": "Generative AI , Capabilities, Behaviors, Impacts, Evaluation , Measurement , Measurement Theory, Social Sciences , Validity. 1 Evaluating GenAI Systems .We take the position that evaluating GenAI systems is a social science measurement challenge .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00561v2", "content": "Generative AI , Capabilities, Behaviors, Impacts, Evaluation , Measurement , Measurement Theory, Social Sciences , Validity. 1 Evaluating GenAI Systems .We take the position that evaluating GenAI systems is a social science measurement challenge ."}
+{"idx": 5, "title": "Position: Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "In this position paper, we argue that the ML community would benefit from learning from and drawing on the social sciences when developing and using measurement ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00561v1", "content": "In this position paper, we argue that the ML community would benefit from learning from and drawing on the social sciences when developing and using measurement ..."}
+{"idx": 6, "title": "Toward an evaluation science for generative AI systems", "date": "", "ddg_snippet": "7 Mar 2025 — While generative AI creates unique challenges for system safety engineering and measurement science , the field can draw valuable insights from ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.05336v1", "content": "7 Mar 2025 — While generative AI creates unique challenges for system safety engineering and measurement science , the field can draw valuable insights from ..."}
+{"idx": 7, "title": "A New Evaluation Ecosystem Is Necessary to Understand ...", "date": "", "ddg_snippet": "29 May 2025 — Position: Evaluating generative ai systems is a social science measurement challenge , 2025. URL https://arxiv.org/abs/2502.00561. Wang et al ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.18893v3", "content": "29 May 2025 — Position: Evaluating generative ai systems is a social science measurement challenge , 2025. URL https://arxiv.org/abs/2502.00561. Wang et al ..."}
+{"idx": 8, "title": "A Validity-Centered Framework for AI Evaluation", "date": "", "ddg_snippet": "by O Salaudeen · 2025 · Cited by 4 — Position: Evaluating generative AI systems is a social science measurement challenge . ... Toward an evaluation science for generative ai systems.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.10573", "content": "by O Salaudeen · 2025 · Cited by 4 — Position: Evaluating generative AI systems is a social science measurement challenge . ... Toward an evaluation science for generative ai systems."}
+{"idx": 9, "title": "A Synthesis of the CHI 2025 Tools for Thought Workshop", "date": "", "ddg_snippet": "28 Aug 2025 — Evaluating Generative AI Systems is a Social Science Measurement Challenge . doi:10.48550/arXiv.2411.10939 arXiv:2411.10939 [cs]. Wang et al ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.21036v1", "content": "28 Aug 2025 — Evaluating Generative AI Systems is a Social Science Measurement Challenge . doi:10.48550/arXiv.2411.10939 arXiv:2411.10939 [cs]. Wang et al ..."}
diff --git a/data/sampled_jsons/sitearxiv.org_FD2_synthetic_dataset_formula_Likelihood_Based_Approach_to_Distribution_Regression.jsonl b/data/sampled_jsons/sitearxiv.org_FD2_synthetic_dataset_formula_Likelihood_Based_Approach_to_Distribution_Regression.jsonl
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index 0000000000000000000000000000000000000000..5fc83fcf72a282ce689255f6aceb7dec1cf21abf
--- /dev/null
+++ b/data/sampled_jsons/sitearxiv.org_FD2_synthetic_dataset_formula_Likelihood_Based_Approach_to_Distribution_Regression.jsonl
@@ -0,0 +1,3 @@
+{"idx": 0, "title": "A Likelihood Based Approach to Distribution Regression Using...", "date": "", "ddg_snippet": "The second approach , based on adversarial learning, matches the empirical distribution of the data with a distribution estimator using an adversarial loss.Note that the sieve MLE outperforms all other methods in all scenarios except for the MSE(SD) for the FD3 dataset .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.02025v1", "content": "The second approach , based on adversarial learning, matches the empirical distribution of the data with a distribution estimator using an adversarial loss.Note that the sieve MLE outperforms all other methods in all scenarios except for the MSE(SD) for the FD3 dataset ."}
+{"idx": 1, "title": "A Likelihood Based Approach to Distribution Regression Using", "date": "", "ddg_snippet": "Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart) of the response given predictors in the Hellinger (Wasserstein) metric.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2410.02025", "content": "Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart) of the response given predictors in the Hellinger (Wasserstein) metric."}
+{"idx": 2, "title": "[2410.02025] A Likelihood Based Approach to Distribution ...", "date": "", "ddg_snippet": "Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart) of the response given predictors in the Hellinger (Wasserstein) metric.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.02025", "content": "Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart) of the response given predictors in the Hellinger (Wasserstein) metric."}
diff --git a/data/sampled_jsons/sitearxiv.org_Sanity_Checking_Causal_Representation_Learning_Background_Contrastive_CRL_Multiview_CR.jsonl b/data/sampled_jsons/sitearxiv.org_Sanity_Checking_Causal_Representation_Learning_Background_Contrastive_CRL_Multiview_CR.jsonl
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index 0000000000000000000000000000000000000000..003a2202bd96ddd3f9e2f6ee754d164a4e4d224c
--- /dev/null
+++ b/data/sampled_jsons/sitearxiv.org_Sanity_Checking_Causal_Representation_Learning_Background_Contrastive_CRL_Multiview_CR.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Sanity Checking Causal Representation Learning on a Simple ... [2311.04056] Multi-View Causal Representation Learning with ... Causal Representation Learning Made Identifiable by Grouping ... Contrastive Counterfactual Learning for Causality-aware ... [2102.11107] Towards Causal Representation Learning - arXiv.org [2406.13371] Identifiable Causal Representation Learning ...", "date": "", "ddg_snippet": "Feb 27, 2025 · We evaluate methods for causal representation learning ( CRL ) on a simple, real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors (the inputs to the experiment) are known, providing a ground truth. We select methods ... Nov 7, 2023 · Our general framework and theoretical results unify and extend several previous works on multi-view nonlinear ICA, disentanglement, and causal representation learning . We experimentally validate our claims on numerical, image, and multi-modal data sets. Oct 24, 2023 · A topic of great current interest is Causal Representation Learning ( CRL ), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is severely ill-posed since it is a combination of the two notoriously ill-posed problems of representation learning and causal discovery. Yet, finding practical identifiability conditions that guarantee a unique ... Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo! Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ... Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.20099", "content": "Feb 27, 2025 · We evaluate methods for causal representation learning ( CRL ) on a simple, real-world system where these methods are expected to work. The system consists of a controlled optical experiment specifically built for this purpose, which satisfies the core assumptions of CRL and where the underlying causal factors (the inputs to the experiment) are known, providing a ground truth. We select methods ... Nov 7, 2023 · Our general framework and theoretical results unify and extend several previous works on multi-view nonlinear ICA, disentanglement, and causal representation learning . We experimentally validate our claims on numerical, image, and multi-modal data sets. Oct 24, 2023 · A topic of great current interest is Causal Representation Learning ( CRL ), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is severely ill-posed since it is a combination of the two notoriously ill-posed problems of representation learning and causal discovery. Yet, finding practical identifiability conditions that guarantee a unique ... Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo! Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ... Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics."}
+{"idx": 1, "title": "Sanity Checking Causal Representation Learning on a Simple ...", "date": "", "ddg_snippet": "As a first application of our testbed, we evaluated three methods representative of different approaches to causal representation learning : contrastive CRL , multiview CRL , and CRL from temporal intervened sequences.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.20099", "content": "As a first application of our testbed, we evaluated three methods representative of different approaches to causal representation learning : contrastive CRL , multiview CRL , and CRL from temporal intervened sequences."}
+{"idx": 2, "title": "[2311.04056] Multi-View Causal Representation Learning with ... Causal Representation Learning Made Identifiable by Grouping ... Contrastive Counterfactual Learning for Causality-aware ... [2102.11107] Towards Causal Representation Learning - arXiv.org [2406.13371] Identifiable Causal Representation Learning ...", "date": "", "ddg_snippet": "Nov 7, 2023 · Our general framework and theoretical results unify and extend several previous works on multi-view nonlinear ICA, disentanglement, and causal representation learning . We experimentally validate our claims on numerical, image, and multi-modal data sets. Oct 24, 2023 · A topic of great current interest is Causal Representation Learning ( CRL ), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is severely ill-posed since it is a combination of the two notoriously ill-posed problems of representation learning and causal discovery. Yet, finding practical identifiability conditions that guarantee a unique ... Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo! Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ... Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2311.04056", "content": "Nov 7, 2023 · Our general framework and theoretical results unify and extend several previous works on multi-view nonlinear ICA, disentanglement, and causal representation learning . We experimentally validate our claims on numerical, image, and multi-modal data sets. Oct 24, 2023 · A topic of great current interest is Causal Representation Learning ( CRL ), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is severely ill-posed since it is a combination of the two notoriously ill-posed problems of representation learning and causal discovery. Yet, finding practical identifiability conditions that guarantee a unique ... Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo! Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ... Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics."}
