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data/sampled_jsons/1e-4_OR_0.0001_EntityErasure_AECM_learning_rate_implementation.jsonl

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+{"idx": 0, "title": "Learning rate annealing with tune.run() - RLlib - Ray", "date": "", "ddg_snippet": "Is there a way to set learning rate annealing with tune.run()? The grid search below will run two training: one LR at 1 e -5 and second at 1 e -6. How do I, for example, have a LR schedule where at the end of 1000 iterations is LR is reduced from 1 e -5 to 1 e -6 and from 1 e -6 to 1 e -7?", "subpage_snippet": "", "source": "discuss.ray.io", "link": "https://discuss.ray.io/t/learning-rate-annealing-with-tune-run/1928", "content": "Is there a way to set learning rate annealing with tune.run()? The grid search below will run two training: one LR at 1 e -5 and second at 1 e -6. How do I, for example, have a LR schedule where at the end of 1000 iterations is LR is reduced from 1 e -5 to 1 e -6 and from 1 e -6 to 1 e -7?"}
+{"idx": 1, "title": "An Analysis of Batch Size vs. Learning Rate on Imagenette – Vishal...", "date": "", "ddg_snippet": "With a batch size of 64 and three different LRs ( 1 e - 4 , 1 e -3, 1 e -2) I achieved the following results using three models (xresnet34, xse_resnext50, xresnet18)The best training run goes to xresnet34 with a batch size of 16 and a learning rate of 1 e -3.", "subpage_snippet": "", "source": "vishalbakshi.github.io", "link": "https://vishalbakshi.github.io/blog/posts/2025-06-18-imagenette/", "content": "With a batch size of 64 and three different LRs ( 1 e - 4 , 1 e -3, 1 e -2) I achieved the following results using three models (xresnet34, xse_resnext50, xresnet18)The best training run goes to xresnet34 with a batch size of 16 and a learning rate of 1 e -3."}
+{"idx": 2, "title": "[Bug]: Learning Rate setting in the GUI does not change if one does...", "date": "", "ddg_snippet": "When I type E - 4 in the Learning Rate field, it does not change it, preserving the previous value (e.g. 8E-5). So you start the training, but it doesn't do as expected.Either it accepts it as 1 E - 4 or 0 . 0001 , or at least shows a validation error explaining the value is not acceptable.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Nerogar/OneTrainer/issues/836", "content": "When I type E - 4 in the Learning Rate field, it does not change it, preserving the previous value (e.g. 8E-5). So you start the training, but it doesn't do as expected.Either it accepts it as 1 E - 4 or 0 . 0001 , or at least shows a validation error explaining the value is not acceptable."}
+{"idx": 3, "title": "Strange learning rate finder plot for custom model - Part 1 (2019)...", "date": "", "ddg_snippet": "learn = learn .split([[ learn .model.frontal_cnn, learn .model.lateral_cnn], learn .model.joined_cnn]). Afterwards I ran the following code to find a good learning rate for my modelIn these cases, I would rather suggest that 1 e -2 and 1 e - 4 are the best learning rates , respectively.", "subpage_snippet": "", "source": "forums.fast.ai", "link": "https://forums.fast.ai/t/strange-learning-rate-finder-plot-for-custom-model/45441", "content": "learn = learn .split([[ learn .model.frontal_cnn, learn .model.lateral_cnn], learn .model.joined_cnn]). Afterwards I ran the following code to find a good learning rate for my modelIn these cases, I would rather suggest that 1 e -2 and 1 e - 4 are the best learning rates , respectively."}
+{"idx": 4, "title": "Fine-Tuning T5 With Hugging Face | Restackio", "date": "", "ddg_snippet": "Learning rates of 1 e - 4 and 3 e - 4 are generally effective for tasks such as classification, summarization, translation, and question answering.", "subpage_snippet": "", "source": "d2wozrt205r2fu.cloudfront.net", "link": "https://d2wozrt205r2fu.cloudfront.net/p/fine-tuning-answer-t5-hugging-face-cat-ai", "content": "Learning rates of 1 e - 4 and 3 e - 4 are generally effective for tasks such as classification, summarization, translation, and question answering."}
+{"idx": 5, "title": "Example Usage | runpod-workers/worker-lora_trainer | DeepWiki", "date": "", "ddg_snippet": "\"lr_scheduler_num_cycles\": 1, \" learning _ rate \": 0 . 0001 lr_scheduler: LR decay pattern. network_dim: LoRA rank dimension. unet_lr: UNet learning rate . save_precision: Model storage format.", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/runpod-workers/worker-lora_trainer/5.2-example-usage", "content": "\"lr_scheduler_num_cycles\": 1, \" learning _ rate \": 0 . 0001 lr_scheduler: LR decay pattern. network_dim: LoRA rank dimension. unet_lr: UNet learning rate . save_precision: Model storage format."}
+{"idx": 6, "title": "Perfect LoRA Training parameters human character - Models - Hugging...", "date": "", "ddg_snippet": "--text_encoder_lr= 0 . 0001 : Slightly lower learning rate for text encoder stability.-- learning _ rate = 1 e - 4 : Lower learning rate to prevent overfitting. --max_train_steps=1500: Sufficient steps for limited data without overtraining.", "subpage_snippet": "", "source": "discuss.huggingface.co", "link": "https://discuss.huggingface.co/t/perfect-lora-training-parameters-human-character/147211", "content": "--text_encoder_lr= 0 . 0001 : Slightly lower learning rate for text encoder stability.-- learning _ rate = 1 e - 4 : Lower learning rate to prevent overfitting. --max_train_steps=1500: Sufficient steps for limited data without overtraining."}
+{"idx": 7, "title": "Songbird Loss function plot looks like (a bad) EKG... - QIIME 2 Forum", "date": "", "ddg_snippet": "If you don't want a noisy loss, the best approach is to lower the learning rate --p- learning - rate . The default is now 1 e -3, you can try 1 e - 4 or 1 e -5 to see if that will give you a cleaner loss (although you will need to train for more epochs). 1 Like.convergence-plot_LR- 0 . 0001 -1.", "subpage_snippet": "", "source": "forum.qiime2.org", "link": "https://forum.qiime2.org/t/songbird-loss-function-plot-looks-like-a-bad-ekg/14329", "content": "If you don't want a noisy loss, the best approach is to lower the learning rate --p- learning - rate . The default is now 1 e -3, you can try 1 e - 4 or 1 e -5 to see if that will give you a cleaner loss (although you will need to train for more epochs). 1 Like.convergence-plot_LR- 0 . 0001 -1."}
+{"idx": 8, "title": "StephanHeijl.com - Notes on BERT: Pre-training of Deep Bidirectional...", "date": "", "ddg_snippet": "Adam settings. Learning rate . 1 e - 4 .The pretraining learning rate is set to 1 e - 4 , not an uncommon learning rate for Adam. The first 10.000 steps are subject to learning rate warm-up, where the lr is linearly increased from 0 to the target.", "subpage_snippet": "", "source": "stephanheijl.com", "link": "https://stephanheijl.com/notes_on_bert.html", "content": "Adam settings. Learning rate . 1 e - 4 .The pretraining learning rate is set to 1 e - 4 , not an uncommon learning rate for Adam. The first 10.000 steps are subject to learning rate warm-up, where the lr is linearly increased from 0 to the target."}
+{"idx": 9, "title": "Simple Linear Regression not converging – Python", "date": "", "ddg_snippet": "Your code seems actually to work fine; except for learning rate , really! Just reduce it from 0.01 to e.g. 0 . 0001 and everything works fine (well, I would also reduce tolerance to something much much smaller, like 1 e -5, to make sure it actually converges to the right solution).", "subpage_snippet": "", "source": "python.tutorialink.com", "link": "https://python.tutorialink.com/simple-linear-regression-not-converging/", "content": "Your code seems actually to work fine; except for learning rate , really! Just reduce it from 0.01 to e.g. 0 . 0001 and everything works fine (well, I would also reduce tolerance to something much much smaller, like 1 e -5, to make sure it actually converges to the right solution)."}

data/sampled_jsons/35068_XLRS-Bench-_Could_Your_Multimodal_LLMs_Understand_Extremely_Large_Ultra-High-Resolution_Remote.jsonl

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+{"idx": 0, "title": "XLRS-Bench: Could Your Multimodal LLMs Understand Extremely ... GitHub - AI9Stars/XLRS-Bench: [CVPR 2025 HIghlight] XLRS ... CVPR 2025 Open Access Repository XLRS-Bench XLRS-Bench|遥感数据集|图像分析数据集 arXiv:2503.23771v1 [cs.CV] 31 Mar 2025 XLRS-Bench: Could Your Multimodal LLMs Understand Extremely ...", "date": "", "ddg_snippet": "Mar 31, 2025 · View a PDF of the paper titled XLRS - Bench : Could Your Multimodal LLMs Understand Extremely Large Ultra - High - Resolution Remote Sensing Imagery ?, by Fengxiang Wang and 11 other authors Apr 1, 2025 · We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far. To address these issues, we present XLRS - Bench : a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios. We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far. Apr 1, 2025 · XL RS - Ben ch 数据集由国防科技大学、清华大学、武汉大学等机构的联合研究团队于2025年推出，旨在评估多模态大语言模型（ ML LM s ）在 超高 分辨率 遥感影像中的感知与推理能力。 To address these issues, we present XLRS - Bench : a com- prehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios. To address these issues, we present XLRS - Bench : a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.23771", "content": "Mar 31, 2025 · View a PDF of the paper titled XLRS - Bench : Could Your Multimodal LLMs Understand Extremely Large Ultra - High - Resolution Remote Sensing Imagery ?, by Fengxiang Wang and 11 other authors Apr 1, 2025 · We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far. To address these issues, we present XLRS - Bench : a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios. We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far. Apr 1, 2025 · XL RS - Ben ch 数据集由国防科技大学、清华大学、武汉大学等机构的联合研究团队于2025年推出，旨在评估多模态大语言模型（ ML LM s ）在 超高 分辨率 遥感影像中的感知与推理能力。 To address these issues, we present XLRS - Bench : a com- prehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios. To address these issues, we present XLRS - Bench : a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios."}
+{"idx": 1, "title": "GitHub - AI9Stars/XLRS-Bench: [CVPR 2025 HIghlight] XLRS ...", "date": "", "ddg_snippet": "Apr 1, 2025 · We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/AI9Stars/XLRS-Bench", "content": "Apr 1, 2025 · We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far."}
+{"idx": 2, "title": "XLRS-Bench", "date": "", "ddg_snippet": "We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far.", "subpage_snippet": "", "source": "xlrs-bench.github.io", "link": "https://xlrs-bench.github.io/home_page.html", "content": "We present XLRS - Bench , a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios, featuring the largest average image size of 8,500 × 8,500 observed thus far."}
+{"idx": 3, "title": "XLRS-Bench: Could Your Multimodal LLMs Understand Extremely ...", "date": "", "ddg_snippet": "To address these issues, we present XLRS - Bench : a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2503.23771", "content": "To address these issues, we present XLRS - Bench : a comprehensive benchmark for evaluating the perception and reasoning capabilities of MLLMs in ultra - high - resolution RS scenarios."}
+{"idx": 4, "title": "( PDF ) XLRS - Bench : Could Your Multimodal LLMs Understand ...", "date": "", "ddg_snippet": "XLRS - Bench focuses on extremely large ultra - high - resolution RS imagery , integrating. over 10 multimodal vision-language perception and reasoning tasks within the same image .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/390354847_XLRS-Bench_Could_Your_Multimodal_LLMs_Understand_Extremely_Large_Ultra-High-Resolution_Remote_Sensing_Imagery", "content": "XLRS - Bench focuses on extremely large ultra - high - resolution RS imagery , integrating. over 10 multimodal vision-language perception and reasoning tasks within the same image ."}
+{"idx": 5, "title": "XLRS - Bench : Could Your Multimodal LLMs Understand Extremely ...", "date": "", "ddg_snippet": "XLRS - Bench focuses on extremely large ultra - high - resolution RS imagery , integrating over 10 multimodal vision-language perception and reasoning tasks within the same image .", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Wang_XLRS-Bench_Could_Your_Multimodal_LLMs_Understand_Extremely_Large_Ultra-High-Resolution_Remote_CVPR_2025_paper.pdf", "content": "XLRS - Bench focuses on extremely large ultra - high - resolution RS imagery , integrating over 10 multimodal vision-language perception and reasoning tasks within the same image ."}
+{"idx": 6, "title": "XLRS - Bench : Could Your Multimodal LLMs Understand Extremely ...", "date": "", "ddg_snippet": "XLRS - Bench boasts the largest average image size (8500$\\times$8500) observed thus far, with all evaluation samples meticulously annotated manually, assisted by a novel semi-automatic captioner on ultra - high - resolution RS images .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=ThgEfn5CSU&referrer=[the+profile+of+Maosong+Sun](/profile?id=~Maosong_Sun1)", "content": "XLRS - Bench boasts the largest average image size (8500$\\times$8500) observed thus far, with all evaluation samples meticulously annotated manually, assisted by a novel semi-automatic captioner on ultra - high - resolution RS images ."}
+{"idx": 7, "title": "CVPR.2025 - Highlight | Cool Papers - Immersive Paper Discovery", "date": "", "ddg_snippet": "Large -scale multimodal representation learning successfully optimizes for zero-shot transfer at test time. Yet the standard pretraining paradigm (contrastive learning on large amounts of image -text data) does not explicitly encourage representations to support few-shot adaptation.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/CVPR.2025?group=Highlight", "content": "Large -scale multimodal representation learning successfully optimizes for zero-shot transfer at test time. Yet the standard pretraining paradigm (contrastive learning on large amounts of image -text data) does not explicitly encourage representations to support few-shot adaptation."}
+{"idx": 8, "title": "【论文翻】 XLRS - Bench : Could Your Multimodal LLMs Understand ...", "date": "", "ddg_snippet": "XLRS - Bench stands out from existing multimodal understanding benchmarks with four key features: i) the largest average image size of 8,500×8,500, featuring extensive 10,000×10,000 imagery ; ii) 16 sub-tasks designed to evaluate MLLMs’ capabilities in...", "subpage_snippet": "", "source": "blog.csdn.net", "link": "https://blog.csdn.net/l963852k/article/details/149417749", "content": "XLRS - Bench stands out from existing multimodal understanding benchmarks with four key features: i) the largest average image size of 8,500×8,500, featuring extensive 10,000×10,000 imagery ; ii) 16 sub-tasks designed to evaluate MLLMs’ capabilities in..."}
+{"idx": 9, "title": "Paper Digest: CVPR 2025 Papers & Highlights – Paper Digest", "date": "", "ddg_snippet": "XLRS - Bench : Could Your Multimodal LLMs Understand Extremely Large Ultra - High - Resolution Remote Sensing Imagery ?", "subpage_snippet": "", "source": "www.paperdigest.org", "link": "https://www.paperdigest.org/2025/06/cvpr-2025-papers-highlights/", "content": "XLRS - Bench : Could Your Multimodal LLMs Understand Extremely Large Ultra - High - Resolution Remote Sensing Imagery ?"}