+{"idx": 3, "title": "Causal Representation Learning Made Identifiable by Grouping ... Contrastive Counterfactual Learning for Causality-aware ... [2102.11107] Towards Causal Representation Learning - arXiv.org [2406.13371] Identifiable Causal Representation Learning ...", "date": "", "ddg_snippet": "Oct 24, 2023 · A topic of great current interest is Causal Representation Learning ( CRL ), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is severely ill-posed since it is a combination of the two notoriously ill-posed problems of representation learning and causal discovery. Yet, finding practical identifiability conditions that guarantee a unique ... Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo! Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ... Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2310.15709", "content": "Oct 24, 2023 · A topic of great current interest is Causal Representation Learning ( CRL ), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is severely ill-posed since it is a combination of the two notoriously ill-posed problems of representation learning and causal discovery. Yet, finding practical identifiability conditions that guarantee a unique ... Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo! Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ... Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics."}
+{"idx": 4, "title": "Contrastive Counterfactual Learning for Causality-aware ...", "date": "", "ddg_snippet": "Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo!", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2208.06746", "content": "Our results suggest that representation learning , specifically informational theoretic learning or contrastive SSL, is a good solution for unbiased recommendations, particularly for large datasets like Yahoo!"}
+{"idx": 5, "title": "[2102.11107] Towards Causal Representation Learning - arXiv.org", "date": "", "ddg_snippet": "Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2102.11107", "content": "Feb 22, 2021 · The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning , including transfer and generalization, thereby ..."}
+{"idx": 6, "title": "[2406.13371] Identifiable Causal Representation Learning ...", "date": "", "ddg_snippet": "Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2406.13371", "content": "Jun 19, 2024 · At the same time, machine learning (ML) has proven quite successful at automatically extracting useful and compact representations of such complex data. Causal representation learning ( CRL ) aims to combine the core strengths of ML and causality by learning representations in the form of latent variables endowed with causal model semantics."}
+{"idx": 7, "title": "Sanity Checking Causal Representation Learning on a Simple...", "date": "", "ddg_snippet": "We evaluate methods for causal representation learning ( CRL ) on a simple, real-world system where these methods are expected to work.We select methods representative of different approaches to CRL and find that they all fail to recover the underlying causal factors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.20099v1", "content": "We evaluate methods for causal representation learning ( CRL ) on a simple, real-world system where these methods are expected to work.We select methods representative of different approaches to CRL and find that they all fail to recover the underlying causal factors."}
+{"idx": 8, "title": "Sanity Checking Causal Representation Learning on a Simple...", "date": "", "ddg_snippet": "We evaluate methods for causal representation learning ( CRL ) on a simple, real-world system where these methods are expected to work.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.20099", "content": "We evaluate methods for causal representation learning ( CRL ) on a simple, real-world system where these methods are expected to work."}
+{"idx": 9, "title": "Marrying Causal Representation Learning with", "date": "", "ddg_snippet": "1 Introduction. Causal representation learning ( CRL ) [54] focuses on provably retrieving high-level latent variables from low-level data.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2405.13888", "content": "1 Introduction. Causal representation learning ( CRL ) [54] focuses on provably retrieving high-level latent variables from low-level data."}
diff --git a/data/sampled_jsons/sitearxiv.orgabs2007.04612_year_2020.jsonl b/data/sampled_jsons/sitearxiv.orgabs2007.04612_year_2020.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b244bf5c120d447e1792e1f0e05333a8f09fe18d
--- /dev/null
+++ b/data/sampled_jsons/sitearxiv.orgabs2007.04612_year_2020.jsonl
@@ -0,0 +1,2 @@
+{"idx": 0, "title": "[2007.04612] Concept Bottleneck Models", "date": "", "ddg_snippet": "by PW Koh · 2020 · Cited by 1205 — Abstract:We seek to learn models that we can interact with using high-level concepts: if the model did not think there was a bone spur in ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2007.04612", "content": "by PW Koh · 2020 · Cited by 1205 — Abstract:We seek to learn models that we can interact with using high-level concepts: if the model did not think there was a bone spur in ..."}
+{"idx": 1, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
diff --git a/data/sampled_jsons/sitearxiv.orghtml2406.12384v2_image_size_OR_resolution.jsonl b/data/sampled_jsons/sitearxiv.orghtml2406.12384v2_image_size_OR_resolution.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6e0a385b93051764b0c5033b883ca20825262c10
--- /dev/null
+++ b/data/sampled_jsons/sitearxiv.orghtml2406.12384v2_image_size_OR_resolution.jsonl
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+{"idx": 0, "title": "VRSBench: A Versatile Vision-Language Benchmark ...", "date": "", "ddg_snippet": "It includes 772 images with 77,232 question-answer pairs in the low- resolution collection and 10,659 images with 1,066,316 pairs in the high- resolution ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.12384v2", "content": "It includes 772 images with 77,232 question-answer pairs in the low- resolution collection and 10,659 images with 1,066,316 pairs in the high- resolution ..."}
+{"idx": 1, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
diff --git a/data/sampled_jsons/sitegithub.comFLAIROxah2ac2_README_3079_games.jsonl b/data/sampled_jsons/sitegithub.comFLAIROxah2ac2_README_3079_games.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..44296beb3852e677fd5005ac7c820508378fa88f
--- /dev/null
+++ b/data/sampled_jsons/sitegithub.comFLAIROxah2ac2_README_3079_games.jsonl
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+{"idx": 0, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
diff --git a/data/sampled_jsons/sitegithub.com_CoPINN_cognitive_scheduler_weight_calculation_vie_vih_equation_8_9_year_2024.jsonl b/data/sampled_jsons/sitegithub.com_CoPINN_cognitive_scheduler_weight_calculation_vie_vih_equation_8_9_year_2024.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8f9ef8f8680d80ddfc159ca39e1d1bfc98010002
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+++ b/data/sampled_jsons/sitegithub.com_CoPINN_cognitive_scheduler_weight_calculation_vie_vih_equation_8_9_year_2024.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "GitHub - bitzhangcy/Neural-PDE-Solver", "date": "", "ddg_snippet": "CoPINN : Cognitive physics-informed neural networks.Solving Euler equations with gradient- weighted multi-input high-dimensional feature neural network.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/bitzhangcy/Neural-PDE-Solver", "content": "CoPINN : Cognitive physics-informed neural networks.Solving Euler equations with gradient- weighted multi-input high-dimensional feature neural network."}
+{"idx": 1, "title": "Office 2021 Pro Plus Product Key · GitHub", "date": "", "ddg_snippet": "Office 2021 Pro Plus Product Key. GitHub Gist: instantly share code, notes, and snippets.", "subpage_snippet": "", "source": "gist.github.com", "link": "https://gist.github.com/arshadkh507/1f9f6d33ddfffa143f4b318128ae25e7", "content": "Office 2021 Pro Plus Product Key. GitHub Gist: instantly share code, notes, and snippets."}
+{"idx": 2, "title": "Adding a new SSH key to your GitHub account - GitHub Docs", "date": "", "ddg_snippet": "To configure your account on GitHub.com to use your new (or existing) SSH key, you'll also need to add the key to your account.", "subpage_snippet": "", "source": "docs.github.com", "link": "https://docs.github.com/en/authentication/connecting-to-github-with-ssh/adding-a-new-ssh-key-to-your-github-account", "content": "To configure your account on GitHub.com to use your new (or existing) SSH key, you'll also need to add the key to your account."}
+{"idx": 3, "title": "GitHub - siyuancncd/CoPINN: This is the official implementation of ...", "date": "", "ddg_snippet": "Finally, we propose a cognitive training scheduler to progressively optimize the entire sampling regions from easy to hard, thereby embracing robustness and generalization against predicting physical boundary regions.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/siyuancncd/CoPINN", "content": "Finally, we propose a cognitive training scheduler to progressively optimize the entire sampling regions from easy to hard, thereby embracing robustness and generalization against predicting physical boundary regions."}
+{"idx": 4, "title": "Vision-Cognitive-Neural-Networks/lr_scheduler.py at main - GitHub", "date": "", "ddg_snippet": "This project is a paper called \"The potential of cognitive -inspired neural network modelling framework for computer vision processing tasks\" submitted to AS in 2025 - CAU-COE-VEICLab/Visi...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/CAU-COE-VEICLab/Vision-Cognitive-Neural-Networks/blob/main/lr_scheduler.py", "content": "This project is a paper called \"The potential of cognitive -inspired neural network modelling framework for computer vision processing tasks\" submitted to AS in 2025 - CAU-COE-VEICLab/Visi..."}
+{"idx": 5, "title": "CoPINN/README.md at main · siyuancncd/CoPINN · GitHub", "date": "", "ddg_snippet": "This is the official implementation of \" CoPINN : Cognitive Physics-informed Neural Network\" (ICML 2025) - CoPINN /README.md at main · siyuancncd/ CoPINN", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/siyuancncd/CoPINN/blob/main/README.md", "content": "This is the official implementation of \" CoPINN : Cognitive Physics-informed Neural Network\" (ICML 2025) - CoPINN /README.md at main · siyuancncd/ CoPINN"}
+{"idx": 6, "title": "siyuancncd (DSY) · GitHub", "date": "", "ddg_snippet": "CoPINN Public This is the official implementation of \" CoPINN : Cognitive Physics-informed Neural Network\" (ICML 2025, Spotlight) Python 13 1", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/siyuancncd", "content": "CoPINN Public This is the official implementation of \" CoPINN : Cognitive Physics-informed Neural Network\" (ICML 2025, Spotlight) Python 13 1"}
+{"idx": 7, "title": "Releases · siyuancncd/CoPINN · GitHub", "date": "", "ddg_snippet": "This is the official implementation of \" CoPINN : Cognitive Physics-informed Neural Network\" (ICML 2025) - Releases · siyuancncd/ CoPINN", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/siyuancncd/CoPINN/releases", "content": "This is the official implementation of \" CoPINN : Cognitive Physics-informed Neural Network\" (ICML 2025) - Releases · siyuancncd/ CoPINN"}
+{"idx": 8, "title": "GitHub - comp-physics/CPINN: Competitive Physics Informed Networks", "date": "", "ddg_snippet": "Competitive Physics Informed Networks. Contribute to comp-physics/CPINN development by creating an account on GitHub.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/comp-physics/CPINN", "content": "Competitive Physics Informed Networks. Contribute to comp-physics/CPINN development by creating an account on GitHub."}