data/sampled_jsons/35068_XLRS-Bench_Table_2_Qwen2-VL_scores_year_2024.jsonl

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+{"idx": 0, "title": "Qwen - Wikipedia", "date": "", "ddg_snippet": "Toggle the table of contents. Qwen. 25 languages.The Qwen-VL series is a line of visual language models that combines a vision transformer with a LLM.[3][14] Alibaba released Qwen 2 - VL with variants of 2 billion and 7 billion parameters.[15][16][17].", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Qwen", "content": "Toggle the table of contents. Qwen. 25 languages.The Qwen-VL series is a line of visual language models that combines a vision transformer with a LLM.[3][14] Alibaba released Qwen 2 - VL with variants of 2 billion and 7 billion parameters.[15][16][17]."}
+{"idx": 1, "title": "microsoft/GUI-Actor-7B- Qwen 2 - VL · Hugging Face", "date": "", "ddg_snippet": "Table 1. Main results on ScreenSpot-Pro, ScreenSpot, and ScreenSpot-v 2 with Qwen 2 - VL as the backbone. † indicates scores obtained from our own evaluation of the official models on Huggingface.", "subpage_snippet": "", "source": "huggingface.1319lm.top", "link": "https://huggingface.1319lm.top/microsoft/GUI-Actor-7B-Qwen2-VL", "content": "Table 1. Main results on ScreenSpot-Pro, ScreenSpot, and ScreenSpot-v 2 with Qwen 2 - VL as the backbone. † indicates scores obtained from our own evaluation of the official models on Huggingface."}
+{"idx": 2, "title": "Qwen 2 .5 VL ! Qwen 2 .5 VL ! Qwen 2 .5 VL ! | Qwen", "date": "", "ddg_snippet": "Qwen 2 .5- VL has significantly enhanced its general image recognition capabilities, expanding the categories of images to an ultra-large number.Watch the video and list the paper titles in a table . Qwen 2 .5- VL .", "subpage_snippet": "", "source": "qwenlm.github.io", "link": "https://qwenlm.github.io/blog/qwen2.5-vl/", "content": "Qwen 2 .5- VL has significantly enhanced its general image recognition capabilities, expanding the categories of images to an ultra-large number.Watch the video and list the paper titles in a table . Qwen 2 .5- VL ."}
+{"idx": 3, "title": "Qwen3-Max 2025 Complete Release Analysis: In-Depth Review of...", "date": "", "ddg_snippet": "Enhanced Coding Capabilities: SWE- Bench Verified score of 69.6, significantly improved agent capabilities. Thinking Version: Qwen3-Max-Thinking achieves 100% accuracy on AIME25, HMMT and other mathematical reasoning benchmarks.", "subpage_snippet": "", "source": "qwq32.com", "link": "https://qwq32.com/blog/2025-qwen3-max", "content": "Enhanced Coding Capabilities: SWE- Bench Verified score of 69.6, significantly improved agent capabilities. Thinking Version: Qwen3-Max-Thinking achieves 100% accuracy on AIME25, HMMT and other mathematical reasoning benchmarks."}
+{"idx": 4, "title": "Qwen3-Next-80B-A3B vs Qwen3-235B-A22B-2507:Why Small Excels", "date": "", "ddg_snippet": "Table Of ContentsQwen3-Next-80B vs Qwen3-235B：Key Differences in ArchitecturesTakeaway: Qwen3-Next-80B-A3B is designed for efficiency without sacrificing much performance.", "subpage_snippet": "", "source": "blogs.novita.ai", "link": "https://blogs.novita.ai/qwen3-next-80b-a3b-vs-qwen3-235b-a22b-2507why-small-excels/", "content": "Table Of ContentsQwen3-Next-80B vs Qwen3-235B：Key Differences in ArchitecturesTakeaway: Qwen3-Next-80B-A3B is designed for efficiency without sacrificing much performance."}
+{"idx": 5, "title": "GitHub - QwenLM/ Qwen 2 .5- VL : Qwen 2 .5- VL is the multimodal large...", "date": "", "ddg_snippet": "In the past five months since Qwen 2 - VL 's release, numerous developers have built new models on the Qwen 2 - VL vision-language models, providing us with valuable feedback. During this period, we focused on building more useful vision-language models.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/QwenLM/Qwen2.5-VL", "content": "In the past five months since Qwen 2 - VL 's release, numerous developers have built new models on the Qwen 2 - VL vision-language models, providing us with valuable feedback. During this period, we focused on building more useful vision-language models."}
+{"idx": 6, "title": "Qwen/ Qwen 2 - VL - 2 B-Instruct · Hugging Face", "date": "", "ddg_snippet": "Naive Dynamic Resolution: Unlike before, Qwen 2 - VL can handle arbitrary image resolutions, mapping them into a dynamic number of visual tokens, offering a more human-like visual processing experience.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct", "content": "Naive Dynamic Resolution: Unlike before, Qwen 2 - VL can handle arbitrary image resolutions, mapping them into a dynamic number of visual tokens, offering a more human-like visual processing experience."}
+{"idx": 7, "title": "qwen/ qwen 2 .5- vl -7b • LM Studio", "date": "", "ddg_snippet": "Qwen 2 .5- VL -7B-Instruct. Qwen 2 .5- VL -7B-Instruct is a vision-language model that processes images, text, and video, supporting structured outputs and visual localization. It can analyze charts, graphics, and layouts, and is capable of temporal reasoning over long video sequences.", "subpage_snippet": "", "source": "lmstudio.ai", "link": "https://lmstudio.ai/models/qwen/qwen2.5-vl-7b", "content": "Qwen 2 .5- VL -7B-Instruct. Qwen 2 .5- VL -7B-Instruct is a vision-language model that processes images, text, and video, supporting structured outputs and visual localization. It can analyze charts, graphics, and layouts, and is capable of temporal reasoning over long video sequences."}
+{"idx": 8, "title": "togetherai/ qwen 2 - vl -72b-instruct", "date": "", "ddg_snippet": "togetherai. qwen 2 - vl -72b-instruct.Preview. YAML. together Qwen 2 - VL (72B) Instruct model icon.", "subpage_snippet": "", "source": "hub.continue.dev", "link": "https://hub.continue.dev/togetherai/qwen2-vl-72b-instruct", "content": "togetherai. qwen 2 - vl -72b-instruct.Preview. YAML. together Qwen 2 - VL (72B) Instruct model icon."}
+{"idx": 9, "title": "Qwen", "date": "", "ddg_snippet": "Qwen3-Max-Preview. Скачать приложение.Задайте вопрос Qwen, узнайте больше.", "subpage_snippet": "", "source": "chat.qwen.ai", "link": "https://chat.qwen.ai/", "content": "Qwen3-Max-Preview. Скачать приложение.Задайте вопрос Qwen, узнайте больше."}

data/sampled_jsons/6yBhoJn6qy_Causal_Modeling_of_Climate_Activism_on_Reddit_Related_Work_section_events.jsonl

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+{"idx": 0, "title": "Causal Modeling of Climate Activism on Reddit - OpenReview", "date": "", "ddg_snippet": "In this 16 work , we develop a comprehensive causal model of how and why 17 Reddit users engage with activist communities driving mass climate 18 protests (mainly the 2019 Earth Strike, Fridays for Future, and Ex- 19 tinction Rebellion). Our framework, based on Stochastic Variational 20 Inference applied to Bayesian Networks, learns the causal ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=6yBhoJn6qy", "content": "In this 16 work , we develop a comprehensive causal model of how and why 17 Reddit users engage with activist communities driving mass climate 18 protests (mainly the 2019 Earth Strike, Fridays for Future, and Ex- 19 tinction Rebellion). Our framework, based on Stochastic Variational 20 Inference applied to Bayesian Networks, learns the causal ..."}
+{"idx": 1, "title": "[2410.10562] Causal Modeling of Climate Activism on Reddit", "date": "", "ddg_snippet": "Climate activism is crucial in stimulating collective societal and behavioral change towards sustainable practices through political pressure. Although multiple factors contribute to the participation in activism , their complex relationships and the scarcity of data on their interactions have restricted most prior research to studying them in isolation, thus preventing the development of a ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.10562", "content": "Climate activism is crucial in stimulating collective societal and behavioral change towards sustainable practices through political pressure. Although multiple factors contribute to the participation in activism , their complex relationships and the scarcity of data on their interactions have restricted most prior research to studying them in isolation, thus preventing the development of a ..."}
+{"idx": 2, "title": "Causal Modeling of Climate Activism on Reddit | Article Information | J ...", "date": "", "ddg_snippet": "Article \"Causal Modeling of Climate Activism on Reddit \" Detailed information of the J-GLOBAL is an information service managed by the Japan Science and Technology Agency (hereinafter referred to as \"JST\"). It provides free access to secondary information on researchers, articles, patents, etc., in science and technology, medicine and pharmacy. The search results guide you to high-quality ...", "subpage_snippet": "", "source": "jglobal.jst.go.jp", "link": "https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202402219833468228", "content": "Article \"Causal Modeling of Climate Activism on Reddit \" Detailed information of the J-GLOBAL is an information service managed by the Japan Science and Technology Agency (hereinafter referred to as \"JST\"). It provides free access to secondary information on researchers, articles, patents, etc., in science and technology, medicine and pharmacy. The search results guide you to high-quality ..."}
+{"idx": 3, "title": "Causal Modeling of Climate Activism on Reddit - Researchr", "date": "", "ddg_snippet": "Causal Modeling of Climate Activism on Reddit . 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 590-600, ACM, 2025. [doi]", "subpage_snippet": "", "source": "researchr.org", "link": "https://researchr.org/publication/LentiAMM25", "content": "Causal Modeling of Climate Activism on Reddit . 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 590-600, ACM, 2025. [doi]"}
+{"idx": 4, "title": "Causal Modeling of Climate Activism on Reddit", "date": "", "ddg_snippet": "In this work , we develop a comprehensive causal model of how and why Reddit users engage with activist communities driving mass climate protests (mainly the 2019 Earth Strike, Fridays for Future, and Extinction Rebellion).", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3696410.3714684", "content": "In this work , we develop a comprehensive causal model of how and why Reddit users engage with activist communities driving mass climate protests (mainly the 2019 Earth Strike, Fridays for Future, and Extinction Rebellion)."}
+{"idx": 5, "title": "Causal Modeling of Climate Activism on Reddit - arXiv.org", "date": "", "ddg_snippet": "We developed a rich and comprehensive causal model to study the interplay between different determinants of climate activism on Reddit . This work represents a first attempt to apply a multi-causal model to social media data.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.10562v1", "content": "We developed a rich and comprehensive causal model to study the interplay between different determinants of climate activism on Reddit . This work represents a first attempt to apply a multi-causal model to social media data."}
+{"idx": 6, "title": "Causal networks for climate model evaluation and constrained ...", "date": "", "ddg_snippet": "Here we apply causal discovery algorithms to sea level pressure data from a large set of climate model simulations and, as a proxy for observations, meteorological reanalyses.", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41467-020-15195-y", "content": "Here we apply causal discovery algorithms to sea level pressure data from a large set of climate model simulations and, as a proxy for observations, meteorological reanalyses."}
+{"idx": 7, "title": "PDF Spatial-temporal Causal Modeling for Climate Change Attribution", "date": "", "ddg_snippet": "In the present work , we employ a relatively simple approach to combining the two: using our Bayesian hierarchical model we estimate the N-year event magnitudes associated with the climate metrics of interest, and we incorporate these estimated variables as additional variables in causal modeling and attribution in the spatio-temporal modeling ...", "subpage_snippet": "", "source": "www.niculescu-mizil.org", "link": "http://www.niculescu-mizil.org/papers/KDD09Climate-final.pdf", "content": "In the present work , we employ a relatively simple approach to combining the two: using our Bayesian hierarchical model we estimate the N-year event magnitudes associated with the climate metrics of interest, and we incorporate these estimated variables as additional variables in causal modeling and attribution in the spatio-temporal modeling ..."}
+{"idx": 8, "title": "Causal Modeling of Climate Activism on Reddit - Semantic Scholar", "date": "", "ddg_snippet": "Climate activism is crucial in stimulating collective societal and behavioral change towards sustainable practices through political pressure. Although multiple factors contribute to the participation in activism , their complex relationships and the scarcity of data on their interactions have restricted most prior research to studying them in isolation, thus preventing the development of a ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Causal-Modeling-of-Climate-Activism-on-Reddit-Lenti-Aiello/c4c7c3972ba102db37738c082f27ebfcd3983057", "content": "Climate activism is crucial in stimulating collective societal and behavioral change towards sustainable practices through political pressure. Although multiple factors contribute to the participation in activism , their complex relationships and the scarcity of data on their interactions have restricted most prior research to studying them in isolation, thus preventing the development of a ..."}
+{"idx": 9, "title": "PDF A methodological approach for inferring causal relationships from ...", "date": "", "ddg_snippet": "A study closely related to our work on extracting causal relationships from climate change social media data is proposed by Lenti et al. (2024). Their approach analyzes Reddit data from 2016 to 2022 using stochastic variational inference and Bayesian networks to examine the impact of sociodemographics, climate news exposure, extreme weather ...", "subpage_snippet": "", "source": "peerj.com", "link": "https://peerj.com/articles/cs-2964.pdf", "content": "A study closely related to our work on extracting causal relationships from climate change social media data is proposed by Lenti et al. (2024). Their approach analyzes Reddit data from 2016 to 2022 using stochastic variational inference and Bayesian networks to examine the impact of sociodemographics, climate news exposure, extreme weather ..."}

data/sampled_jsons/American_Political_Science_Review_journal_domain.jsonl

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+{"idx": 1, "title": "FirstView articles | American Political Science Review", "date": "", "ddg_snippet": "Journals · American Political Science Review ; FirstView articles. English; Français ... We illustrate this in the domains of policing and gender, examining ...", "subpage_snippet": "", "source": "www.cambridge.org", "link": "https://www.cambridge.org/core/journals/american-political-science-review/firstview", "content": "Journals · American Political Science Review ; FirstView articles. English; Français ... We illustrate this in the domains of policing and gender, examining ..."}
+{"idx": 2, "title": "Vol. 22, No. 1, Feb., 1928 of The American Political ...", "date": "", "ddg_snippet": "The American Political Science Review (APSR) is the longest runningpublication of the American Political Science Association (APSA). APSR,first published in ...", "subpage_snippet": "", "source": "www.jstor.org", "link": "https://www.jstor.org/stable/i333476", "content": "The American Political Science Review (APSR) is the longest runningpublication of the American Political Science Association (APSA). APSR,first published in ..."}
+{"idx": 3, "title": "Vol. 11, No. 1, Feb., 1917 of The American Political ...", "date": "", "ddg_snippet": "The American Political Science Review (APSR ) is the longest runningpublication of the American Political Science Association (APSA). APSR,first published in ...", "subpage_snippet": "", "source": "www.jstor.org", "link": "https://www.jstor.org/stable/i306597", "content": "The American Political Science Review (APSR ) is the longest runningpublication of the American Political Science Association (APSA). APSR,first published in ..."}
+{"idx": 4, "title": "American Political Science Review, Cambridge University ...", "date": "", "ddg_snippet": "463-478 The Coevolution of American Political Science and the American Political Science Review ... 613-618 The Study of Political Parties, 1906–2005: The View ...", "subpage_snippet": "", "source": "ideas.repec.org", "link": "https://ideas.repec.org/s/cup/apsrev7.html", "content": "463-478 The Coevolution of American Political Science and the American Political Science Review ... 613-618 The Study of Political Parties, 1906–2005: The View ..."}
+{"idx": 5, "title": "FAQs - American Political Science Association (APSA)", "date": "", "ddg_snippet": "APSA Preprints is a free-to-access pre-publication platform dedicated to early research outputs in political science and related disciplines.", "subpage_snippet": "", "source": "apsanet.org", "link": "https://apsanet.org/publications/apsa-preprints/faqs/", "content": "APSA Preprints is a free-to-access pre-publication platform dedicated to early research outputs in political science and related disciplines."}
+{"idx": 6, "title": "This Journal's Future Is Female", "date": "", "ddg_snippet": "29 Jul 2019 — The American Political Science Review's new editors want to preserve its strong reputation while broadening its readership, relevance and ...", "subpage_snippet": "", "source": "www.insidehighered.com", "link": "https://www.insidehighered.com/news/2019/07/30/political-science-association-pleases-and-surprises-members-its-flagship", "content": "29 Jul 2019 — The American Political Science Review's new editors want to preserve its strong reputation while broadening its readership, relevance and ..."}
+{"idx": 7, "title": "Popular culture in (and out of) American political science", "date": "", "ddg_snippet": "by N Dorzweiler · 2017 · Cited by 14 — Abstract. Historically, American political science has rarely engaged popular culture as a central topic of study, despite the domain's outsized ...", "subpage_snippet": "", "source": "journals.sagepub.com", "link": "https://journals.sagepub.com/doi/abs/10.1177/0952695116684314", "content": "by N Dorzweiler · 2017 · Cited by 14 — Abstract. Historically, American political science has rarely engaged popular culture as a central topic of study, despite the domain's outsized ..."}
+{"idx": 8, "title": "Political Science — Whole Tale 1.2.0.0 documentation", "date": "", "ddg_snippet": "Top journals , including the American Journal of Political Science (AJPS) and the American Political Science Review ( APSR ) require authors reporting empirical ...", "subpage_snippet": "", "source": "wholetale.readthedocs.io", "link": "https://wholetale.readthedocs.io/en/latest/project/cases/political-science.html", "content": "Top journals , including the American Journal of Political Science (AJPS) and the American Political Science Review ( APSR ) require authors reporting empirical ..."}
+{"idx": 9, "title": "American Political Science Review - - Latest issue", "date": "", "ddg_snippet": "The Women, Peace, and Security (WPS) sector assumes increasing the number of women involved in peace negotiations drives better outcomes for local women.", "subpage_snippet": "", "source": "www.cambridge.org", "link": "https://www.cambridge.org/core/journals/american-political-science-review/latest-issue", "content": "The Women, Peace, and Security (WPS) sector assumes increasing the number of women involved in peace negotiations drives better outcomes for local women."}

data/sampled_jsons/Beautiful_Soup_Python_library_primary_function_HTML_parsing.jsonl

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+{"idx": 0, "title": "BeautifulSoup – Scraping Paragraphs from HTML |", "date": "", "ddg_snippet": "... Beautiful Soup (bs4) is a Python library for pulling data ... BeautifulSoup() function helps us to parse the html file or you say the encoding in html .", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/beautifulsoup-scraping-paragraphs-from-html/", "content": "... Beautiful Soup (bs4) is a Python library for pulling data ... BeautifulSoup() function helps us to parse the html file or you say the encoding in html ."}
+{"idx": 1, "title": "Python Web Scraping Tutorial | GeeksforGeeks", "date": "", "ddg_snippet": "Beautiful Soup sits on top of famous Python parsers like LXML and HTML , allowing you to try different parsing strategies or trade speed for ...", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/python-web-scraping-tutorial/", "content": "Beautiful Soup sits on top of famous Python parsers like LXML and HTML , allowing you to try different parsing strategies or trade speed for ..."}
+{"idx": 2, "title": "Implementing Web Scraping in Python with BeautifulSoup |", "date": "", "ddg_snippet": "A really nice thing about the BeautifulSoup library is that it is built on the top of the HTML parsing libraries like html5lib, lxml, html . parser ...", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/implementing-web-scraping-python-beautiful-soup/", "content": "A really nice thing about the BeautifulSoup library is that it is built on the top of the HTML parsing libraries like html5lib, lxml, html . parser ..."}
+{"idx": 3, "title": "Beautifulsoup Installation - Python - GeeksforGeeks", "date": "", "ddg_snippet": "Beautiful Soup is a Python library for pulling data out of HTML and XML files. ... BeautifulSoup BeautifulSoup(bs4) is a Python library for pulling ...", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/beautifulsoup-installation-python/", "content": "Beautiful Soup is a Python library for pulling data out of HTML and XML files. ... BeautifulSoup BeautifulSoup(bs4) is a Python library for pulling ..."}
+{"idx": 4, "title": "Python Parse HTML", "date": "", "ddg_snippet": "Before you start parsing , you need to bring in the Beautiful Soup library with this code. ... Beautiful Soup is excellent for parsing HTML and ...", "subpage_snippet": "", "source": "Serply.io", "link": "https://Serply.io/blog/python-parse-html", "content": "Before you start parsing , you need to bring in the Beautiful Soup library with this code. ... Beautiful Soup is excellent for parsing HTML and ..."}
+{"idx": 5, "title": "4 Best Python Libraries for Efficient Web Scraping (Updated)", "date": "", "ddg_snippet": "BeautifulSoup : This is a Python library used to parse ... Beautiful Soup is one of the best Python libraries for parsing HTML and XML documents.", "subpage_snippet": "", "source": "www.scrapingdog.com", "link": "https://www.scrapingdog.com/blog/best-python-web-scraping-libraries/", "content": "BeautifulSoup : This is a Python library used to parse ... Beautiful Soup is one of the best Python libraries for parsing HTML and XML documents."}
+{"idx": 6, "title": "Web Scraping with Python | A Beginner's Guide | PromptCloud", "date": "", "ddg_snippet": "Requests can be used to retrieve HTML content from web pages, which can then be parsed using Beautiful Soup . ... Beautiful Soup is a convenient-to-use ...", "subpage_snippet": "", "source": "www.promptcloud.com", "link": "https://www.promptcloud.com/blog/web-scraping-python-guide/", "content": "Requests can be used to retrieve HTML content from web pages, which can then be parsed using Beautiful Soup . ... Beautiful Soup is a convenient-to-use ..."}
+{"idx": 7, "title": "Open Source Software in Python", "date": "", "ddg_snippet": "Beautiful Soup - Beautiful Soup is a Python HTML /XML parser designed for quick turnaround projects like screen-scraping.", "subpage_snippet": "", "source": "pythonsource.com:443", "link": "https://pythonsource.com:443/", "content": "Beautiful Soup - Beautiful Soup is a Python HTML /XML parser designed for quick turnaround projects like screen-scraping."}
+{"idx": 8, "title": "Beautiful Soup 4 Python - PythonForBeginners.com", "date": "", "ddg_snippet": "Beautiful Soup is a Python library for pulling data out of HTML and XML files. ... Python script, import the library Now you have to pass something to ...", "subpage_snippet": "", "source": "www.pythonforbeginners.com:443", "link": "https://www.pythonforbeginners.com:443/beautifulsoup/beautifulsoup-4-python", "content": "Beautiful Soup is a Python library for pulling data out of HTML and XML files. ... Python script, import the library Now you have to pass something to ..."}
+{"idx": 9, "title": "Web Scraping with BeautifulSoup - PythonForBeginners.com", "date": "", "ddg_snippet": "Beautiful Soup sits on top of popular Python parsers like lxml and html5lib, allowing you to try out different parsing strategies or trade speed for ...", "subpage_snippet": "", "source": "www.pythonforbeginners.com", "link": "https://www.pythonforbeginners.com/python-on-the-web/web-scraping-with-beautifulsoup", "content": "Beautiful Soup sits on top of popular Python parsers like lxml and html5lib, allowing you to try out different parsing strategies or trade speed for ..."}

data/sampled_jsons/Boltzmann-Aligned_Inverse_Folding_Model_BA-Cycle_method_Section_3.2_difference_previous_methods.jsonl

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+{"idx": 0, "title": "Boltzmann-Aligned Inverse Folding Model as a Predictor of ...", "date": "", "ddg_snippet": "12 Oct 2024 — Next, we present a method (Sec. 3.2 ) that integrates the inverse folding model into Boltzmann alignment . This method is named BA - Cycle and uses ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.09543v1", "content": "12 Oct 2024 — Next, we present a method (Sec. 3.2 ) that integrates the inverse folding model into Boltzmann alignment . This method is named BA - Cycle and uses ..."}
+{"idx": 1, "title": "Energy-Based Models for Predicting Mutational Effects on ...", "date": "", "ddg_snippet": "by P Soga · 2025 — Boltzmann - Aligned Inverse Folding Model as a Predictor of Mu- tational Effects on Protein-Protein Interactions. In The Thirteenth ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/pdf/10.1145/3711896.3736931", "content": "by P Soga · 2025 — Boltzmann - Aligned Inverse Folding Model as a Predictor of Mu- tational Effects on Protein-Protein Interactions. In The Thirteenth ..."}
+{"idx": 2, "title": "A general temperature-guided language model to design ...", "date": "", "ddg_snippet": "27 Nov 2024 — We introduce PRIME, a deep learning model , which can suggest protein mutants with improved stability and activity without any prior experimental mutagenesis ...", "subpage_snippet": "", "source": "www.science.org", "link": "https://www.science.org/doi/10.1126/sciadv.adr2641", "content": "27 Nov 2024 — We introduce PRIME, a deep learning model , which can suggest protein mutants with improved stability and activity without any prior experimental mutagenesis ..."}
+{"idx": 3, "title": "Book", "date": "", "ddg_snippet": "Boltzmann - Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions Xiaoran Jiao, Weian Mao, Wengong Jin, Peiyuan ...", "subpage_snippet": "", "source": "proceedings.iclr.cc", "link": "https://proceedings.iclr.cc/paper_files/paper/2025", "content": "Boltzmann - Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions Xiaoran Jiao, Weian Mao, Wengong Jin, Peiyuan ..."}
+{"idx": 4, "title": "Limitations and challenges in protein stability prediction ...", "date": "", "ddg_snippet": "by T Sanavia · 2020 · Cited by 155 — To model mutations, FoldX uses a rotamer approach , allowing conformational changes of sidechains and keeping the backbone fixed. Another group ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7397395/", "content": "by T Sanavia · 2020 · Cited by 155 — To model mutations, FoldX uses a rotamer approach , allowing conformational changes of sidechains and keeping the backbone fixed. Another group ..."}
+{"idx": 5, "title": "Protein representations: Encoding biological information ...", "date": "", "ddg_snippet": "by D Harding-Larsen · 2024 · Cited by 17 — In this review, we investigate the methodologies for protein representation utilizing the protein sequence, structure, or dynamics. We also analyse the ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0734975024001538", "content": "by D Harding-Larsen · 2024 · Cited by 17 — In this review, we investigate the methodologies for protein representation utilizing the protein sequence, structure, or dynamics. We also analyse the ..."}
+{"idx": 6, "title": "RNA Structural Dynamics As Captured by Molecular Simulations", "date": "", "ddg_snippet": "by J Šponer · 2018 · Cited by 567 — This procedure is analogous to the free-energy perturbation method (see section 3.2 .7) and is used to switch between two alternative force ...", "subpage_snippet": "", "source": "pubs.acs.org", "link": "https://pubs.acs.org/doi/10.1021/acs.chemrev.7b00427", "content": "by J Šponer · 2018 · Cited by 567 — This procedure is analogous to the free-energy perturbation method (see section 3.2 .7) and is used to switch between two alternative force ..."}
+{"idx": 7, "title": "UC Berkeley", "date": "", "ddg_snippet": "by O Zhang · 2025 — At present, few approaches exist for modeling IDRs within the context of folded regions. 167 pages", "subpage_snippet": "", "source": "escholarship.org", "link": "https://escholarship.org/content/qt7xz4z3c4/qt7xz4z3c4.pdf", "content": "by O Zhang · 2025 — At present, few approaches exist for modeling IDRs within the context of folded regions. 167 pages"}
+{"idx": 8, "title": "Statistical Computation for Problems in Dynamic ... - Harvard DASH", "date": "", "ddg_snippet": "loop modeling datasets and compare with other previous methods in Section 3.3. We conclude the paper with a brief discussion in Section 3.4. 3.2 Methods . Our ...", "subpage_snippet": "", "source": "dash.harvard.edu", "link": "https://dash.harvard.edu/bitstreams/891f2837-34ad-48b8-b60f-3a4ca88e179a/download", "content": "loop modeling datasets and compare with other previous methods in Section 3.3. We conclude the paper with a brief discussion in Section 3.4. 3.2 Methods . Our ..."}
+{"idx": 9, "title": "Machine learning meets physics: A two-way street - PMC", "date": "", "ddg_snippet": "by H Levine · 2024 · Cited by 20 — This article introduces a special issue on the interaction between the rapidly expanding field of machine learning and ongoing research in physics.", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11228530/", "content": "by H Levine · 2024 · Cited by 20 — This article introduces a special issue on the interaction between the rapidly expanding field of machine learning and ongoing research in physics."}