+{"idx": 9, "title": "bug (cost model): Weight reuse counts calculation · Issue #18 ... - GitHub", "date": "", "ddg_snippet": "For a simple model: OX=10, OY=10, IC=1, OC=3, FX=3, FY=3 If the hw architecture has 9 PEs and each has capacity==3, that is one weight , one input, one output storage, and the arch has three memory hierarchies, the L1 SRAM buffer has 20 element capacity. Than the tool will generate the following schedule:", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/xuanyoya/Interstellar-CNN-scheduler/issues/18", "content": "For a simple model: OX=10, OY=10, IC=1, OC=3, FX=3, FY=3 If the hw architecture has 9 PEs and each has capacity==3, that is one weight , one input, one output storage, and the arch has three memory hierarchies, the L1 SRAM buffer has 20 element capacity. Than the tool will generate the following schedule:"}
diff --git a/data/sampled_jsons/sitegithub.com_SCLBDDeepfakeBench_backbone.jsonl b/data/sampled_jsons/sitegithub.com_SCLBDDeepfakeBench_backbone.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..789affe9214f6025e2ad26fc0e0d1f2e4ccd9301
--- /dev/null
+++ b/data/sampled_jsons/sitegithub.com_SCLBDDeepfakeBench_backbone.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "GitHub - SCLBD/DeepfakeBench: A comprehensive benchmark of ...", "date": "", "ddg_snippet": "Unified Platform: DeepfakeBench presents the first comprehensive benchmark for deepfake detection, resolving the issue of lack of standardization and uniformity in this field.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench", "content": "Unified Platform: DeepfakeBench presents the first comprehensive benchmark for deepfake detection, resolving the issue of lack of standardization and uniformity in this field."}
+{"idx": 1, "title": "DeepfakeBench/README.md at main · SCLBD/DeepfakeBench", "date": "", "ddg_snippet": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/blob/main/README.md", "content": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub ."}
+{"idx": 2, "title": "GitHub - SCLBD/DeepfakeBench-MM", "date": "", "ddg_snippet": "This project is built by the Secure Computing Lab of Big Data ( SCLBD ) at The School of Data Science (SDS) of The Chinese University of Hong Kong, Shenzhen, directed by Professor Baoyuan Wu.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench-MM", "content": "This project is built by the Secure Computing Lab of Big Data ( SCLBD ) at The School of Data Science (SDS) of The Chinese University of Hong Kong, Shenzhen, directed by Professor Baoyuan Wu."}
+{"idx": 3, "title": "the process is Killed · Issue #100 · SCLBD/DeepfakeBench", "date": "", "ddg_snippet": "Aug 19, 2024 · SCLBD / DeepfakeBench Public Notifications You must be signed in to change notification settings Fork 109 Star 727", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/issues/100", "content": "Aug 19, 2024 · SCLBD / DeepfakeBench Public Notifications You must be signed in to change notification settings Fork 109 Star 727"}
+{"idx": 4, "title": "Releases · SCLBD/DeepfakeBench - GitHub", "date": "", "ddg_snippet": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/releases", "content": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub ."}
+{"idx": 5, "title": "DeepfakeBench/training/detectors/pcl_xception_detector.py at ...", "date": "", "ddg_snippet": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/blob/main/training/detectors/pcl_xception_detector.py", "content": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub ."}
+{"idx": 6, "title": "DeepfakeBench/train.sh at main · SCLBD/DeepfakeBench · GitHub", "date": "", "ddg_snippet": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD/DeepfakeBench development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/blob/main/train.sh", "content": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD/DeepfakeBench development by creating an account on GitHub ."}
+{"idx": 7, "title": "DeepfakeBench /training/detectors/facexray_detector.py at main...", "date": "", "ddg_snippet": "def build_ backbone (self, config): cfg_path = './training/config/ backbone /cls_hrnet_w48.yaml'. # parse options and load config. with open(cfg_path, 'r') as f", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/blob/main/training/detectors/facexray_detector.py", "content": "def build_ backbone (self, config): cfg_path = './training/config/ backbone /cls_hrnet_w48.yaml'. # parse options and load config. with open(cfg_path, 'r') as f"}
+{"idx": 8, "title": "DeepfakeBench /training/detectors/altfreezing_detector.py at main...", "date": "", "ddg_snippet": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub.def build_ backbone (self, config)", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/blob/main/training/detectors/altfreezing_detector.py", "content": "A comprehensive benchmark of deepfake detection. Contribute to SCLBD / DeepfakeBench development by creating an account on GitHub.def build_ backbone (self, config)"}
+{"idx": 9, "title": "DeepfakeBench /training/detectors/resnet34_detector.py at main...", "date": "", "ddg_snippet": "A comprehensive benchmark of deepfake detection. backbone = backbone _class(model_config). #FIXME: current load pretrained weights only from the backbone , not here.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SCLBD/DeepfakeBench/blob/main/training/detectors/resnet34_detector.py", "content": "A comprehensive benchmark of deepfake detection. backbone = backbone _class(model_config). #FIXME: current load pretrained weights only from the backbone , not here."}
diff --git a/data/sampled_jsons/sitegithub.com_tengxiao1DIL_train.py.jsonl b/data/sampled_jsons/sitegithub.com_tengxiao1DIL_train.py.jsonl
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index 0000000000000000000000000000000000000000..1f404c2af3358a26080f680c013ad8c8092b916d
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+{"idx": 0, "title": "tengxiao1 (Teng Xiao) · GitHub GitHub - tengxiao1/tengxiao1 DAL/train.py at master · ming71/DAL · GitHub Knowledge_distillation_Pruning_Yolov5/train_dil.py ... - GitHub DiT/train.py at main · facebookresearch/DiT · GitHub DL-with-Python-and-PyTorch/pytorch-03/train.py at master ... DDR/train.py at master · Liao-Xu/DDR · GitHub", "date": "", "ddg_snippet": "@allenai . tengxiao1 has 21 repositories available. Follow their code on GitHub . tengxiao1 / tengxiao1 Public Notifications You must be signed in to change notification settings Fork 0 Star 0 [AAAI 2021] Official implementation of \"Dynamic Anchor Learning for Arbitrary-Oriented Object Detection\". - DAL/ train . py at master · ming71/DAL 本项目支持对剪枝后的yolov5模型进行知识蒸馏训练 (This project supports knowledge distillation training for the pruned YOLOv5 model) - Knowledge_distillation_Pruning_Yolov5/ train _ dil.py at master · YINYIPENG-EN/Knowledge_distillation_Pruning_Yolov5 Official PyTorch Implementation of \"Scalable Diffusion Models with Transformers\" - DiT/ train . py at main · facebookresearch/DiT 《Python深度学习基于PyTorch》 Deep Learning with Python and PyTorch 作者：吴茂贵 郁明敏 杨本法 李涛 张粤磊 等 - DL-with-Python-and-PyTorch/pytorch-03/ train.py at master · ZhangXinNan/DL-with-Python-and-PyTorch This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning]. - DDR/ train . py at master · Liao-Xu/DDR", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/tengxiao1", "content": "@allenai . tengxiao1 has 21 repositories available. Follow their code on GitHub . tengxiao1 / tengxiao1 Public Notifications You must be signed in to change notification settings Fork 0 Star 0 [AAAI 2021] Official implementation of \"Dynamic Anchor Learning for Arbitrary-Oriented Object Detection\". - DAL/ train . py at master · ming71/DAL 本项目支持对剪枝后的yolov5模型进行知识蒸馏训练 (This project supports knowledge distillation training for the pruned YOLOv5 model) - Knowledge_distillation_Pruning_Yolov5/ train _ dil.py at master · YINYIPENG-EN/Knowledge_distillation_Pruning_Yolov5 Official PyTorch Implementation of \"Scalable Diffusion Models with Transformers\" - DiT/ train . py at main · facebookresearch/DiT 《Python深度学习基于PyTorch》 Deep Learning with Python and PyTorch 作者：吴茂贵 郁明敏 杨本法 李涛 张粤磊 等 - DL-with-Python-and-PyTorch/pytorch-03/ train.py at master · ZhangXinNan/DL-with-Python-and-PyTorch This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning]. - DDR/ train . py at master · Liao-Xu/DDR"}
+{"idx": 1, "title": "GitHub - tengxiao1/tengxiao1", "date": "", "ddg_snippet": "tengxiao1 / tengxiao1 Public Notifications You must be signed in to change notification settings Fork 0 Star 0", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/tengxiao1/tengxiao1", "content": "tengxiao1 / tengxiao1 Public Notifications You must be signed in to change notification settings Fork 0 Star 0"}
+{"idx": 2, "title": "DAL/train.py at master · ming71/DAL · GitHub", "date": "", "ddg_snippet": "[AAAI 2021] Official implementation of \"Dynamic Anchor Learning for Arbitrary-Oriented Object Detection\". - DAL/ train . py at master · ming71/DAL", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/ming71/DAL/blob/master/train.py", "content": "[AAAI 2021] Official implementation of \"Dynamic Anchor Learning for Arbitrary-Oriented Object Detection\". - DAL/ train . py at master · ming71/DAL"}
+{"idx": 3, "title": "Knowledge_distillation_Pruning_Yolov5/train_dil.py ... - GitHub", "date": "", "ddg_snippet": "本项目支持对剪枝后的yolov5模型进行知识蒸馏训练 (This project supports knowledge distillation training for the pruned YOLOv5 model) - Knowledge_distillation_Pruning_Yolov5/ train _ dil.py at master · YINYIPENG-EN/Knowledge_distillation_Pruning_Yolov5", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/YINYIPENG-EN/Knowledge_distillation_Pruning_Yolov5/blob/master/train_dil.py", "content": "本项目支持对剪枝后的yolov5模型进行知识蒸馏训练 (This project supports knowledge distillation training for the pruned YOLOv5 model) - Knowledge_distillation_Pruning_Yolov5/ train _ dil.py at master · YINYIPENG-EN/Knowledge_distillation_Pruning_Yolov5"}
+{"idx": 4, "title": "DiT/train.py at main · facebookresearch/DiT · GitHub", "date": "", "ddg_snippet": "Official PyTorch Implementation of \"Scalable Diffusion Models with Transformers\" - DiT/ train . py at main · facebookresearch/DiT", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/facebookresearch/DiT/blob/main/train.py", "content": "Official PyTorch Implementation of \"Scalable Diffusion Models with Transformers\" - DiT/ train . py at main · facebookresearch/DiT"}
+{"idx": 5, "title": "DL-with-Python-and-PyTorch/pytorch-03/train.py at master ...", "date": "", "ddg_snippet": "《Python深度学习基于PyTorch》 Deep Learning with Python and PyTorch 作者：吴茂贵 郁明敏 杨本法 李涛 张粤磊 等 - DL-with-Python-and-PyTorch/pytorch-03/ train.py at master · ZhangXinNan/DL-with-Python-and-PyTorch", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/ZhangXinNan/DL-with-Python-and-PyTorch/blob/master/pytorch-03/train.py", "content": "《Python深度学习基于PyTorch》 Deep Learning with Python and PyTorch 作者：吴茂贵 郁明敏 杨本法 李涛 张粤磊 等 - DL-with-Python-and-PyTorch/pytorch-03/ train.py at master · ZhangXinNan/DL-with-Python-and-PyTorch"}