data/sampled_jsons/Buchholz_causal_representation_learning_Gaussian_distribution_assumptions.jsonl

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+{"idx": 0, "title": "CausalML", "date": "", "ddg_snippet": "At the moment, I m particularly interested in causal representation learning and applications in biology. ... Causal Representation Learning .", "subpage_snippet": "", "source": "www.juliusvonkugelgen.com", "link": "https://www.juliusvonkugelgen.com/", "content": "At the moment, I m particularly interested in causal representation learning and applications in biology. ... Causal Representation Learning ."}
+{"idx": 1, "title": "Identifying Weight-Variant Latent Causal Models", "date": "", "ddg_snippet": "Despite its advantages, causal representation learning is a notoriously hard problem—without certain assumptions , identifying the true latent ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2208.14153v6", "content": "Despite its advantages, causal representation learning is a notoriously hard problem—without certain assumptions , identifying the true latent ..."}
+{"idx": 2, "title": "On the Origins of Linear Representations in Large Language", "date": "", "ddg_snippet": "First, linear representation structure is not specific to the choice of model architecture, but a by-product of how the model learns the conditional ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2403.03867v1", "content": "First, linear representation structure is not specific to the choice of model architecture, but a by-product of how the model learns the conditional ..."}
+{"idx": 3, "title": "CausalML", "date": "", "ddg_snippet": "At the moment, I m particularly interested in causal representation learning and applications in biology. ... Causal Representation Learning .", "subpage_snippet": "", "source": "sites.google.com", "link": "https://sites.google.com/view/julius-von-kuegelgen/home/", "content": "At the moment, I m particularly interested in causal representation learning and applications in biology. ... Causal Representation Learning ."}
+{"idx": 4, "title": "Bryon Aragam // University of Chicago", "date": "", "ddg_snippet": "This is the goal of the emerging field of causal representation learning (CRL) that uses causality as a vector for building flexible, interpretable ...", "subpage_snippet": "", "source": "www.bryonaragam.com", "link": "http://www.bryonaragam.com/", "content": "This is the goal of the emerging field of causal representation learning (CRL) that uses causality as a vector for building flexible, interpretable ..."}
+{"idx": 5, "title": "Bryon Aragam // University of Chicago", "date": "", "ddg_snippet": "... causal discovery methods and then uses a variational autoencoder (VAE) that is constrained to abide by the Markov factorization of the distribution ...", "subpage_snippet": "", "source": "www.bryonaragam.com", "link": "https://www.bryonaragam.com/", "content": "... causal discovery methods and then uses a variational autoencoder (VAE) that is constrained to abide by the Markov factorization of the distribution ..."}
+{"idx": 6, "title": "Pradeep Ravikumar", "date": "", "ddg_snippet": "Abstract: We consider the linear causal representation learning setting where we observe a linear mixing of $d$ unknown latent factors, which follow ...", "subpage_snippet": "", "source": "www.catalyzex.com", "link": "https://www.catalyzex.com/author/Pradeep+Ravikumar", "content": "Abstract: We consider the linear causal representation learning setting where we observe a linear mixing of $d$ unknown latent factors, which follow ..."}
+{"idx": 7, "title": "Pradeep Ravikumar", "date": "", "ddg_snippet": "Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models. ... Learning Linear Causal Representations from ...", "subpage_snippet": "", "source": "www.csauthors.net", "link": "https://www.csauthors.net/pradeep-ravikumar/", "content": "Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models. ... Learning Linear Causal Representations from ..."}
+{"idx": 8, "title": "Stefan Bauer", "date": "", "ddg_snippet": "Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models.", "subpage_snippet": "", "source": "www.csauthors.net", "link": "https://www.csauthors.net/stefan-bauer/", "content": "Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models."}
+{"idx": 9, "title": "NeurIPS 2023 Orals", "date": "", "ddg_snippet": "... conditioning on discrete events.Our key tool is probability generating functions :they provide a compact closed-form representation of distributions ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2023/events/oral", "content": "... conditioning on discrete events.Our key tool is probability generating functions :they provide a compact closed-form representation of distributions ..."}

data/sampled_jsons/CRAB_benchmark_Xu_et_al_2024a_virtual_agent.jsonl

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+{"idx": 0, "title": "[2407.01511] CRAB: Cross-environment Agent Benchmark for Multimodal ...", "date": "", "ddg_snippet": "To overcome these limitations, we introduce Crab , the first agent benchmark framework designed to support cross-environment tasks, incorporating a graph-based fine-grained evaluation method and an efficient mechanism for task and evaluator construction.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2407.01511", "content": "To overcome these limitations, we introduce Crab , the first agent benchmark framework designed to support cross-environment tasks, incorporating a graph-based fine-grained evaluation method and an efficient mechanism for task and evaluator construction."}
+{"idx": 1, "title": "CRAB: Cross-platform Agent Benchmark for Multimodal ... - GitHub", "date": "", "ddg_snippet": "🌐 Cross-platform and Multi-environment Create build agent environments that support various deployment options including in-memory, Docker-hosted, virtual machines, or distributed physical machines, provided they are accessible via Python functions. Let the agent access all the environments in the same time through a unified interface. ⚙ ️Easy-to-use Configuration Add a new action by ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/camel-ai/crab", "content": "🌐 Cross-platform and Multi-environment Create build agent environments that support various deployment options including in-memory, Docker-hosted, virtual machines, or distributed physical machines, provided they are accessible via Python functions. Let the agent access all the environments in the same time through a unified interface. ⚙ ️Easy-to-use Configuration Add a new action by ..."}
+{"idx": 2, "title": "CRAB: Cross-platfrom agent benchmark for multi-modal embodied language ...", "date": "", "ddg_snippet": "CRAB : Cross-platfrom agent benchmark for multi-modal embodied language model agents Tianqi Xu · Linyao Chen · Dai-Jie Wu · Yanjun Chen · Zecheng Zhang · Xiang Yao · Zhiqiang Xie · Yongchao Chen · Shilong Liu · Bochen Qian · Philip Torr · Bernard Ghanem · Guohao Li", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/100913", "content": "CRAB : Cross-platfrom agent benchmark for multi-modal embodied language model agents Tianqi Xu · Linyao Chen · Dai-Jie Wu · Yanjun Chen · Zecheng Zhang · Xiang Yao · Zhiqiang Xie · Yongchao Chen · Shilong Liu · Bochen Qian · Philip Torr · Bernard Ghanem · Guohao Li"}
+{"idx": 3, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal Language Model ...", "date": "", "ddg_snippet": "To overcome these limitations, we introduce CRAB , the first cross-environment agent benchmark framework, incorporating a graph-based fine-grained evaluation method and an efficient task generation method.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.findings-acl.1113/", "content": "To overcome these limitations, we introduce CRAB , the first cross-environment agent benchmark framework, incorporating a graph-based fine-grained evaluation method and an efficient task generation method."}
+{"idx": 4, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal Language Model ...", "date": "", "ddg_snippet": "CRAB aims to become a general-purpose agent benchmark framework for Multimodal Language Model (MLM) agents . CRAB provides an end-to-end while easy-to-use framework to build agents , operate environments, and create benchmarks to evaluate them, featuring three key components: cross-environment support, a graph evaluator, and task generation.", "subpage_snippet": "", "source": "crab.camel-ai.org", "link": "https://crab.camel-ai.org/", "content": "CRAB aims to become a general-purpose agent benchmark framework for Multimodal Language Model (MLM) agents . CRAB provides an end-to-end while easy-to-use framework to build agents , operate environments, and create benchmarks to evaluate them, featuring three key components: cross-environment support, a graph evaluator, and task generation."}
+{"idx": 5, "title": "(PDF) CRAB: Cross-environment Agent Benchmark for ... - ResearchGate", "date": "", "ddg_snippet": "To overcome these limitations, we introduce Crab , the first agent benchmark framework designed to support cross-environment tasks, incorporating a graph-based fine-grained evaluation method and an ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381910878_CRAB_Cross-environment_Agent_Benchmark_for_Multimodal_Language_Model_Agents", "content": "To overcome these limitations, we introduce Crab , the first agent benchmark framework designed to support cross-environment tasks, incorporating a graph-based fine-grained evaluation method and an ..."}
+{"idx": 6, "title": "Crab: Cross-platform Agent Benchmark for Multimodal Embodied Language ...", "date": "", "ddg_snippet": "To address these limitations, we introduce the Crab framework, a well-defined, highly structured, and unified benchmark framework, which enables agents to interact across multiple environments, incorporates a graph-based, fine-grained evaluation system, and supports automatic task generation.", "subpage_snippet": "", "source": "repository.kaust.edu.sa", "link": "https://repository.kaust.edu.sa/items/d4cba8f4-69ec-4499-a347-9f2908a2b93d", "content": "To address these limitations, we introduce the Crab framework, a well-defined, highly structured, and unified benchmark framework, which enables agents to interact across multiple environments, incorporates a graph-based, fine-grained evaluation system, and supports automatic task generation."}
+{"idx": 7, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal Language Model ...", "date": "", "ddg_snippet": "We build an agent benchmark CRAB Benchmark -v0 featuring with cross-environment, graph evaluator, and task generation through CRAB framework. The environments consists of an Android smartphone emulator and a Ubuntu Linux desktop virtual machine.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2407.01511", "content": "We build an agent benchmark CRAB Benchmark -v0 featuring with cross-environment, graph evaluator, and task generation through CRAB framework. The environments consists of an Android smartphone emulator and a Ubuntu Linux desktop virtual machine."}
+{"idx": 8, "title": "CRAB: CROSS ENVIRONMENT AGENT BENCHMARK FOR MULTIMODAL ... - OpenReview", "date": "", "ddg_snippet": "Leveraging CRAB , we developed a cross-platform Crab Benchmark -v0 comprising 120 tasks in computer desktop and mobile phone envi- ronments. We evaluated 6 advanced MLMs using different single and multi- agent system configurations on this benchmark .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=qqKJjwibsp", "content": "Leveraging CRAB , we developed a cross-platform Crab Benchmark -v0 comprising 120 tasks in computer desktop and mobile phone envi- ronments. We evaluated 6 advanced MLMs using different single and multi- agent system configurations on this benchmark ."}
+{"idx": 9, "title": "CRAB: cross-environment agent benchmark for multimodal language model ...", "date": "", "ddg_snippet": "To overcome these limitations, we introduce CRAB , the first agent benchmark framework designed to support cross-environment tasks, incorporating a graph-based fine-grained evaluation method and an efficient mechanism for task and evaluator construction.", "subpage_snippet": "", "source": "ora.ox.ac.uk", "link": "https://ora.ox.ac.uk/objects/uuid:53a31ad5-7aa7-46c7-aa52-5a5e2dc0e6cd", "content": "To overcome these limitations, we introduce CRAB , the first agent benchmark framework designed to support cross-environment tasks, incorporating a graph-based fine-grained evaluation method and an efficient mechanism for task and evaluator construction."}

data/sampled_jsons/CVE-Bench_A_Benchmark_for_AI_Agents_Ability_to_Exploit_Real-World_Web_Application_Vulnerabilities.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "by Y Zhu · 2025 · Cited by 14 — In CVE - Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real - world conditions.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.17332", "content": "by Y Zhu · 2025 · Cited by 14 — In CVE - Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real - world conditions."}
+{"idx": 1, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "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.", "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."}
+{"idx": 2, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "by Y Zhu · Cited by 12 — We introduce CVE-Bench, a benchmark built from real-world web applications . Each application contains a critical-security vulnerability that actually happened.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=3pk0p4NGmQ", "content": "by Y Zhu · Cited by 12 — We introduce CVE-Bench, a benchmark built from real-world web applications . Each application contains a critical-security vulnerability that actually happened."}
+{"idx": 3, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "by Y Zhu · 2025 · Cited by 12 — In CVE - Bench , we design a sandbox framework that enables LLM agents to exploit vul- nerable web applications in scenarios that mimic real - world ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.17332", "content": "by Y Zhu · 2025 · Cited by 12 — In CVE - Bench , we design a sandbox framework that enables LLM agents to exploit vul- nerable web applications in scenarios that mimic real - world ..."}
+{"idx": 4, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "by Y Zhu · 2025 · Cited by 14 — In CVE - Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real - world conditions.", "subpage_snippet": "", "source": "ui.adsabs.harvard.edu", "link": "https://ui.adsabs.harvard.edu/abs/2025arXiv250317332Z/abstract", "content": "by Y Zhu · 2025 · Cited by 14 — In CVE - Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real - world conditions."}
+{"idx": 5, "title": "[Literature Review] CVE-Bench: A Benchmark for AI Agents ...", "date": "", "ddg_snippet": "21 Mar 2025 — A novel framework called CVE-Bench designed to evaluate the capacities of AI agents, particularly large language models (LLMs), in conducting cyberattacks on ...", "subpage_snippet": "", "source": "www.themoonlight.io", "link": "https://www.themoonlight.io/en/review/cve-bench-a-benchmark-for-ai-agents-ability-to-exploit-real-world-web-application-vulnerabilities", "content": "21 Mar 2025 — A novel framework called CVE-Bench designed to evaluate the capacities of AI agents, particularly large language models (LLMs), in conducting cyberattacks on ..."}
+{"idx": 6, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "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 ...", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/paper/165204", "content": "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 ..."}
+{"idx": 7, "title": "CVE-Bench: A Real-World Cybersecurity Benchmark for ...", "date": "", "ddg_snippet": "23 Apr 2025 — Daniel Kang introduced \" CVE-Bench,\" the first benchmark to evaluate AI agents against real-world cybersecurity vulnerabilities. SESSION ...", "subpage_snippet": "", "source": "far.ai", "link": "https://far.ai/events/sessions/daniel-kang-cve-bench-a-real-world-cybersecurity-benchmark-for-ai-agents", "content": "23 Apr 2025 — Daniel Kang introduced \" CVE-Bench,\" the first benchmark to evaluate AI agents against real-world cybersecurity vulnerabilities. SESSION ..."}
+{"idx": 8, "title": "Chloé Messdaghi's Post - CVE-Bench", "date": "", "ddg_snippet": "Evaluate the capability of AI systems to leverage actual vulnerabilities by utilizing a benchmark that tests them against 40 key CVEs from the National ...", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/chloemessdaghi_cve-bench-a-benchmark-for-ai-agents-ability-activity-7325202007328194560-oJXW", "content": "Evaluate the capability of AI systems to leverage actual vulnerabilities by utilizing a benchmark that tests them against 40 key CVEs from the National ..."}
+{"idx": 9, "title": "Measuring AI Agents' Ability to Exploit Web Applications", "date": "", "ddg_snippet": "In this post, we introduce CVE-bench — the first benchmark built on real-world vulnerabilities, which contains: 40 real-world vulnerability- ...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@danieldkang/measuring-ai-agents-ability-to-exploit-web-applications-ba4225aa281f", "content": "In this post, we introduce CVE-bench — the first benchmark built on real-world vulnerabilities, which contains: 40 real-world vulnerability- ..."}

data/sampled_jsons/Catoni_Contextual_Bandits_Theorem_3.1_Theorem_3.4_regret_bound_σ_t_√(Σσ_t^2).jsonl

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+{"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": "ICML 2022 Papers", "date": "", "ddg_snippet": "SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One -shot Graph Generators ... Versatile Dueling Bandits : Best-of-both ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2022/papers.html", "content": "SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One -shot Graph Generators ... Versatile Dueling Bandits : Best-of-both ..."}
+{"idx": 2, "title": "Extended UCB Policies for Multi-Armed Bandit Problems", "date": "", "ddg_snippet": "... 4 p= 4 and q = 2 q=2 ) to arbitrarily chosen p > q > 1 p > q > 1 as long as the two moments have a known controlled relationship, while ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/1112.1768v5", "content": "... 4 p= 4 and q = 2 q=2 ) to arbitrarily chosen p > q > 1 p > q > 1 as long as the two moments have a known controlled relationship, while ..."}
+{"idx": 3, "title": "How Balanced Should Causal Covariates Be?", "date": "", "ddg_snippet": "A key assumption in causal inference is unconfoundedness [Rosenbaum and Rubin, 1983 ] , which posits that biases of the selection mechanism can be ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.03860v1", "content": "A key assumption in causal inference is unconfoundedness [Rosenbaum and Rubin, 1983 ] , which posits that biases of the selection mechanism can be ..."}
+{"idx": 4, "title": "Machine Learning Feb 2025", "date": "", "ddg_snippet": "Title: LoRA- One : One -Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/list/stat.ML/2025-02", "content": "Title: LoRA- One : One -Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently"}
+{"idx": 5, "title": "The Stats Map · Basic Inequalities", "date": "", "ddg_snippet": "To prove this just apply expectations to the inequality 1 { x ≥ t } ≤ t x 1 { x ≥ t } which holds for all x and all t ≥ 0 .", "subpage_snippet": "", "source": "thestatsmap.com", "link": "https://thestatsmap.com/basic-inequalities", "content": "To prove this just apply expectations to the inequality 1 { x ≥ t } ≤ t x 1 { x ≥ t } which holds for all x and all t ≥ 0 ."}
+{"idx": 6, "title": "The Stats Map · Active Statistical Inference", "date": "", "ddg_snippet": "Suppose we have data ( X i , Y i ) i = 1 N , where Y i is unobserved and X i is observed. ... V ( θ ) = N 1 ( V ( Y ) + E ...", "subpage_snippet": "", "source": "thestatsmap.com", "link": "https://thestatsmap.com/active-statistical-inference", "content": "Suppose we have data ( X i , Y i ) i = 1 N , where Y i is unobserved and X i is observed. ... V ( θ ) = N 1 ( V ( Y ) + E ..."}
+{"idx": 7, "title": "Downloads", "date": "", "ddg_snippet": "3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/Downloads/2022", "content": "3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation"}
+{"idx": 8, "title": "Statistics and Machine Learning Working Group: List of Past", "date": "", "ddg_snippet": "14 Feb 2025 Off-Policy Evaluations of Linear Functionals: From Nonadaptive Semiparametric Efficiency to Adaptive Nonasymptotic Optimality Ojash ...", "subpage_snippet": "", "source": "statml.cs.cmu.edu", "link": "http://statml.cs.cmu.edu/blog/", "content": "14 Feb 2025 Off-Policy Evaluations of Linear Functionals: From Nonadaptive Semiparametric Efficiency to Adaptive Nonasymptotic Optimality Ojash ..."}

data/sampled_jsons/Catoni_Contextual_Bandits_are_Robust_to_Heavy-tailed_Rewards_Assumption_4.1.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Catoni Contextual Bandits are Robust to Heavy - tailed Rewards", "date": "", "ddg_snippet": "This work considers a dierent route for robustness to heavy - tailed rewards , building on the well-studied Catoni ’s mean estimator from the robust statistics literature. We design a contextual bandit (CB)...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.02486", "content": "This work considers a dierent route for robustness to heavy - tailed rewards , building on the well-studied Catoni ’s mean estimator from the robust statistics literature. We design a contextual bandit (CB)..."}
+{"idx": 1, "title": "ICML Poster Catoni Contextual Bandits are Robust to Heavy - tailed ...", "date": "", "ddg_snippet": "Abstract: Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range $[0, R]$, and their regret scales polynomially with this reward range $R$.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46438", "content": "Abstract: Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range $[0, R]$, and their regret scales polynomially with this reward range $R$."}
+{"idx": 2, "title": "Multi-Armed Bandits | Papers With Code", "date": "", "ddg_snippet": "Catoni Contextual Bandits are Robust to Heavy - tailed Rewards .Multi-agent Multi-armed Bandit with Fully Heavy - tailed Dynamics.", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/task/multi-armed-bandits/codeless?page=4", "content": "Catoni Contextual Bandits are Robust to Heavy - tailed Rewards .Multi-agent Multi-armed Bandit with Fully Heavy - tailed Dynamics."}
+{"idx": 3, "title": "Cooperative Multi-Agent Bandits with Heavy Tails", "date": "", "ddg_snippet": "Cooperative Multiagent Bandits with Heavy Tails . tailed effects, which is the central theme of this paper. Catoni (2012) provides this as the optimal achievable rate under heavy tails , and Bubeck et al. (2013) demonstrate that the trimmed mean achieves this rate (see appendix).", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v119/dubey20a/dubey20a.pdf", "content": "Cooperative Multiagent Bandits with Heavy Tails . tailed effects, which is the central theme of this paper. Catoni (2012) provides this as the optimal achievable rate under heavy tails , and Bubeck et al. (2013) demonstrate that the trimmed mean achieves this rate (see appendix)."}
+{"idx": 4, "title": "Bandits Corrupted by Nature: Lower Bounds on Regret and Robust ...", "date": "", "ddg_snippet": "Heavy - tailed bandits . Bubeck et al.The choice of βi reflects the difference between heavy - tailed bandits √and corrupted bandits . When the data are heavy - tailed but not corrupted, Catoni (2012) shows that βi ≃ σi n is a good choice for. the scaling parameter.", "subpage_snippet": "", "source": "hal.science", "link": "https://hal.science/hal-04615733v1/document", "content": "Heavy - tailed bandits . Bubeck et al.The choice of βi reflects the difference between heavy - tailed bandits √and corrupted bandits . When the data are heavy - tailed but not corrupted, Catoni (2012) shows that βi ≃ σi n is a good choice for. the scaling parameter."}
+{"idx": 5, "title": "(PDF) Regret Minimization in Isotonic, Heavy - Tailed Contextual ...", "date": "", "ddg_snippet": "(ii) Bandits with heavy tails — In the multi-armed bandit literature, one typically assumes that the reward . distributions are bounded and sub-gaussian. This assumption is restrictive in applications with heavy", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/355496335_Regret_Minimization_in_Isotonic_Heavy-Tailed_Contextual_Bandits_via_Adaptive_Confidence_Bands", "content": "(ii) Bandits with heavy tails — In the multi-armed bandit literature, one typically assumes that the reward . distributions are bounded and sub-gaussian. This assumption is restrictive in applications with heavy"}
+{"idx": 6, "title": "Nearly optimal regret for stochastic linear bandits with heavy - tailed ...", "date": "", "ddg_snippet": "In linear stochastic bandits , it is commonly assumed that payoffs are with sub-Gaussian noises. In this paper, under a weaker assumption on noises, we study the problem of linear stochastic bandits with heavy - tailed payoffs (LinBET), where the ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3491440.3491846", "content": "In linear stochastic bandits , it is commonly assumed that payoffs are with sub-Gaussian noises. In this paper, under a weaker assumption on noises, we study the problem of linear stochastic bandits with heavy - tailed payoffs (LinBET), where the ..."}
+{"idx": 7, "title": "On Private and Robust Bandits", "date": "", "ddg_snippet": "We study private and robust multi-armed bandits (MABs), where the agent receives Huber’s contaminated heavy - tailed rewards and meanwhile needs to ensure dif-ferential privacy.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/6d13e085b79d454da5910e4ca82a3d9d-Paper-Conference.pdf", "content": "We study private and robust multi-armed bandits (MABs), where the agent receives Huber’s contaminated heavy - tailed rewards and meanwhile needs to ensure dif-ferential privacy."}
+{"idx": 8, "title": "Chenlu Ye - Google Akademik", "date": "", "ddg_snippet": "Corruption- Robust Offline Reinforcement Learning with General Function Approximation. Catoni Contextual Bandits are Robust to Heavy - tailed Rewards .", "subpage_snippet": "", "source": "scholar.google.com.tr", "link": "https://scholar.google.com.tr/citations?user=c8yK5XsAAAAJ&hl=tr", "content": "Corruption- Robust Offline Reinforcement Learning with General Function Approximation. Catoni Contextual Bandits are Robust to Heavy - tailed Rewards ."}
+{"idx": 9, "title": "Optimal Algorithms for Stochastic Multi-Armed", "date": "", "ddg_snippet": "Multi-Armed Bandits with Heavy - Tailed Rewards We compare APE2 with robust UCB [3] and DSEE [17].", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper/2020/file/607bc9ebe4abfcd65181bfbef6252830-Paper.pdf", "content": "Multi-Armed Bandits with Heavy - Tailed Rewards We compare APE2 with robust UCB [3] and DSEE [17]."}

data/sampled_jsons/Causal_Representation_Learning_robust_stochastic_mixing_function_2024_arxiv.jsonl