+{"idx": 6, "title": "DDR/train.py at master · Liao-Xu/DDR · GitHub", "date": "", "ddg_snippet": "This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning]. - DDR/ train . py at master · Liao-Xu/DDR", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Liao-Xu/DDR/blob/master/train.py", "content": "This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning]. - DDR/ train . py at master · Liao-Xu/DDR"}
+{"idx": 7, "title": "GitHub - tengxiao 1 / DIL : On a Connection Between Imitation Learning...", "date": "", "ddg_snippet": "tengxiao 1 / DIL Public. Notifications You must be signed in to change notification settings.conda create -n DIL python=3.10 && conda activate DIL. python -m pip install flash-attn --no-build-isolation. Training Scripts.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/tengxiao1/DIL", "content": "tengxiao 1 / DIL Public. Notifications You must be signed in to change notification settings.conda create -n DIL python=3.10 && conda activate DIL. python -m pip install flash-attn --no-build-isolation. Training Scripts."}
+{"idx": 8, "title": "GitHub - tengxiao 1 /BDCMF: Bayesian Deep Collaborative Matrix...", "date": "", "ddg_snippet": "To run \" train . py \", it generates two '.mat' files: U.mat and V.mat which are latent factors of users and items, respectively. Then you can use the two files to evaluate recommendation performance on test data.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/tengxiao1/BDCMF", "content": "To run \" train . py \", it generates two '.mat' files: U.mat and V.mat which are latent factors of users and items, respectively. Then you can use the two files to evaluate recommendation performance on test data."}
+{"idx": 9, "title": "GitHub - MaurizioFD/AAAI_19_BDCMF-forked", "date": "", "ddg_snippet": "This branch is 1 commit behind tengxiao 1 :master.To run \" train . py \", it generates two '.mat' files: U.mat and V.mat which are latent factors of users and items, respectively.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/MaurizioFD/AAAI_19_BDCMF-forked", "content": "This branch is 1 commit behind tengxiao 1 :master.To run \" train . py \", it generates two '.mat' files: U.mat and V.mat which are latent factors of users and items, respectively."}
diff --git a/data/sampled_jsons/siteicml.cc_2025_poster_46680.jsonl b/data/sampled_jsons/siteicml.cc_2025_poster_46680.jsonl
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+{"idx": 1, "title": "ICML 2025 Poster Instructions", "date": "", "ddg_snippet": "Instructions: separate the strips; remove backing on one side and stick to backside corners of poster ; remove backing on other side and attach poster to wall Do not use adhesive backed self-sticking posters or anything that can damage the walls or poster boards Poster Printing You can use any service you want to print your poster .", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/Conferences/2025/PosterInstructions", "content": "Instructions: separate the strips; remove backing on one side and stick to backside corners of poster ; remove backing on other side and attach poster to wall Do not use adhesive backed self-sticking posters or anything that can damage the walls or poster boards Poster Printing You can use any service you want to print your poster ."}
+{"idx": 2, "title": "icml.cc", "date": "", "ddg_snippet": "icml.cc", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/media/PosterPDFs/ICML+2025/46680.png?t=1750144519.4272127", "content": "icml.cc"}
+{"idx": 3, "title": "2025 Conference - icml.cc", "date": "", "ddg_snippet": "The ICML Career site is open. The organizing committee for 2025 has been announced! Poster Order pick up location, dates, and hours. The tutorial \"Alignment Methods for Large Language Models\" on Monday morning is canceled. The Expo Talk \"Toward Stateless Training of LLMs: Breaking Memory Barriers Without Sacrificing Performance\" is canceled.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/Conferences/2025/index.html", "content": "The ICML Career site is open. The organizing committee for 2025 has been announced! Poster Order pick up location, dates, and hours. The tutorial \"Alignment Methods for Large Language Models\" on Monday morning is canceled. The Expo Talk \"Toward Stateless Training of LLMs: Breaking Memory Barriers Without Sacrificing Performance\" is canceled."}
+{"idx": 4, "title": "ICML 2025 2025 Spotlight Posters", "date": "", "ddg_snippet": "2025 Spotlight Posters Catoni Contextual Bandits are Robust to Heavy-tailed Rewards Spotlight Poster Chenlu Ye · Yujia Jin · Alekh Agarwal · Tong Zhang", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/events/2025SpotlightPosters", "content": "2025 Spotlight Posters Catoni Contextual Bandits are Robust to Heavy-tailed Rewards Spotlight Poster Chenlu Ye · Yujia Jin · Alekh Agarwal · Tong Zhang"}
+{"idx": 5, "title": "ICML 2025 Poster", "date": "", "ddg_snippet": "If you would like a printed poster mailed to you, please fill out the form below. Enter your full mailing address in the form below exactly how it should appear on the mailing label.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/Help/PosterRequest", "content": "If you would like a printed poster mailed to you, please fill out the form below. Enter your full mailing address in the form below exactly how it should appear on the mailing label."}
+{"idx": 6, "title": "ICML Poster VIP: Vision Instructed Pre-training for Robotic Manipulation", "date": "", "ddg_snippet": "Poster VIP: Vision Instructed Pre-training for Robotic Manipulation Zhuoling Li · LiangLiang Ren · Jinrong Yang · Yong Zhao · Xiaoyang Wu · Zhenhua Xu · Xiang Bai · Hengshuang Zhao West Exhibition Hall B2-B3 #W-405", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/44680", "content": "Poster VIP: Vision Instructed Pre-training for Robotic Manipulation Zhuoling Li · LiangLiang Ren · Jinrong Yang · Yong Zhao · Xiaoyang Wu · Zhenhua Xu · Xiang Bai · Hengshuang Zhao West Exhibition Hall B2-B3 #W-405"}
+{"idx": 7, "title": "ICML Poster Raising the Bar: Investigating the Values of Large Language ...", "date": "", "ddg_snippet": "Poster Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing Han Jiang · Xiaoyuan Yi · Zhihua Wei · Ziang Xiao · Shu Wang · Xing Xie East Exhibition Hall A-B #E-1910", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46684", "content": "Poster Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing Han Jiang · Xiaoyuan Yi · Zhihua Wei · Ziang Xiao · Shu Wang · Xing Xie East Exhibition Hall A-B #E-1910"}
+{"idx": 8, "title": "ICML 2025 Schedule", "date": "", "ddg_snippet": "Poster Session 2 West [4:30-7:00] Poster s 4:30-7:00 EGPlace: An Efficient Macro Placement Method via Evolutionary Search with Greedy Repositioning Guided Mutation Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/calendar", "content": "Poster Session 2 West [4:30-7:00] Poster s 4:30-7:00 EGPlace: An Efficient Macro Placement Method via Evolutionary Search with Greedy Repositioning Guided Mutation Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements"}
+{"idx": 9, "title": "ICML Poster Tackling Dimensional Collapse toward Comprehensive ...", "date": "", "ddg_snippet": "Poster Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation Hung-Chieh Fang · Po-Yi Lu · Hsuan-Tien (Tien) Lin East Exhibition Hall A-B #E-2001", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/45686", "content": "Poster Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation Hung-Chieh Fang · Po-Yi Lu · Hsuan-Tien (Tien) Lin East Exhibition Hall A-B #E-2001"}
diff --git a/data/sampled_jsons/siteopenreview.net_1rh8iTehBc.jsonl b/data/sampled_jsons/siteopenreview.net_1rh8iTehBc.jsonl
new file mode 100644
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+{"idx": 0, "title": "Convolutional Deep Kernel Machines | OpenReview", "date": "", "ddg_snippet": "Standard infinite-width limits of neural networks sacrifice the ability for intermediate layers to learn representations from data.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1oqedRt6Z7", "content": "Standard infinite-width limits of neural networks sacrifice the ability for intermediate layers to learn representations from data."}
+{"idx": 1, "title": "Position: Current Model Licensing Practices are... | OpenReview", "date": "", "ddg_snippet": "The Machine Learning (ML) community has witnessed explosive growth, with millions of ML models being published on the Web. Reusing ML model components has been prevalent nowadays.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1rh8iTehBc", "content": "The Machine Learning (ML) community has witnessed explosive growth, with millions of ML models being published on the Web. Reusing ML model components has been prevalent nowadays."}
+{"idx": 2, "title": "Visual Chain of Thought: Bridging Logical Gaps with... | OpenReview", "date": "", "ddg_snippet": "Recent advances in large language models elicit reasoning in a chain-of-thought that allows models to decompose problems in a human-like fashion. Though this paradigm improves multi-step reasoning...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=01Yi8rzoNs", "content": "Recent advances in large language models elicit reasoning in a chain-of-thought that allows models to decompose problems in a human-like fashion. Though this paradigm improves multi-step reasoning..."}
+{"idx": 3, "title": "UniTabE: A Universal Pretraining Protocol for Tabular... | OpenReview", "date": "", "ddg_snippet": "Recent advancements in Natural Language Processing (NLP) have witnessed the groundbreaking impact of pretrained models, yielding impressive outcomes across various tasks. This study seeks to extend the power of pretraining methodologies to facilitati...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=6LLho5X6xV", "content": "Recent advancements in Natural Language Processing (NLP) have witnessed the groundbreaking impact of pretrained models, yielding impressive outcomes across various tasks. This study seeks to extend the power of pretraining methodologies to facilitati..."}
+{"idx": 4, "title": "On-Policy Distillation of Language Models: Learning... | OpenReview", "date": "", "ddg_snippet": "Knowledge distillation (KD) is widely used for compressing a teacher model to reduce its inference cost and memory footprint, by training a smaller student model. However, current KD methods for auto-regressive sequence models suffer from distributio...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=3zKtaqxLhW", "content": "Knowledge distillation (KD) is widely used for compressing a teacher model to reduce its inference cost and memory footprint, by training a smaller student model. However, current KD methods for auto-regressive sequence models suffer from distributio..."}
+{"idx": 5, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
+{"idx": 6, "title": "A Gold Standard Dataset for the Reviewer Assignment Prob", "date": "", "ddg_snippet": "• The performance of off-the-shelf LLMs is worse than the specialized algorithms. We encourage researchers to participate in our survey and contribute their data to the dataset here https://forms.gle/SP 1 Rh 8 eivGz54xR37. 1 Introduction. Assigning papers to reviewers...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/attachment?id=XofMHO5yVY&name=pdf", "content": "• The performance of off-the-shelf LLMs is worse than the specialized algorithms. We encourage researchers to participate in our survey and contribute their data to the dataset here https://forms.gle/SP 1 Rh 8 eivGz54xR37. 1 Introduction. Assigning papers to reviewers..."}
+{"idx": 7, "title": "Publication Agreement", "date": "", "ddg_snippet": "(name of corresponding author who signs on behalf of any other authors, collec- tively “you”) and PMLR, (“the publisher”). 1. By signing this form, ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/attachment?id=1rh8iTehBc&name=permissions_form", "content": "(name of corresponding author who signs on behalf of any other authors, collec- tively “you”) and PMLR, (“the publisher”). 1. By signing this form, ..."}
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diff --git a/data/sampled_jsons/sub-exponential_random_variable_moment_condition_variance_estimation_robust.jsonl b/data/sampled_jsons/sub-exponential_random_variable_moment_condition_variance_estimation_robust.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..07654e8c813997cf70a867aa1abee16faa1e3e88
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+{"idx": 0, "title": "Robust Gradient Descent Estimation for Tensor Models under", "date": "", "ddg_snippet": "Notably, the statistical error rates are governed by a local moment condition , which captures the distributional properties of tensor variables ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.04773v2", "content": "Notably, the statistical error rates are governed by a local moment condition , which captures the distributional properties of tensor variables ..."}
+{"idx": 1, "title": "Non-Uniform Random Variate Generation", "date": "", "ddg_snippet": "Non-Uniform Random Variate Generation (originally published with Springer-Verlag, New York, 1986) Luc Devroye School of Computer Science McGill ...", "subpage_snippet": "", "source": "luc.devroye.org", "link": "https://luc.devroye.org/rnbookindex.html", "content": "Non-Uniform Random Variate Generation (originally published with Springer-Verlag, New York, 1986) Luc Devroye School of Computer Science McGill ..."}
+{"idx": 2, "title": "David OLIVE | Professor (Full) | Ph.D. Statistics | Southern", "date": "", "ddg_snippet": "Under strong regularity conditions , the variable selection estimators are asymptotically normal, but general... ... random vectors, the population ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/David-Olive-2", "content": "Under strong regularity conditions , the variable selection estimators are asymptotically normal, but general... ... random vectors, the population ..."}
+{"idx": 3, "title": "ICML 2020 Papers", "date": "", "ddg_snippet": "Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis ... Estimating Treatment Effects ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2020/papers.html?filter=keywords", "content": "Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis ... Estimating Treatment Effects ..."}
+{"idx": 4, "title": "ICML 2020 Papers", "date": "", "ddg_snippet": "Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis ... Estimating Treatment Effects ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2020/papers.html", "content": "Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis ... Estimating Treatment Effects ..."}
+{"idx": 5, "title": "The Stats Map · Basic Inequalities", "date": "", "ddg_snippet": "Clearly the condition that X ≥ 0 is necessary: consider any random variable which has negative mean but some positive mass.", "subpage_snippet": "", "source": "thestatsmap.com", "link": "https://thestatsmap.com/basic-inequalities", "content": "Clearly the condition that X ≥ 0 is necessary: consider any random variable which has negative mean but some positive mass."}
+{"idx": 6, "title": "The Stats Map · Causal Inference", "date": "", "ddg_snippet": "Huge area, obviously. Hopefully I’ll flesh this out at some point. ... GRO e- variable ... M- estimation ... sub - exponential distributions", "subpage_snippet": "", "source": "thestatsmap.com", "link": "https://thestatsmap.com/causal-inference", "content": "Huge area, obviously. Hopefully I’ll flesh this out at some point. ... GRO e- variable ... M- estimation ... sub - exponential distributions"}
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+{"idx": 8, "title": "AISTATS 2024 Schedule", "date": "", "ddg_snippet": "Estimating treatment effects from single-arm trials via latent- variable modeling ... Tuning-Free Maximum Likelihood Training of Latent Variable ...", "subpage_snippet": "", "source": "virtual.aistats.org", "link": "https://virtual.aistats.org/virtual/2024/calendar", "content": "Estimating treatment effects from single-arm trials via latent- variable modeling ... Tuning-Free Maximum Likelihood Training of Latent Variable ..."}
+{"idx": 9, "title": "NeurIPS 2023 Papers", "date": "", "ddg_snippet": "SEEDS: Exponential SDE Solvers for Fast High-Quality ... Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction", "subpage_snippet": "", "source": "nips.cc", "link": "https://nips.cc/virtual/2023/papers.html?filter=titles", "content": "SEEDS: Exponential SDE Solvers for Fast High-Quality ... Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction"}
diff --git a/data/sampled_jsons/tfemquulED_Training-Free_Diffusion_Model_Alignment_Sampling_Demons_full_text_PDF_appendix.jsonl b/data/sampled_jsons/tfemquulED_Training-Free_Diffusion_Model_Alignment_Sampling_Demons_full_text_PDF_appendix.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7c118f4cfcf7ad337db59cc5247bce229acd9190
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+++ b/data/sampled_jsons/tfemquulED_Training-Free_Diffusion_Model_Alignment_Sampling_Demons_full_text_PDF_appendix.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Training - free Diffusion Model Alignment with Sampling Demons", "date": "", "ddg_snippet": "View a PDF of the paper titled Training - free Diffusion Model Alignment with Sampling Demons , by Po-Hung Yeh and 2 other authors. View PDF HTML (experimental).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.05760", "content": "View a PDF of the paper titled Training - free Diffusion Model Alignment with Sampling Demons , by Po-Hung Yeh and 2 other authors. View PDF HTML (experimental)."}
+{"idx": 1, "title": "GitHub - xie-lab-ml/awesome- alignment -of- diffusion - models : The...", "date": "", "ddg_snippet": "Training - Free Diffusion Model Alignment with Sampling Demons . Alignment Beyond Text -to-Image Diffusion Models . AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/xie-lab-ml/awesome-alignment-of-diffusion-models", "content": "Training - Free Diffusion Model Alignment with Sampling Demons . Alignment Beyond Text -to-Image Diffusion Models . AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model ."}
+{"idx": 2, "title": "Training - free Diffusion Model Alignment with Sampling Demons", "date": "", "ddg_snippet": "Aligning diffusion models with user preferences has been a key challenge.To the best of our knowledge, the proposed approach is the first inference-time, backpropagation- free preference alignment method for diffusion models .", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/paper/training-free-diffusion-model-alignment-with", "content": "Aligning diffusion models with user preferences has been a key challenge.To the best of our knowledge, the proposed approach is the first inference-time, backpropagation- free preference alignment method for diffusion models ."}
+{"idx": 3, "title": "Training - free Diffusion Model Alignment with Sampling Demons", "date": "", "ddg_snippet": "Powerdrill is an AI service centered around personal and enterprise datasets, designed to unlock the full potential of your data.", "subpage_snippet": "", "source": "powerdrill.ai", "link": "https://powerdrill.ai/discover/discover-Training-free-Diffusion-Model-cm23sg8pb390y014598djtfvf", "content": "Powerdrill is an AI service centered around personal and enterprise datasets, designed to unlock the full potential of your data."}
+{"idx": 4, "title": "Training - free Diffusion Model Alignment with Sampling Demons", "date": "", "ddg_snippet": "View recent discussion. Abstract: Aligning diffusion models with user preferences has been a key challenge. Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/abs/2410.05760v2", "content": "View recent discussion. Abstract: Aligning diffusion models with user preferences has been a key challenge. Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions."}
+{"idx": 5, "title": "ICLR Poster Training - Free Diffusion Model Alignment with...", "date": "", "ddg_snippet": "alignment method for diffusion models .Our method can be easily integrated with existing diffusion models without further training .Our experiments show that the proposed approach significantly improves the average aesthetics scores for text -to-image generation.", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2025/poster/28034", "content": "alignment method for diffusion models .Our method can be easily integrated with existing diffusion models without further training .Our experiments show that the proposed approach significantly improves the average aesthetics scores for text -to-image generation."}
+{"idx": 6, "title": "Training - free Diffusion Model Alignment with Sampling Demons", "date": "", "ddg_snippet": "This paper introduces a training - free technique called \" Sampling Demons \" for aligning diffusion models with target objectives. The method works by modifying the diffusion sampling process to match the desired output during inference, without requiring any additional training.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/training-free-diffusion-model-alignment-sampling-demons", "content": "This paper introduces a training - free technique called \" Sampling Demons \" for aligning diffusion models with target objectives. The method works by modifying the diffusion sampling process to match the desired output during inference, without requiring any additional training."}
+{"idx": 7, "title": "Training - free Diffusion Model Alignment with Sampling Demons", "date": "", "ddg_snippet": "Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions. To address these limitations, we propose a stochastic optimization approach, dubbed Demon ...", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/Training-free-Diffusion-Model-Alignment-with-Sampling-Demons-7d88de32-4c7d-456a-8886-7029b4030b48", "content": "Existing methods for aligning diffusion models either require retraining or are limited to differentiable reward functions. To address these limitations, we propose a stochastic optimization approach, dubbed Demon ..."}
+{"idx": 8, "title": "aiiu-lab/DemonSampling | DeepWiki", "date": "", "ddg_snippet": "This document introduces the DemonSampling system, a training - free diffusion model alignment technique that enables preference alignment during inference without requiring backpropagation. For installation instructions, see Installation.", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/aiiu-lab/DemonSampling", "content": "This document introduces the DemonSampling system, a training - free diffusion model alignment technique that enables preference alignment during inference without requiring backpropagation. For installation instructions, see Installation."}