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+{"idx": 0, "title": "Sanity Checking Causal Representation Learning on a ...", "date": "", "ddg_snippet": "28 Apr 2025 — The underlying causal factors are transformed into observations through a nonlinear and deterministic mixing function (Buchholz et al., 2023, ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.20099v2", "content": "28 Apr 2025 — The underlying causal factors are transformed into observations through a nonlinear and deterministic mixing function (Buchholz et al., 2023, ..."}
+{"idx": 1, "title": "unifying causal representation learning with", "date": "", "ddg_snippet": "by D Yao · 2024 · Cited by 13 — Causal representation learning (CRL ) aims at recovering latent causal variables from high-dimensional observations to solve causal ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2409.02772", "content": "by D Yao · 2024 · Cited by 13 — Causal representation learning (CRL ) aims at recovering latent causal variables from high-dimensional observations to solve causal ..."}
+{"idx": 2, "title": "SPARTAN: A Sparse Transformer Learning Local Causation", "date": "", "ddg_snippet": "by A Lei · 2024 · Cited by 4 — We demonstrate experimentally that learning a sparse, local causal world model improves robustness and adaptation efficiency, and that our model ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2411.06890", "content": "by A Lei · 2024 · Cited by 4 — We demonstrate experimentally that learning a sparse, local causal world model improves robustness and adaptation efficiency, and that our model ..."}
+{"idx": 3, "title": "Causal Representation Learning Made Identifiable by ...", "date": "", "ddg_snippet": "7 Jun 2024 — Here, we show identifiability based on novel, weak constraints, which requires no temporal structure, intervention, nor weak supervision.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2310.15709v2", "content": "7 Jun 2024 — Here, we show identifiability based on novel, weak constraints, which requires no temporal structure, intervention, nor weak supervision."}
+{"idx": 4, "title": "From Causal to Concept-Based Representation Learning", "date": "", "ddg_snippet": "by G Rajendran · 2024 · Cited by 6 — A sparsity principle for partially observable causal representation learning. arXiv preprint. arXiv:2403.08335, 2024 . [134] M. Yang, F. Liu, Z. Chen, X. Shen ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/b76a9959151d377ddd2c77a275a97475-Paper-Conference.pdf", "content": "by G Rajendran · 2024 · Cited by 6 — A sparsity principle for partially observable causal representation learning. arXiv preprint. arXiv:2403.08335, 2024 . [134] M. Yang, F. Liu, Z. Chen, X. Shen ..."}
+{"idx": 5, "title": "Linear Causal Representation Learning from Unknown ...", "date": "", "ddg_snippet": "by B Varıcı · 2024 · Cited by 4 — In this paper, we address the open problem of using unknown multi-node (UMN) stochastic interven- tions to recover the latent causal variables Z ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.05937", "content": "by B Varıcı · 2024 · Cited by 4 — In this paper, we address the open problem of using unknown multi-node (UMN) stochastic interven- tions to recover the latent causal variables Z ..."}
+{"idx": 6, "title": "Unifying Causal Representation Learning and Foundation ...", "date": "", "ddg_snippet": "9 Dec 2024 — In this work, we relate these two approaches and study how to learn human-interpretable concepts from data.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2402.09236v2", "content": "9 Dec 2024 — In this work, we relate these two approaches and study how to learn human-interpretable concepts from data."}
+{"idx": 7, "title": "Disentangled Representation Learning in Non-Markovian ...", "date": "", "ddg_snippet": "by A Li · 2024 · Cited by 5 — Considering various data modalities, such as images, videos, and text, humans perform causal reasoning using high-level causal variables, as opposed to ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/bd7ffcbd088b5e12f3b9eecc9c498b27-Paper-Conference.pdf", "content": "by A Li · 2024 · Cited by 5 — Considering various data modalities, such as images, videos, and text, humans perform causal reasoning using high-level causal variables, as opposed to ..."}
+{"idx": 8, "title": "Causal Representation Learning from Multi-modal ...", "date": "", "ddg_snippet": "by Y Sun · 2025 · Cited by 6 — In this paper, we leverage causal principles to develop theoretically sound ML models for multimodal biomedical data, aiming to provide reliable and ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11952583/", "content": "by Y Sun · 2025 · Cited by 6 — In this paper, we leverage causal principles to develop theoretically sound ML models for multimodal biomedical data, aiming to provide reliable and ..."}
+{"idx": 9, "title": "arXiv:2306.01213v4 [cs.LG] 23 Aug 2024", "date": "", "ddg_snippet": "by A Komanduri · 2023 · Cited by 17 — We propose ICM-VAE, a framework for learning causally disentangled representations supervised by causally related ob- served labels. We model ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2306.01213", "content": "by A Komanduri · 2023 · Cited by 17 — We propose ICM-VAE, a framework for learning causally disentangled representations supervised by causally related ob- served labels. We model ..."}

data/sampled_jsons/Checks-and-Balances_Framework_Section_3.2_four-step_self-supervised_learning_process_mapping_behavio.jsonl

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+{"idx": 0, "title": "Order Personal Checks Online At Affordable Prices | Checks.com", "date": "", "ddg_snippet": "We print an exceptional collection of high-quality personal checks at cheap prices. Whether you are buying a checkbook for the first time or are reordering your favorite check design, you’ll always get the same low price - no discounts codes required.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/", "content": "We print an exceptional collection of high-quality personal checks at cheap prices. Whether you are buying a checkbook for the first time or are reordering your favorite check design, you’ll always get the same low price - no discounts codes required."}
+{"idx": 1, "title": "View Over 70 Personal Checks Designs at Low Prices", "date": "", "ddg_snippet": "Order your favorite personal checks online at low prices. Checks .com features a variety of over 70 personal check designs to fit your unique personality.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/c/129/personal-checks", "content": "Order your favorite personal checks online at low prices. Checks .com features a variety of over 70 personal check designs to fit your unique personality."}
+{"idx": 2, "title": "Value Checks - Order Our Best Value Checks Online", "date": "", "ddg_snippet": "Order value-priced personal checks online starting at just $8.20 per box at Checks .com! We have a variety of inexpensive check designs to choose from, so you can find the perfect one to match your style and budget.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/c/323/value-checks", "content": "Order value-priced personal checks online starting at just $8.20 per box at Checks .com! We have a variety of inexpensive check designs to choose from, so you can find the perfect one to match your style and budget."}
+{"idx": 3, "title": "How To Order Checks Online | Checks.com", "date": "", "ddg_snippet": "Order checks , address labels and checkbook covers online, secure, fast and easy with Checks .com. Customize and preview your checks before you order.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/how-to-order-checks", "content": "Order checks , address labels and checkbook covers online, secure, fast and easy with Checks .com. Customize and preview your checks before you order."}
+{"idx": 4, "title": "Traditional Checks - Order Affordable Personal Checks Online", "date": "", "ddg_snippet": "Checks .com's collection of traditional checks offers the widest variety of designs where you're sure to find a favorite or two. Also check out our line of Choice Checks for our most exclusive and most secure check designs, or browse our cheaper-priced checks for an incredibly low price per box.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/c/334/traditional-checks", "content": "Checks .com's collection of traditional checks offers the widest variety of designs where you're sure to find a favorite or two. Also check out our line of Choice Checks for our most exclusive and most secure check designs, or browse our cheaper-priced checks for an incredibly low price per box."}
+{"idx": 5, "title": "Reorder Discounted Personal Checks Online", "date": "", "ddg_snippet": "At Checks .com, whenever you reorder checks , you pay the same low price as intro customers. Reorder checks for discounted prices online today!", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/quickreorder", "content": "At Checks .com, whenever you reorder checks , you pay the same low price as intro customers. Reorder checks for discounted prices online today!"}
+{"idx": 6, "title": "Renaissance Checks - Order Discounted Personal Checks", "date": "", "ddg_snippet": "Artistic scrolls and elegance grace these renaissance checks in a rich four color rotation. Coordinating renaissance address labels and checkbook cover are also available.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/p/834/renaissance-checks", "content": "Artistic scrolls and elegance grace these renaissance checks in a rich four color rotation. Coordinating renaissance address labels and checkbook cover are also available."}
+{"idx": 7, "title": "Modern Checks - Order Cool & Contemporary Personal Checks", "date": "", "ddg_snippet": "Show your trendy style with contemporary and cool personal checks from Checks .com! Choose a stylish check design or pattern and order checks online today!", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/c/274/modern-checks", "content": "Show your trendy style with contemporary and cool personal checks from Checks .com! Choose a stylish check design or pattern and order checks online today!"}
+{"idx": 8, "title": "Pretty in Pink Checks - Order Discounted Personal Checks", "date": "", "ddg_snippet": "Discover the perfect blend of Parisian style and elegance with our Pretty in Pink checks . Designed for those who live life with flair, these top-tear pink personal checks are available in four vibrant designs featuring stripes, polka dots and diamond patterns.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/p/1799/pretty-in-pink-checks", "content": "Discover the perfect blend of Parisian style and elegance with our Pretty in Pink checks . Designed for those who live life with flair, these top-tear pink personal checks are available in four vibrant designs featuring stripes, polka dots and diamond patterns."}
+{"idx": 9, "title": "Horse Checks - Order Discounted Personal Checks", "date": "", "ddg_snippet": "Horse Play Checks Photographs of galloping horses adorn this equine rotation of stallions, mustangs and foals. Coordinating horse return address labels are available.", "subpage_snippet": "", "source": "www.checks.com", "link": "https://www.checks.com/p/811/horse-play-checks", "content": "Horse Play Checks Photographs of galloping horses adorn this equine rotation of stallions, mustangs and foals. Coordinating horse return address labels are available."}

data/sampled_jsons/Concept_Bottleneck_Models_Without_Predefined_Concepts_abstract.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Concept Bottleneck Models Without Predefined Concepts", "date": "", "ddg_snippet": "by S Schrodi · 2024 · Cited by 8 — Abstract:There has been considerable recent interest in interpretable concept-based models such as Concept Bottleneck Models (CBMs), ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2407.03921", "content": "by S Schrodi · 2024 · Cited by 8 — Abstract:There has been considerable recent interest in interpretable concept-based models such as Concept Bottleneck Models (CBMs), ..."}
+{"idx": 1, "title": "Selective Concept Bottleneck Models Without Predefined ...", "date": "", "ddg_snippet": "by S Schrodi — We present a method to convert black-box models into concept bottleneck models without predefined concepts and introduce an input-dependent concept selection ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=uuvujfQXZy", "content": "by S Schrodi — We present a method to convert black-box models into concept bottleneck models without predefined concepts and introduce an input-dependent concept selection ..."}
+{"idx": 2, "title": "Concept Bottleneck Models Without Predefined Concepts", "date": "", "ddg_snippet": "4 Jul 2024 — One popular framework are Concept Bottleneck Models (CBMs ) [1] , i.e., models that first predicts human-interpretable concepts and then use ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2407.03921v1", "content": "4 Jul 2024 — One popular framework are Concept Bottleneck Models (CBMs ) [1] , i.e., models that first predicts human-interpretable concepts and then use ..."}
+{"idx": 3, "title": "Selective Concept Bottleneck Models Without Predefined ...", "date": "", "ddg_snippet": "In this work, we discover the concepts encoded by the model through unsupervised concept discovery techniques instead. We further leverage a simple input- ...", "subpage_snippet": "", "source": "tmlr.infinite-conf.org", "link": "https://tmlr.infinite-conf.org/paper_pages/PMO30TLI4l.html", "content": "In this work, we discover the concepts encoded by the model through unsupervised concept discovery techniques instead. We further leverage a simple input- ..."}
+{"idx": 4, "title": "Hierarchical concept Bottleneck models for vision and their ...", "date": "", "ddg_snippet": "by F Pittino · 2023 · Cited by 12 — In this work we develop and discuss a Concept Bottleneck model for images segmentation, objects fine classification and tracking, and compare it to more ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0952197622006649", "content": "by F Pittino · 2023 · Cited by 12 — In this work we develop and discuss a Concept Bottleneck model for images segmentation, objects fine classification and tracking, and compare it to more ..."}
+{"idx": 5, "title": "Cross-Modal Conceptualization in Bottleneck Models", "date": "", "ddg_snippet": "by D Alukaev · 2023 · Cited by 7 — The objective of this study is to enhance the prac- ticality of Concept Bottleneck Models by elimi- nating the need for predefined concepts ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2023.emnlp-main.318.pdf", "content": "by D Alukaev · 2023 · Cited by 7 — The objective of this study is to enhance the prac- ticality of Concept Bottleneck Models by elimi- nating the need for predefined concepts ..."}
+{"idx": 6, "title": "improving the predictability of concept bottleneck models", "date": "", "ddg_snippet": "We establish theoretical results for concept - bottleneck models (CBMs), revealing how these properties guide the design of concept sets that optimize model ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/poster/93623", "content": "We establish theoretical results for concept - bottleneck models (CBMs), revealing how these properties guide the design of concept sets that optimize model ..."}
+{"idx": 7, "title": "Learning Bottleneck Concepts in Image Classification", "date": "", "ddg_snippet": "by B Wang · 2023 · Cited by 88 — This paper proposes Bot- tleneck Concept Learner (BotCL), which represents an im- age solely by the presence/absence of concepts learned through training over ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2023/papers/Wang_Learning_Bottleneck_Concepts_in_Image_Classification_CVPR_2023_paper.pdf", "content": "by B Wang · 2023 · Cited by 88 — This paper proposes Bot- tleneck Concept Learner (BotCL), which represents an im- age solely by the presence/absence of concepts learned through training over ..."}
+{"idx": 8, "title": "LABEL-FREE CONCEPT BOTTLENECK MODELS", "date": "", "ddg_snippet": "Given a neural network backbone, Label-free CBM transforms the backbone into an interpretable CBM without the need of concept labels with the following 4 steps ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/f6e0ef2be0578f171a67040f6fc6873a70f1ac9c.pdf", "content": "Given a neural network backbone, Label-free CBM transforms the backbone into an interpretable CBM without the need of concept labels with the following 4 steps ..."}
+{"idx": 9, "title": "Label-Free Concept Bottleneck Models", "date": "", "ddg_snippet": "by T Oikarinen · 2023 · Cited by 264 — A novel framework to transform any neural network into an interpretable CBM without labeled concept data, while retaining a high accuracy.", "subpage_snippet": "", "source": "ui.adsabs.harvard.edu", "link": "https://ui.adsabs.harvard.edu/abs/2023arXiv230406129O/abstract", "content": "by T Oikarinen · 2023 · Cited by 264 — A novel framework to transform any neural network into an interpretable CBM without labeled concept data, while retaining a high accuracy."}

data/sampled_jsons/Coordinate-wise_Private_Median_and_the_l_infinity_Guarantee_challenge_regression_solution_vector.jsonl