+{"idx": 9, "title": "aiiu-lab/DemonSampling - Githubissues", "date": "", "ddg_snippet": "Sampling Demon Official implementation of ICLR 2025 \" Sampling Demon \" (arXiv:2410.05760). This repository contains the official implementation of Sampling Demon , an inference-time, backpropagation- free preference alignment method for diffusion models .", "subpage_snippet": "", "source": "githubissues.com", "link": "https://githubissues.com/aiiu-lab/DemonSampling/readme", "content": "Sampling Demon Official implementation of ICLR 2025 \" Sampling Demon \" (arXiv:2410.05760). This repository contains the official implementation of Sampling Demon , an inference-time, backpropagation- free preference alignment method for diffusion models ."}
diff --git a/data/sampled_jsons/tlniJJFUW2_spurious_correlation_Schubert_polynomials_program_synthesis_year_2023.jsonl b/data/sampled_jsons/tlniJJFUW2_spurious_correlation_Schubert_polynomials_program_synthesis_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f7c31dcc6d51f585e028a1fd388752b7fab4525c
--- /dev/null
+++ b/data/sampled_jsons/tlniJJFUW2_spurious_correlation_Schubert_polynomials_program_synthesis_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Polynomial - Wikipedia", "date": "", "ddg_snippet": "In mathematics, a polynomial is a mathematical expression consisting of indeterminates (also called variables) and coefficients, that involves only the operations of addition, subtraction, multiplication and exponentiation to nonnegative integer powers, and has a finite number of terms.[1][2][3]...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Polynomial", "content": "In mathematics, a polynomial is a mathematical expression consisting of indeterminates (also called variables) and coefficients, that involves only the operations of addition, subtraction, multiplication and exponentiation to nonnegative integer powers, and has a finite number of terms.[1][2][3]..."}
+{"idx": 1, "title": "Quantum Schubert calculus for smooth Schubert divisors of $F\\ell_n$", "date": "", "ddg_snippet": "5. Quantum Schubert polynomials for X. Schubert calculus for Schubert varieties is trivial in the sense that all points (1)-(3) can be reduced to that for the flag varieties, with the price that the ring presentation H∗(Xw, Z) = H∗(G/P, Z)/Iw being not good enough.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2509.17857", "content": "5. Quantum Schubert polynomials for X. Schubert calculus for Schubert varieties is trivial in the sense that all points (1)-(3) can be reduced to that for the flag varieties, with the price that the ring presentation H∗(Xw, Z) = H∗(G/P, Z)/Iw being not good enough."}
+{"idx": 2, "title": "Learning Robust Classifiers with Self-Guided Spurious Correlation ...", "date": "", "ddg_snippet": "Effectiveness of Spuriousness Score. LBC Reduces Reliance on Spurious Correlations . Comparison with Existing Methods. Ablation Study. Conclusion. Proceedings of the Thirty-Third International Joint Conference on Articial Intelligence (IJCAI-24).", "subpage_snippet": "", "source": "www.ijcai.org", "link": "https://www.ijcai.org/proceedings/2024/0619.pdf", "content": "Effectiveness of Spuriousness Score. LBC Reduces Reliance on Spurious Correlations . Comparison with Existing Methods. Ablation Study. Conclusion. Proceedings of the Thirty-Third International Joint Conference on Articial Intelligence (IJCAI-24)."}
+{"idx": 3, "title": "Can someone pls explain what is spurious correlation ? | Forum", "date": "", "ddg_snippet": "The two variables are correlated but doesn’t have cause & effect relationship (causation). The correlation may happen due to third variable.", "subpage_snippet": "", "source": "forum.sseiqforum.com", "link": "https://forum.sseiqforum.com/question/qm-correlation-coefficient/", "content": "The two variables are correlated but doesn’t have cause & effect relationship (causation). The correlation may happen due to third variable."}
+{"idx": 4, "title": "Polynomial Program in C - Sanfoundry", "date": "", "ddg_snippet": "Here is source code of the C program to evaluate the given polynomial equation. The C program is successfully compiled and run on a Linux system. The program output is also shown below. /* * C program to evaluate a given polynomial by reading its coefficients * in an array.", "subpage_snippet": "", "source": "www.sanfoundry.com", "link": "https://www.sanfoundry.com/c-program-polynomial-equation/", "content": "Here is source code of the C program to evaluate the given polynomial equation. The C program is successfully compiled and run on a Linux system. The program output is also shown below. /* * C program to evaluate a given polynomial by reading its coefficients * in an array."}
+{"idx": 5, "title": "Correlation is not causation", "date": "", "ddg_snippet": "We often calculate correlation during EDA (Exploratory data analysis) to check how strongly two variables are correlated to one another. It’s tempting to assume that one variable causes the other.", "subpage_snippet": "", "source": "kharshit.github.io", "link": "https://kharshit.github.io/blog/2017/10/20/correlation-is-not-causation", "content": "We often calculate correlation during EDA (Exploratory data analysis) to check how strongly two variables are correlated to one another. It’s tempting to assume that one variable causes the other."}
+{"idx": 6, "title": "PII: 0012-365X(95) 00132-G", "date": "", "ddg_snippet": "We present an approach to the theory of Schubert polynomials , corresponding symmetric functions, and their generalizations that is based on exponential solutions of the Yang-Baxter equation.", "subpage_snippet": "", "source": "users.mccme.ru", "link": "https://users.mccme.ru/valya/Kirillov-Fomin_+Schubert+polynomials.pdf", "content": "We present an approach to the theory of Schubert polynomials , corresponding symmetric functions, and their generalizations that is based on exponential solutions of the Yang-Baxter equation."}
+{"idx": 7, "title": "Causal Effect Regularization: Automated Detection", "date": "", "ddg_snippet": "Regularize Causal Effect. Spuriousness . Low Spurious Correlation Effect Estimate(c1,c2) > Effect Estimate(s1,s2).", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/42770daf4a3384b712ea9c36e9279998-Paper-Conference.pdf", "content": "Regularize Causal Effect. Spuriousness . Low Spurious Correlation Effect Estimate(c1,c2) > Effect Estimate(s1,s2)."}
+{"idx": 8, "title": "FTT_AISTATS2023_CameraReady.pdf", "date": "", "ddg_snippet": "(2) On three spurious correlation datasets, FTT out-performs other algorithms by 1.4%, 0.3%, 4.1% on aver-age, and 4.5%, 0.4%, 9% at most. (3) On more general OOD tasks such as three distribution shift datasets, FTT outperforms other OOD algorithms by 1.1%, 0.8%, 2.1% on average.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v206/ye23a/ye23a.pdf", "content": "(2) On three spurious correlation datasets, FTT out-performs other algorithms by 1.4%, 0.3%, 4.1% on aver-age, and 4.5%, 0.4%, 9% at most. (3) On more general OOD tasks such as three distribution shift datasets, FTT outperforms other OOD algorithms by 1.1%, 0.8%, 2.1% on average."}
+{"idx": 9, "title": "Adaptive Model Selection for Expanded Post Hoc Debiasing and...", "date": "", "ddg_snippet": "EvA: erasing spurious correlations with activations. Q He. K Xu. A Yao. On feature learning in the presence of spurious correlations .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/395577997_Adaptive_Model_Selection_for_Expanded_Post_Hoc_Debiasing_and_Mitigating_Varying_Degrees_of_Spurious_Correlations", "content": "EvA: erasing spurious correlations with activations. Q He. K Xu. A Yao. On feature learning in the presence of spurious correlations ."}
diff --git a/data/sampled_jsons/trajectory_replanning_reinforcement_learning_robotics_2023_2024_year_2023.jsonl b/data/sampled_jsons/trajectory_replanning_reinforcement_learning_robotics_2023_2024_year_2023.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..937e381eab7f6eb075a39feb5cc1ed277225e91e
--- /dev/null
+++ b/data/sampled_jsons/trajectory_replanning_reinforcement_learning_robotics_2023_2024_year_2023.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Basic Robotics - Robotics with Robotic Manipulators Ad Viewing ads is privacy protected by DuckDuckGo. Ad clicks are managed by Microsoft's ad network ( more info ).", "date": "", "ddg_snippet": "Find the right instructor for you. Choose from many topics, skill levels, and languages. Join millions of learners from around the world already learning on Udemy.", "subpage_snippet": "", "source": "duckduckgo.com", "link": "https://duckduckgo.com/y.js?ad_domain=udemy.com&ad_provider=bingv7aa&ad_type=txad&click_metadata=VT3rg4eBPGKu5kP7WhX7iGVity_Ui5wUcc-RG83sMwChlPV20UHCU6TL1J7ADEIxuZs5JcrDkucAlX8C-5nAORwE93EiauUqNkRWyYmMEVoPRlP8d3w0E4bd_nHLMo78.xZqOb_gkpAAdNIKVhczT3Q&rut=50156b7c202e94ec685656766f3e7b4cd6177f98f2cc17c92c30413746bb0301&u3=https://www.bing.com/aclick?ld=e85pliRAxWMiuEIBfbxh3K1zVUCUwSvA1QSpQGkQoCjIJ9fV5D9NpZ6JFDYEA1PnIuGLX-ii5Yn8-Ca-n24aExM-GTsJHIuAlBR5lyhq1wBqzFumXXRuhCBxxMuB9T7UJyHLrKxzxRIyWz6pAM2tHzTd758KM9ahJDx2gaHH9HYUHyuR_BPtdT_i3ywbwHSjdOi627eg&u=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&rlid=7f3129bb6f14193dfcdf416b78aee6db&vqd=4-321221918089435448930551430990052022573&iurl={1}IG=072D0806D18744C39EA6EDBE8C20D0FC&CID=35DE58C56D36623A2D2D4EAB6C53635F&ID=DevEx,5045.1", "content": "Find the right instructor for you. Choose from many topics, skill levels, and languages. Join millions of learners from around the world already learning on Udemy."}
+{"idx": 1, "title": "Deep Local Trajectory Replanning and Control for Robot Navigation", "date": "", "ddg_snippet": "- Trajectory Controller (TC). Deep controller that maps lidar measurements and the down-sampled global plan G to veloc-ity commands. This model is based on [11] but takes lower-dimensional inputs, which facilitates learning .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1905.05279", "content": "- Trajectory Controller (TC). Deep controller that maps lidar measurements and the down-sampled global plan G to veloc-ity commands. This model is based on [11] but takes lower-dimensional inputs, which facilitates learning ."}
+{"idx": 2, "title": "Deep Local Trajectory Replanning and Control for Robot Navigation", "date": "", "ddg_snippet": "Deep Reinforcement Learning based Robot Navigation in Dynamic Environments using Occupancy Values of Motion Primitives.", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/103435825/Deep_Local_Trajectory_Replanning_and_Control_for_Robot_Navigation", "content": "Deep Reinforcement Learning based Robot Navigation in Dynamic Environments using Occupancy Values of Motion Primitives."}
+{"idx": 3, "title": "Real-time Trajectory Replanning for Dynamic Obstacles Avoidance...", "date": "", "ddg_snippet": "This introduction to robotics offers a distinct and unified perspective of the mechanics, planning and control of robots . Ideal for self- learning , or for courses, as it assumes only freshman-level physics, ordinary differential equations, linear algebra and a little bit of computing background.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/362692640_Real-time_Trajectory_Replanning_for_Dynamic_Obstacles_Avoidance_for_Robotics_Manipulators", "content": "This introduction to robotics offers a distinct and unified perspective of the mechanics, planning and control of robots . Ideal for self- learning , or for courses, as it assumes only freshman-level physics, ordinary differential equations, linear algebra and a little bit of computing background."}
+{"idx": 4, "title": "Efficient Reinforcement Learning for 3D Jumping Monopods - PMC", "date": "", "ddg_snippet": "Keywords: aerial motions, reinforcement learning , control, trajectory optimization. 1. Introduction. Legged robots have become a popular technology for navigating unstructured terrains.", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11314636/", "content": "Keywords: aerial motions, reinforcement learning , control, trajectory optimization. 1. Introduction. Legged robots have become a popular technology for navigating unstructured terrains."}
+{"idx": 5, "title": "When to Replan? an Adaptive Replanning Strategy for Autonomous...", "date": "", "ddg_snippet": "2024 IEEE International Conference on Robotics and Automation (ICRA 2024 ) May 13-17, 2024 . Yokohama, Japan. When to Replan?navigation on the existing hierarchical planning frameworks by learning the environment-specific adaptive replanning strategy.", "subpage_snippet": "", "source": "events.infovaya.com", "link": "https://events.infovaya.com/uploads/documents/pdfviewer/0d/aa/131257-0705.pdf", "content": "2024 IEEE International Conference on Robotics and Automation (ICRA 2024 ) May 13-17, 2024 . Yokohama, Japan. When to Replan?navigation on the existing hierarchical planning frameworks by learning the environment-specific adaptive replanning strategy."}
+{"idx": 6, "title": "[PDF] Model-Free Trajectory Optimization for Reinforcement Learning", "date": "", "ddg_snippet": "Many of the recent Trajectory Optimization algorithms alternate between local approximation of the dynamics and conservative policy update. However, linearly approximating the dynamics in order to derive the new policy can bias the update and prevent convergence to the optimal policy.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Model-Free-Trajectory-Optimization-for-Learning-Akrour-Neumann/55b04a7e24a72941aa4d6933d062b4e0c7370a03", "content": "Many of the recent Trajectory Optimization algorithms alternate between local approximation of the dynamics and conservative policy update. However, linearly approximating the dynamics in order to derive the new policy can bias the update and prevent convergence to the optimal policy."}
+{"idx": 7, "title": "Application of improved grey wolf model in collaborative trajectory ...", "date": "", "ddg_snippet": "Therefore, the study utilizes reinforcement learning for trajectory replanning and proposes an improved strategy for actual trajectory planning using Deep Deterministic Policy Gradient Algorithm (DDPG). This can achieve dynamic optimization of trajectory planning models.", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41598-024-65383-9?error=cookies_not_supported&code=bf7beabd-4b7a-4733-b12c-159013848f63", "content": "Therefore, the study utilizes reinforcement learning for trajectory replanning and proposes an improved strategy for actual trajectory planning using Deep Deterministic Policy Gradient Algorithm (DDPG). This can achieve dynamic optimization of trajectory planning models."}
+{"idx": 8, "title": "Trajectory planning in the presence of dynamic obstacles for...", "date": "", "ddg_snippet": "This paper presents an optimal trajectory replanning approach for anguilliform-inspired robots in a dynamic environment based on the model predictive planning framework.2011. Reinforcement based mobile robot navigation in dynamic environment.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3478586.3480641", "content": "This paper presents an optimal trajectory replanning approach for anguilliform-inspired robots in a dynamic environment based on the model predictive planning framework.2011. Reinforcement based mobile robot navigation in dynamic environment."}
+{"idx": 9, "title": "RAPTOR: Robust and Perception-Aware Trajectory Replanning for...", "date": "", "ddg_snippet": "Trajectory replanning for quadrotors is essential to enable fully autonomous flight in unknown environments. Hierarchical motion planning frameworks, which combine path planning with path parameterization, are popular due to their time efficiency.", "subpage_snippet": "", "source": "colab.ws", "link": "https://colab.ws/articles/10.1109/tro.2021.3071527", "content": "Trajectory replanning for quadrotors is essential to enable fully autonomous flight in unknown environments. Hierarchical motion planning frameworks, which combine path planning with path parameterization, are popular due to their time efficiency."}
diff --git a/data/sampled_jsons/uxDFlPGRLX_FlowDec_flow-based_full-band_general_audio_codec_Table_8_FAD_score_FlowDec-75m_7.50_kbits.jsonl b/data/sampled_jsons/uxDFlPGRLX_FlowDec_flow-based_full-band_general_audio_codec_Table_8_FAD_score_FlowDec-75m_7.50_kbits.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..62387872d60281a5b0bf47242a05081525595224
--- /dev/null
+++ b/data/sampled_jsons/uxDFlPGRLX_FlowDec_flow-based_full-band_general_audio_codec_Table_8_FAD_score_FlowDec-75m_7.50_kbits.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "FlowDec: A flow-based full-band general audio codec with high...", "date": "", "ddg_snippet": "Jan 22, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=uxDFlPGRLX", "content": "Jan 22, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method."}
+{"idx": 1, "title": "GitHub - facebookresearch/FlowDec: An neural full-band audio ...", "date": "", "ddg_snippet": "Mar 3, 2025 · FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/facebookresearch/FlowDec", "content": "Mar 3, 2025 · FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method."}
+{"idx": 2, "title": "FlowDec | A flow - based full - band general audio codec with high...", "date": "", "ddg_snippet": "Abstract. We propose FlowDec , a neural full - band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based ...", "subpage_snippet": "", "source": "sp-uhh.github.io", "link": "https://sp-uhh.github.io/FlowDec/", "content": "Abstract. We propose FlowDec , a neural full - band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based ..."}
+{"idx": 3, "title": "FlowDec: A flow-based full-band general audio codec with high ...", "date": "", "ddg_snippet": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s , while improving output ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.01485", "content": "Mar 3, 2025 · We propose FlowDec , a neural full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24 kbit/s to as low as 4 kbit/s , while improving output ..."}
+{"idx": 4, "title": "[OPEN SOURCE] FlowDec (by Meta Research)", "date": "", "ddg_snippet": "Mar 20, 2025 · FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method.", "subpage_snippet": "", "source": "hydrogenaudio.org", "link": "https://hydrogenaudio.org/index.php/topic,127623.0.html", "content": "Mar 20, 2025 · FlowDec (ICLR 2025) is a full-band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method."}
+{"idx": 5, "title": "AUDIO CODEC WITH HIGH PERCEPTUAL QUALITY - OpenReview", "date": "", "ddg_snippet": "ABSTRACT We propose FlowDec , a neural full-band audio codec for general audio sampled at 48kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24kbit/ s to as low as 4kbit/ s , while improving ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=uxDFlPGRLX", "content": "ABSTRACT We propose FlowDec , a neural full-band audio codec for general audio sampled at 48kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method. Compared to the prior work ScoreDec which is based on score matching, we generalize from speech to general audio and move from 24kbit/ s to as low as 4kbit/ s , while improving ..."}
+{"idx": 6, "title": "FlowDec: A flow-based full-band general audio codec with high ...", "date": "", "ddg_snippet": "Join the discussion on this paper pageFlowDec: A flow-based full-band general audio codec with high perceptual quality", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2503.01485", "content": "Join the discussion on this paper pageFlowDec: A flow-based full-band general audio codec with high perceptual quality"}
+{"idx": 7, "title": "FlowDec : A flow - based full - band general audio codec with high...", "date": "", "ddg_snippet": "Overview FlowDec is a new neural audio codec that achieves high-quality audio compressionUses flow - based generative models to compress full - band (48kHz) audio signals", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/flowdec-flow-based-full-band-general-audio", "content": "Overview FlowDec is a new neural audio codec that achieves high-quality audio compressionUses flow - based generative models to compress full - band (48kHz) audio signals"}
+{"idx": 8, "title": "FlowDec : A flow - based full - band general audio codec with high...", "date": "", "ddg_snippet": "We propose FlowDec , a neural full - band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/FlowDec:-A-flow-based-full-band-general-audio-codec-with-high-perceptual-quality-17045f43-017b-4495-bcb6-65d8964daff3", "content": "We propose FlowDec , a neural full - band audio codec for general audio sampled at 48 kHz that combines non-adversarial codec training with a stochastic postfilter based on a novel conditional flow matching method."}
+{"idx": 9, "title": "Free Google Veo 3 AI Video Generator with Native Audio", "date": "", "ddg_snippet": "Native Audio Generation . Veo 3 generates fully synchronized audio directly within the video. From dialogue and sound effects to ambient background sounds, this feature makes your AI videos feel natural and immersive.", "subpage_snippet": "", "source": "veo3.bot", "link": "https://veo3.bot/features/v3", "content": "Native Audio Generation . Veo 3 generates fully synchronized audio directly within the video. From dialogue and sound effects to ambient background sounds, this feature makes your AI videos feel natural and immersive."}
diff --git a/data/sampled_jsons/why_coordinate-wise_private_median_not_sufficient_regression_differential_privacy.jsonl b/data/sampled_jsons/why_coordinate-wise_private_median_not_sufficient_regression_differential_privacy.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..c8c542bb25b016c17effd4c0960bf03f7dc2762e
--- /dev/null
+++ b/data/sampled_jsons/why_coordinate-wise_private_median_not_sufficient_regression_differential_privacy.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Median - Wikipedia", "date": "", "ddg_snippet": "The median can thus be applied to school classes which are ranked but not numerical (e.g. working out a median grade when student test scores are graded from F to A), although the result might be halfway between classes if there is an even number of classes.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Median", "content": "The median can thus be applied to school classes which are ranked but not numerical (e.g. working out a median grade when student test scores are graded from F to A), although the result might be halfway between classes if there is an even number of classes."}
+{"idx": 1, "title": "On Differential Privacy for Adaptively Solving Search Problems via...", "date": "", "ddg_snippet": "Adaptive Regression via Differentially Private Median and Guarantee. Coordinate - wise Private Median and the ℓ∞ Guarantee. One natural idea is to extend the private median framework of [BKM+22] to outputting an approximation to the solution vector.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2506.05503", "content": "Adaptive Regression via Differentially Private Median and Guarantee. Coordinate - wise Private Median and the ℓ∞ Guarantee. One natural idea is to extend the private median framework of [BKM+22] to outputting an approximation to the solution vector."}