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+{"idx": 0, "title": "Approximation guarantees of Median Mechanism in $\\\\mathbb{R}^d$ A Nearly-Optimal Bound for Fast Regression with $\\\\ell ... Coordinate-Wise Median in Byzantine Federated Learning Approximation Guarantees of Median Mechanism in Rd arXiv:2502.08578v2 [cs.GT] 13 Feb 2025 Communication-efficient and Byzantine-robust distributed ... Optimality of the coordinate-wise median mechanism for ...", "date": "", "ddg_snippet": "Feb 12, 2025 · The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approximation ratio in d -dimensional spaces. Apr 24, 2023 · Moreover, we develop a novel analytical framework for $\\ell_\\infty$ guarantee regression that utilizes the Oblivious Coordinate-wise Embedding (OCE) property introduced in [Song and Yu, ICML'21]. Our analysis is much simpler and more general than that of [Price, Song and Woodruff, ICALP'17]. Abstract Federated learning enables clients to train local models on private data while exchanging model updates only. A key step in this pro-cess is gradient aggregation. We investigate the coordinate-wise median as an aggregation rule in both centralized and decentralized federated learning under Byzantine failures. In order to lower the communication cost in the decentralized setting, we ... The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approx-imation ratio in -dimensional spaces. Feb 13, 2025 · The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approximation ratio in d-dimensional spaces. √ The best known approximation guarantee in May 1, 2023 · One algorithm is based on communication-efficient surrogate likelihood framework, another algorithm integrates approximate proximal point technique into the first algorithm. The two algorithms both explore two robust local gradient aggregation schemes: coordinate-wise median and coordinate-wise trimmed mean. We show that the trimmed-mean-based We refer to the generalized coordinate-wise median mechanism with 0 constant points and the standard coordinate -system as the coordinate-wise median mechanism and denote it by c(x).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.08578", "content": "Feb 12, 2025 · The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approximation ratio in d -dimensional spaces. Apr 24, 2023 · Moreover, we develop a novel analytical framework for $\\ell_\\infty$ guarantee regression that utilizes the Oblivious Coordinate-wise Embedding (OCE) property introduced in [Song and Yu, ICML'21]. Our analysis is much simpler and more general than that of [Price, Song and Woodruff, ICALP'17]. Abstract Federated learning enables clients to train local models on private data while exchanging model updates only. A key step in this pro-cess is gradient aggregation. We investigate the coordinate-wise median as an aggregation rule in both centralized and decentralized federated learning under Byzantine failures. In order to lower the communication cost in the decentralized setting, we ... The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approx-imation ratio in -dimensional spaces. Feb 13, 2025 · The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approximation ratio in d-dimensional spaces. √ The best known approximation guarantee in May 1, 2023 · One algorithm is based on communication-efficient surrogate likelihood framework, another algorithm integrates approximate proximal point technique into the first algorithm. The two algorithms both explore two robust local gradient aggregation schemes: coordinate-wise median and coordinate-wise trimmed mean. We show that the trimmed-mean-based We refer to the generalized coordinate-wise median mechanism with 0 constant points and the standard coordinate -system as the coordinate-wise median mechanism and denote it by c(x)."}
+{"idx": 1, "title": "A Nearly-Optimal Bound for Fast Regression with $\\\\ell ...", "date": "", "ddg_snippet": "Apr 24, 2023 · Moreover, we develop a novel analytical framework for $\\ell_\\infty$ guarantee regression that utilizes the Oblivious Coordinate-wise Embedding (OCE) property introduced in [Song and Yu, ICML'21]. Our analysis is much simpler and more general than that of [Price, Song and Woodruff, ICALP'17].", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=cJh37mrFms", "content": "Apr 24, 2023 · Moreover, we develop a novel analytical framework for $\\ell_\\infty$ guarantee regression that utilizes the Oblivious Coordinate-wise Embedding (OCE) property introduced in [Song and Yu, ICML'21]. Our analysis is much simpler and more general than that of [Price, Song and Woodruff, ICALP'17]."}
+{"idx": 2, "title": "Coordinate-Wise Median in Byzantine Federated Learning", "date": "", "ddg_snippet": "Abstract Federated learning enables clients to train local models on private data while exchanging model updates only. A key step in this pro-cess is gradient aggregation. We investigate the coordinate-wise median as an aggregation rule in both centralized and decentralized federated learning under Byzantine failures. In order to lower the communication cost in the decentralized setting, we ...", "subpage_snippet": "", "source": "schmiste.github.io", "link": "https://schmiste.github.io/asiaccs25.pdf", "content": "Abstract Federated learning enables clients to train local models on private data while exchanging model updates only. A key step in this pro-cess is gradient aggregation. We investigate the coordinate-wise median as an aggregation rule in both centralized and decentralized federated learning under Byzantine failures. In order to lower the communication cost in the decentralized setting, we ..."}
+{"idx": 3, "title": "Approximation Guarantees of Median Mechanism in Rd", "date": "", "ddg_snippet": "The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approx-imation ratio in -dimensional spaces.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/epdf/10.1145/3717823.3718156", "content": "The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approx-imation ratio in -dimensional spaces."}
+{"idx": 4, "title": "Communication-efficient and Byzantine-robust distributed ...", "date": "", "ddg_snippet": "May 1, 2023 · One algorithm is based on communication-efficient surrogate likelihood framework, another algorithm integrates approximate proximal point technique into the first algorithm. The two algorithms both explore two robust local gradient aggregation schemes: coordinate-wise median and coordinate-wise trimmed mean. We show that the trimmed-mean-based", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S0031320323000134", "content": "May 1, 2023 · One algorithm is based on communication-efficient surrogate likelihood framework, another algorithm integrates approximate proximal point technique into the first algorithm. The two algorithms both explore two robust local gradient aggregation schemes: coordinate-wise median and coordinate-wise trimmed mean. We show that the trimmed-mean-based"}
+{"idx": 5, "title": "Optimality of the coordinate-wise median mechanism for ...", "date": "", "ddg_snippet": "We refer to the generalized coordinate-wise median mechanism with 0 constant points and the standard coordinate -system as the coordinate-wise median mechanism and denote it by c(x).", "subpage_snippet": "", "source": "whanncar.github.io", "link": "https://whanncar.github.io/papers/median.pdf", "content": "We refer to the generalized coordinate-wise median mechanism with 0 constant points and the standard coordinate -system as the coordinate-wise median mechanism and denote it by c(x)."}
+{"idx": 6, "title": "Efficient Sparse Least Absolute Deviation Regression with", "date": "", "ddg_snippet": "... by reformulating the sparse LAD problem as a penalized least square estimation problem and adopts a three-stage noise injection to guarantee the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2401.01294v1", "content": "... by reformulating the sparse LAD problem as a penalized least square estimation problem and adopts a three-stage noise injection to guarantee the ..."}
+{"idx": 7, "title": "Real-time Bus Travel Time Prediction and Reliability", "date": "", "ddg_snippet": "However, this remains a challenging task due to the limitations of existing models and data sources. ... the parameters of the distributions were ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.05907v1", "content": "However, this remains a challenging task due to the limitations of existing models and data sources. ... the parameters of the distributions were ..."}
+{"idx": 8, "title": "Approximation, Randomization, and Combinatorial Optimization.", "date": "", "ddg_snippet": "... them can a carpenter cut out using a panel saw making guillotine cuts, i.e., only moving forward through the material along a straight line until it ...", "subpage_snippet": "", "source": "drops.dagstuhl.de", "link": "https://drops.dagstuhl.de/entities/volume/LIPIcs-volume-40", "content": "... them can a carpenter cut out using a panel saw making guillotine cuts, i.e., only moving forward through the material along a straight line until it ..."}
+{"idx": 9, "title": "arXiv:2502.08578v2 [cs.GT] 13 Feb 2025", "date": "", "ddg_snippet": "Feb 13, 2025 · The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approximation ratio in d-dimensional spaces. √ The best known approximation guarantee in", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.08578", "content": "Feb 13, 2025 · The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approximation ratio in d-dimensional spaces. √ The best known approximation guarantee in"}

data/sampled_jsons/Crocker_stacks_persistent_homology.jsonl

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+{"idx": 0, "title": "Persistent homology approach for uncovering transitions to Chaos", "date": "", "ddg_snippet": "Conclusion This study demonstrates the effectiveness of using persistent homology to uncover topological insights in the time series of dynamic systems. By varying the control parameter, we observed different transitions in the behavior of the system, which are reflected in the time series.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S0960077925000670", "content": "Conclusion This study demonstrates the effectiveness of using persistent homology to uncover topological insights in the time series of dynamic systems. By varying the control parameter, we observed different transitions in the behavior of the system, which are reflected in the time series."}
+{"idx": 1, "title": "Persistent Topological Features in Large Language Models", "date": "", "ddg_snippet": "Differently than standard persistent homology , short- and long-lived features represent how the model dynamically evolves. Short-lived features indicate a high rate of rearrangement of the points x i between adjacent layers, while long-lived features suggest a phase of retention of (relative) positions in the model.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.11042v1", "content": "Differently than standard persistent homology , short- and long-lived features represent how the model dynamically evolves. Short-lived features indicate a high rate of rearrangement of the points x i between adjacent layers, while long-lived features suggest a phase of retention of (relative) positions in the model."}
+{"idx": 2, "title": "A roadmap for the computation of persistent homology - PMC", "date": "", "ddg_snippet": "Abstract Persistent homology (PH) is a method used in topological data analysis (TDA) to study qualitative features of data that persist across multiple scales. It is robust to perturbations of input data, independent of dimensions and coordinates, and provides a compact representation of the qualitative features of the input. The computation of PH is an open area with numerous important and ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6979512/", "content": "Abstract Persistent homology (PH) is a method used in topological data analysis (TDA) to study qualitative features of data that persist across multiple scales. It is robust to perturbations of input data, independent of dimensions and coordinates, and provides a compact representation of the qualitative features of the input. The computation of PH is an open area with numerous important and ..."}
+{"idx": 3, "title": "A Case Study on Identifying Bifurcation and Chaos with CROCKER Plots", "date": "", "ddg_snippet": "A proposed persistent homology point summary, conformance, was able to identify models with successful dynamics learning and detect discrepancies in the manifold density distribution.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/359937143_A_Case_Study_on_Identifying_Bifurcation_and_Chaos_with_CROCKER_Plots", "content": "A proposed persistent homology point summary, conformance, was able to identify models with successful dynamics learning and detect discrepancies in the manifold density distribution."}
+{"idx": 4, "title": "TDA: Applications and Deep Dive into Persistent Homology", "date": "", "ddg_snippet": "This article aims to introduce readers to the basics of Topological Data Analysis (TDA), focusing on persistent homology and its applications. This concept is crucial because it serves as the ...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@kennywang2003/topological-data-analysis-persistent-homology-22636f4e34bf", "content": "This article aims to introduce readers to the basics of Topological Data Analysis (TDA), focusing on persistent homology and its applications. This concept is crucial because it serves as the ..."}
+{"idx": 5, "title": "Persistent homology approach for uncovering transitions to Chaos", "date": "", "ddg_snippet": "The CROCKER plot is an interactive visualization technique used to track changes in the homology of data over varying parameters. CROCKER stands for \"Contour Realization Of Computed k -dimensional hole Evolution in the VR complex\" [44] and provides a comprehensive visual representation of PH.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0960077925000670", "content": "The CROCKER plot is an interactive visualization technique used to track changes in the homology of data over varying parameters. CROCKER stands for \"Contour Realization Of Computed k -dimensional hole Evolution in the VR complex\" [44] and provides a comprehensive visual representation of PH."}
+{"idx": 6, "title": "Capturing dynamics of time-varying data via topology", "date": "", "ddg_snippet": "Crocker stacks are convenient for visualization, amenable to machine learning, and satisfy a desirable continuity property which we prove. We demonstrate the utility of crocker stacks for a parameter identification task involving an influential model of biological aggregations [57].", "subpage_snippet": "", "source": "www.aimsciences.org", "link": "https://www.aimsciences.org/article/id/2acaee54-6688-46a4-b35d-447f84c4c691", "content": "Crocker stacks are convenient for visualization, amenable to machine learning, and satisfy a desirable continuity property which we prove. We demonstrate the utility of crocker stacks for a parameter identification task involving an influential model of biological aggregations [57]."}
+{"idx": 7, "title": "Lu Xian Henry Adams Chad M. Topaz Lori Ziegelmeier", "date": "", "ddg_snippet": "these are the same components as scale ε varies. However, as we will show in Section 6, since the crocker stack contains enough information to recover the persistent homology barcodes, one can confirm these are the same connected components as ε varies by considerin", "subpage_snippet": "", "source": "par.nsf.gov", "link": "https://par.nsf.gov/servlets/purl/10388958", "content": "these are the same components as scale ε varies. However, as we will show in Section 6, since the crocker stack contains enough information to recover the persistent homology barcodes, one can confirm these are the same connected components as ε varies by considerin"}
+{"idx": 8, "title": "PDF Neural Persistence Dynamics - proceedings.neurips.cc", "date": "", "ddg_snippet": "In the following, we present a runtime breakdown of the pre-processing steps (i.e., Vietoris-Rips persistent homology (PH) computation, and the vectorization of persistence diagrams), as well as a runtime comparison to prior work (PSK and crocker stacks ) and our baseline approach.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/3a509449a73fd0aab8c0cf5705827036-Paper-Conference.pdf", "content": "In the following, we present a runtime breakdown of the pre-processing steps (i.e., Vietoris-Rips persistent homology (PH) computation, and the vectorization of persistence diagrams), as well as a runtime comparison to prior work (PSK and crocker stacks ) and our baseline approach."}
+{"idx": 9, "title": "PDF Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series ...", "date": "", "ddg_snippet": "An alternative to zigzag but a closely related approach to assess properties of time-varying data with per-sistent homology , namely, crocker stacks , has been recently suggested by Xian et al. (2020), though the crocker stacks representations are not learnable in DL models.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v139/chen21o/chen21o.pdf", "content": "An alternative to zigzag but a closely related approach to assess properties of time-varying data with per-sistent homology , namely, crocker stacks , has been recently suggested by Xian et al. (2020), though the crocker stacks representations are not learnable in DL models."}

data/sampled_jsons/Curriculum_Learning_Physics-Informed_Neural_Networks_year_2023.jsonl