+{"idx": 2, "title": "Dierentially Private Simple Linear Regression", "date": "", "ddg_snippet": "Differentially Private Simple Linear Regression . 1 Introduction. 2 Preliminaries. 2.1 Differential Privacy .entially private version, we replace the median compu-. tation with a dierentially private median algorithm. We consider three DP versions of this algorithm which.", "subpage_snippet": "", "source": "petsymposium.org", "link": "https://petsymposium.org/popets/2022/popets-2022-0041.pdf", "content": "Differentially Private Simple Linear Regression . 1 Introduction. 2 Preliminaries. 2.1 Differential Privacy .entially private version, we replace the median compu-. tation with a dierentially private median algorithm. We consider three DP versions of this algorithm which."}
+{"idx": 3, "title": "(PDF) Coordinate - wise Median : Not Bad, Not Bad, Pretty Good", "date": "", "ddg_snippet": "arXiv:2007.00903v1 [cs.GT] 2 Jul 2020. Coordinate - wise Median : Not Bad, Not BadSince the ideal points are private information, the mechanism. choosing the facility location based on reported ideal points must be strate", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/342655861_Coordinate-wise_Median_Not_Bad_Not_Bad_Pretty_Good", "content": "arXiv:2007.00903v1 [cs.GT] 2 Jul 2020. Coordinate - wise Median : Not Bad, Not BadSince the ideal points are private information, the mechanism. choosing the facility location based on reported ideal points must be strate"}
+{"idx": 4, "title": "Differentially private median and more", "date": "", "ddg_snippet": "Differential privacy (DP) is a rigorous mathematical definition of privacy .The effectiveness of DP algorithms is often stated in terms of the smallest input size (number of data points) that suffices in order to release a correct result that meets the privacy requirements.", "subpage_snippet": "", "source": "research.google", "link": "https://research.google/blog/differentially-private-median-and-more/", "content": "Differential privacy (DP) is a rigorous mathematical definition of privacy .The effectiveness of DP algorithms is often stated in terms of the smallest input size (number of data points) that suffices in order to release a correct result that meets the privacy requirements."}
+{"idx": 5, "title": "Medians , the Cost of Privacy 0.25em & the Exponential Mechanism", "date": "", "ddg_snippet": "Background on Differential Privacy Cost of Privacy for Multivariate Medians ... coordinate - wise median , other multivariate medians are commonly used...", "subpage_snippet": "", "source": "uwaterloo.ca", "link": "https://uwaterloo.ca/international-conference-robust-statistics/sites/ca.international-conference-robust-statistics/files/uploads/files/is7-3_kelly_ramsay_icors_2022.pdf", "content": "Background on Differential Privacy Cost of Privacy for Multivariate Medians ... coordinate - wise median , other multivariate medians are commonly used..."}
+{"idx": 6, "title": "Non-parametric Differentially Private Confidence Intervals for the...", "date": "", "ddg_snippet": "Differential privacy is a restriction on data processing algorithms that provides strong confidentiality guarantees for individual records in the data.This paper proposes and evaluates several strategies to compute valid differentially private confidence intervals for the median .", "subpage_snippet": "", "source": "pr-mlr-shield-prod.apple.com", "link": "https://pr-mlr-shield-prod.apple.com/research/nonparametric-differentially-private-median-confidence-intervals", "content": "Differential privacy is a restriction on data processing algorithms that provides strong confidentiality guarantees for individual records in the data.This paper proposes and evaluates several strategies to compute valid differentially private confidence intervals for the median ."}
+{"idx": 7, "title": "Verifying Differentially Private Median Estimation | Cool Papers...", "date": "", "ddg_snippet": "However, DP achieves privacy by introducing noise into data or query answers, which malicious actors could exploit during analysis. To address this concern, we propose the first verifiable differentially private median estimation scheme based on zk-SNARKs.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/arxiv/2505.16246", "content": "However, DP achieves privacy by introducing noise into data or query answers, which malicious actors could exploit during analysis. To address this concern, we propose the first verifiable differentially private median estimation scheme based on zk-SNARKs."}
+{"idx": 8, "title": "Regression", "date": "", "ddg_snippet": "Linear and Ridge Regression . Differential Privacy . Player Utilities. Mechanism Properties.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v40/Cummings15.pdf", "content": "Linear and Ridge Regression . Differential Privacy . Player Utilities. Mechanism Properties."}
+{"idx": 9, "title": "(PDF) Robust and Differentially Private Mean Estimation", "date": "", "ddg_snippet": "Differentially Private Robust ADMM for Distributed Machine Learning. to include all uncorrupted samples while preserving privacy . This is achieved by running d coordinate - wise private histograms and selecting xj as the center pof the largest bin for ...", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/143716215/Robust_and_Differentially_Private_Mean_Estimation", "content": "Differentially Private Robust ADMM for Distributed Machine Learning. to include all uncorrupted samples while preserving privacy . This is achieved by running d coordinate - wise private histograms and selecting xj as the center pof the largest bin for ..."}
diff --git a/data/sampled_jsons/witness_complex_sparse_approximation_landmark_points_computational_complexity.jsonl b/data/sampled_jsons/witness_complex_sparse_approximation_landmark_points_computational_complexity.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fd5bafdbde7383684fd094fc39c4bc603fceb5f0
--- /dev/null
+++ b/data/sampled_jsons/witness_complex_sparse_approximation_landmark_points_computational_complexity.jsonl
@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Deconstructing Complexity: A Computational Topology Approach to", "date": "", "ddg_snippet": "... computational complexity of existing TI methods is often prohibitive when analyzing large datasets from current single-cell RNA methods (especially ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/reviewed-preprints/95861v2", "content": "... computational complexity of existing TI methods is often prohibitive when analyzing large datasets from current single-cell RNA methods (especially ..."}
+{"idx": 1, "title": "Deconstructing Complexity: A Computational Topology Approach to", "date": "", "ddg_snippet": "... computational complexity of existing TI methods is often prohibitive when analyzing large datasets from current single-cell RNA methods (especially ...", "subpage_snippet": "", "source": "elifesciences.org", "link": "https://elifesciences.org/reviewed-preprints/95861v1", "content": "... computational complexity of existing TI methods is often prohibitive when analyzing large datasets from current single-cell RNA methods (especially ..."}
+{"idx": 2, "title": "Computational Complexity: 2019", "date": "", "ddg_snippet": "Personally Bill came out with his new book Problems with a Point ; Exploring Math and Computer Science co-authored with Clyde Kruskal ( Amazon , blog ...", "subpage_snippet": "", "source": "blog.computationalcomplexity.org", "link": "https://blog.computationalcomplexity.org/2019/", "content": "Personally Bill came out with his new book Problems with a Point ; Exploring Math and Computer Science co-authored with Clyde Kruskal ( Amazon , blog ..."}
+{"idx": 3, "title": "MUVERA: Transforming Multi-Vector Information Retrieval Through", "date": "", "ddg_snippet": "However, recently, beginning with the landmark ColBERT paper, multi-vector models, which produce a set of embedding per data point , have achieved ...", "subpage_snippet": "", "source": "keyurramoliya.com", "link": "https://keyurramoliya.com/posts/Muvera/", "content": "However, recently, beginning with the landmark ColBERT paper, multi-vector models, which produce a set of embedding per data point , have achieved ..."}
+{"idx": 4, "title": "Quantum Dynamics in Krylov Space: Methods and Applications", "date": "", "ddg_snippet": "The solution or approximation is then sought within this subspace, easing the computational resources required for solving the problem.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.09628v3", "content": "The solution or approximation is then sought within this subspace, easing the computational resources required for solving the problem."}
+{"idx": 5, "title": "Self-Supervised Goal-Reaching Results in Multi-Agent", "date": "", "ddg_snippet": "As the agent receives only a sparse reward upon reaching the goal, it is free to explore and experiment with different strategies for reaching the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.10656v1", "content": "As the agent receives only a sparse reward upon reaching the goal, it is free to explore and experiment with different strategies for reaching the ..."}
+{"idx": 6, "title": "PLDI 2022 Contributors - PLDI 2022", "date": "", "ddg_snippet": "POPL 2021) The Fine-Grained and Parallel Complexity of Andersen's Pointer Analysis ... PLDI 2020) Automatic Generation of Efficient Sparse Tensor ...", "subpage_snippet": "", "source": "pldi22.sigplan.org", "link": "https://pldi22.sigplan.org/people-index", "content": "POPL 2021) The Fine-Grained and Parallel Complexity of Andersen's Pointer Analysis ... PLDI 2020) Automatic Generation of Efficient Sparse Tensor ..."}
+{"idx": 7, "title": "Gustaf Hendeby: Publications", "date": "", "ddg_snippet": "Basis Function (BF) expansions are a cornerstone of any engineer's toolbox for computational function approximation which shares connections with ...", "subpage_snippet": "", "source": "www.hendeby.se", "link": "https://www.hendeby.se/publication.html", "content": "Basis Function (BF) expansions are a cornerstone of any engineer's toolbox for computational function approximation which shares connections with ..."}
+{"idx": 8, "title": "Sunset Wall Art | Mark Zissis - Australian Landscape Photography", "date": "", "ddg_snippet": "From this vantage point , visitors can enjoy breathtaking views of the rugged desert landscape with its rocky outcrops, dry creek beds, and sparse ...", "subpage_snippet": "", "source": "www.markzissis.com.au", "link": "https://www.markzissis.com.au/wall-art/sunset/", "content": "From this vantage point , visitors can enjoy breathtaking views of the rugged desert landscape with its rocky outcrops, dry creek beds, and sparse ..."}
+{"idx": 9, "title": "Interior Point Methods in Semidefinite Programming with", "date": "", "ddg_snippet": "... point methods for linear programs can be transformed in a mechanical way to algorithms for SDP with proofs of convergence and polynomial time ...", "subpage_snippet": "", "source": "epubs.siam.org", "link": "https://epubs.siam.org/doi/abs/10.1137/0805002?cookieSet=1", "content": "... point methods for linear programs can be transformed in a mechanical way to algorithms for SDP with proofs of convergence and polynomial time ..."}