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+{"idx": 0, "title": "Meta-learning (computer science) - Wikipedia", "date": "", "ddg_snippet": "A Memory-Augmented Neural Network , or MANN for short, is claimed to be able to encode new information quickly and thus to adapt to new tasks after ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Meta-learning_(computer_science)", "content": "A Memory-Augmented Neural Network , or MANN for short, is claimed to be able to encode new information quickly and thus to adapt to new tasks after ..."}
+{"idx": 1, "title": "Machine learning - Wikipedia", "date": "", "ddg_snippet": "1 Within a subdiscipline in machine learning , advances in the field of deep learning have allowed neural networks , a class of statistical algorithms ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Machine_learning", "content": "1 Within a subdiscipline in machine learning , advances in the field of deep learning have allowed neural networks , a class of statistical algorithms ..."}
+{"idx": 2, "title": "Self-supervised learning - Wikipedia", "date": "", "ddg_snippet": "In the context of neural networks , self-supervised learning aims to leverage inherent structures or relationships within the input data to create ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Self-supervised_learning", "content": "In the context of neural networks , self-supervised learning aims to leverage inherent structures or relationships within the input data to create ..."}
+{"idx": 3, "title": "Feature learning - Wikipedia", "date": "", "ddg_snippet": "Multilayer neural networks can be used to perform feature learning , since they learn a representation of their input at the hidden layer(s) which is ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Feature_learning", "content": "Multilayer neural networks can be used to perform feature learning , since they learn a representation of their input at the hidden layer(s) which is ..."}
+{"idx": 4, "title": "Conference on Neural Information Processing Systems - Wikipedia", "date": "", "ddg_snippet": "The first proceedings was published in book form by the American Institute of Physics in 1987, and was entitled Neural Information Processing Systems ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Conference_on_Neural_Information_Processing_Systems", "content": "The first proceedings was published in book form by the American Institute of Physics in 1987, and was entitled Neural Information Processing Systems ..."}
+{"idx": 5, "title": "DataPro | 0 articles | Packt Learning Hub", "date": "", "ddg_snippet": "Its architecture includes novel training strategies like GRPO, curriculum learning , and expert initialization, making it a new benchmark in ...", "subpage_snippet": "", "source": "www.packtpub.com", "link": "https://www.packtpub.com/en-ic/learning/datapro", "content": "Its architecture includes novel training strategies like GRPO, curriculum learning , and expert initialization, making it a new benchmark in ..."}
+{"idx": 6, "title": "Chen Xu | DeepAI", "date": "", "ddg_snippet": "Transfer learning based physics - informed neural networks for solving inverse problems in tunneling ... learning methods called physics - informed ne ...", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/profile/chen-xu-6525", "content": "Transfer learning based physics - informed neural networks for solving inverse problems in tunneling ... learning methods called physics - informed ne ..."}
+{"idx": 7, "title": "Shiji Song | DeepAI", "date": "", "ddg_snippet": "Learning Specialized Activation Functions for Physics - informed Neural ... Physics - informed neural networks (PINNs) are known to suffer from optimi...", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/profile/shiji-song", "content": "Learning Specialized Activation Functions for Physics - informed Neural ... Physics - informed neural networks (PINNs) are known to suffer from optimi..."}
+{"idx": 8, "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"}
+{"idx": 9, "title": "Downloads", "date": "", "ddg_snippet": "... for Multi-Objective Reinforcement Learning ... Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/Downloads/2021", "content": "... for Multi-Objective Reinforcement Learning ... Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach"}

data/sampled_jsons/Cybench_A_Framework_for_Evaluating_Cybersecurity_Capabilities_abstract.jsonl

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+{"idx": 0, "title": "[2408.08926] Cybench : A Framework for Evaluating Cybersecurity ...", "date": "", "ddg_snippet": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks. We include 40 professional-level Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2408.08926", "content": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks. We include 40 professional-level Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful..."}
+{"idx": 1, "title": "(PDF) Cybench : A Framework for Evaluating Cybersecurity ...", "date": "", "ddg_snippet": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks. We include 40 professional-level Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/383236134_Cybench_A_Framework_for_Evaluating_Cybersecurity_Capabilities_and_Risk_of_Language_Models", "content": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks. We include 40 professional-level Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful..."}
+{"idx": 2, "title": "Cybench : A Framework for Evaluating Cybersecurity Capabilities ...", "date": "", "ddg_snippet": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks.1 We include 40 professionallevel Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful, and spanning a wide range...", "subpage_snippet": "", "source": "ee.stanford.edu", "link": "https://ee.stanford.edu/cybench-framework-evaluating-cybersecurity-capabilities-and-risks-language-models", "content": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks.1 We include 40 professionallevel Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful, and spanning a wide range..."}
+{"idx": 3, "title": "Cybench : A Framework for Evaluating Cybersecurity Capabilities ...", "date": "", "ddg_snippet": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks. We include 40 professional-level Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=tc90LV0yRL", "content": "Toward that end, we introduce Cybench , a framework for specifying cybersecurity tasks and evaluating agents on those tasks. We include 40 professional-level Capture the Flag (CTF) tasks from 4 distinct CTF competitions, chosen to be recent, meaningful..."}
+{"idx": 4, "title": "GitHub - andyzorigin/ cybench", "date": "", "ddg_snippet": "Cybench : A Framework for Evaluating Cybersecurity Capabilities and Risk. This repository contains code used in the Cybench project (website, paper), which serves to evaluate agent capabilities and risks on cybersecurity tasks. Cybench includes the following features", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/andyzorigin/cybench", "content": "Cybench : A Framework for Evaluating Cybersecurity Capabilities and Risk. This repository contains code used in the Cybench project (website, paper), which serves to evaluate agent capabilities and risks on cybersecurity tasks. Cybench includes the following features"}
+{"idx": 5, "title": "Cybench : A Framework for Evaluating Cybersecurity Capabilities ...", "date": "", "ddg_snippet": "This paper presents Cybench , a framework designed to evaluate the cybersecurity capabilities and risks of language models (LMs) in identifying vulnerabilities and executing exploits.", "subpage_snippet": "", "source": "ai-search.io", "link": "https://ai-search.io/papers/cybench-a-framework-for-evaluating-cybersecurity-capabilities-and-risk-of-language-models", "content": "This paper presents Cybench , a framework designed to evaluate the cybersecurity capabilities and risks of language models (LMs) in identifying vulnerabilities and executing exploits."}
+{"idx": 6, "title": "Can LLM Agents Compete in CTFs?. Evaluating LLM... | Medium", "date": "", "ddg_snippet": "Cybench is a framework designed to evaluate language models' (LMs) ability to solve cybersecurity tasks like Capture the Flag (CTF) challenges. It allows AI agents to identify vulnerabilities, execute exploits, and solve tasks in a structured environment.", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@arohablue/can-ai-compete-in-ctf-b6d9016ff254", "content": "Cybench is a framework designed to evaluate language models' (LMs) ability to solve cybersecurity tasks like Capture the Flag (CTF) challenges. It allows AI agents to identify vulnerabilities, execute exploits, and solve tasks in a structured environment."}
+{"idx": 7, "title": "Google News - Cybersecurity threats to language models - Overview", "date": "", "ddg_snippet": "Cybench : A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models.", "subpage_snippet": "", "source": "news.google.com", "link": "https://news.google.com/stories/CAAqNggKIjBDQklTSGpvSmMzUnZjbmt0TXpZd1NoRUtEd2kxcllQNERSSGxSZ0JldXB4UE1TZ0FQAQ?hl=en-US&gl=US&ceid=US:en", "content": "Cybench : A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models."}
+{"idx": 8, "title": "AI Task Length Horizons in Offensive Cybersecurity — LessWrong", "date": "", "ddg_snippet": "I asked the same question for offensive cybersecurity , a domain with distinct skills and unique AI-safety implications. Using METR’s methodology on five cyber benchmarks, with tasks ranging from 0.5s to 25h in human-expert estimated times...", "subpage_snippet": "", "source": "www.lesswrong.com", "link": "https://www.lesswrong.com/posts/fjgYkTWKAXSxsxdsj/preload", "content": "I asked the same question for offensive cybersecurity , a domain with distinct skills and unique AI-safety implications. Using METR’s methodology on five cyber benchmarks, with tasks ranging from 0.5s to 25h in human-expert estimated times..."}
+{"idx": 9, "title": "2025.02.20 xAI Risk Management Framework Draft - Google Docs", "date": "", "ddg_snippet": "capabilities for benign or beneficial purposes, such as scientifically investigating Grok’s capabilities for risk assessment purposes, or if such requests cover information that is already readily and easily available, including by an internet search.", "subpage_snippet": "", "source": "x.ai", "link": "https://x.ai/documents/2025.02.20-RMF-Draft.pdf", "content": "capabilities for benign or beneficial purposes, such as scientifically investigating Grok’s capabilities for risk assessment purposes, or if such requests cover information that is already readily and easily available, including by an internet search."}

data/sampled_jsons/DCBM_GitHub_min_area_max_area_area_threshold.jsonl

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+{"idx": 0, "title": "GitHub - deepopo/DCBM", "date": "", "ddg_snippet": "This is an implementation of the IEEE TPAMI paper The Decoupling Concept Bottleneck Model ( DCBM ). The vision-language-model (VLM) part is being refined and will be available soon. Figure 1: DCBM Pipeline. (A) DCBM for prediction and interpretation. (B) DCBM for human-machine interaction, including forward intervention and backward rectification.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/deepopo/DCBM", "content": "This is an implementation of the IEEE TPAMI paper The Decoupling Concept Bottleneck Model ( DCBM ). The vision-language-model (VLM) part is being refined and will be available soon. Figure 1: DCBM Pipeline. (A) DCBM for prediction and interpretation. (B) DCBM for human-machine interaction, including forward intervention and backward rectification."}
+{"idx": 1, "title": "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. However, current CBMs typically rely on concept sets extracted from large language models or extensive image corpora, limiting their effectiveness in data-sparse scenarios. We propose Data-efficient CBMs ( DCBMs ), which reduce the need for large sample sizes ...", "subpage_snippet": "", "source": "kathpra.github.io", "link": "https://kathpra.github.io/DCBM/", "content": "Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts. However, current CBMs typically rely on concept sets extracted from large language models or extensive image corpora, limiting their effectiveness in data-sparse scenarios. We propose Data-efficient CBMs ( DCBMs ), which reduce the need for large sample sizes ..."}
+{"idx": 2, "title": "DCBM/main.py at main · deepopo/DCBM · GitHub", "date": "", "ddg_snippet": "Contribute to deepopo/ DCBM development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/deepopo/DCBM/blob/main/main.py", "content": "Contribute to deepopo/ DCBM development by creating an account on GitHub ."}
+{"idx": 3, "title": "[Support]: Min Max Ratio help · Issue #8350 - GitHub", "date": "", "ddg_snippet": "person: min_area : 18000 # max_area : 100000 # min_ratio: 0.5 how is this worked out ? # max_ratio: 2.0 how is this worked out ? # min_score: 0.5 threshold: 0.75 Also on a separate question can I run a Google coral on top of using my Nvidia gpu or is it one or the other? Version 12.1 Frigate config file ui:", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/blakeblackshear/frigate/issues/8350", "content": "person: min_area : 18000 # max_area : 100000 # min_ratio: 0.5 how is this worked out ? # max_ratio: 2.0 how is this worked out ? # min_score: 0.5 threshold: 0.75 Also on a separate question can I run a Google coral on top of using my Nvidia gpu or is it one or the other? Version 12.1 Frigate config file ui:"}
+{"idx": 4, "title": "Releases · KathPra/DCBM · GitHub", "date": "", "ddg_snippet": "Official repo for ICML25 paper: DCBM : Data-Efficient Visual Concept Bottleneck Models - Releases · KathPra/ DCBM", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/KathPra/DCBM/releases", "content": "Official repo for ICML25 paper: DCBM : Data-Efficient Visual Concept Bottleneck Models - Releases · KathPra/ DCBM"}
+{"idx": 5, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "Abstract Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts. However, current CBMs typically rely on con-cept sets extracted from large language models or extensive image corpora, limiting their effec-tiveness in data-sparse scenarios. We propose Data-eficient CBMs ( DCBMs ), which reduce the need for large ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2412.11576v3", "content": "Abstract Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts. However, current CBMs typically rely on con-cept sets extracted from large language models or extensive image corpora, limiting their effec-tiveness in data-sparse scenarios. We propose Data-eficient CBMs ( DCBMs ), which reduce the need for large ..."}
+{"idx": 6, "title": "GitHub - fraspass/dcsbm: Spectral clustering on spherical coordinates ...", "date": "", "ddg_snippet": "The code in this repository can be used to reproduce the results and simulations in Sanna Passino, F., Heard, N. A., and Rubin-Delanchy, P. (2021) \"Spectral clustering on spherical coordinates under the degree-corrected stochastic blockmodel\", Technometrics (to appear, link to the arXiv publication).", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/fraspass/dcsbm", "content": "The code in this repository can be used to reproduce the results and simulations in Sanna Passino, F., Heard, N. A., and Rubin-Delanchy, P. (2021) \"Spectral clustering on spherical coordinates under the degree-corrected stochastic blockmodel\", Technometrics (to appear, link to the arXiv publication)."}
+{"idx": 7, "title": "openmv学习之旅②之色块追踪算法的改善 - CSDN博客", "date": "", "ddg_snippet": "area_threshold 面积阈值，如果色块被框起来的面积小于这个值，会被过滤掉。 pixels_threshold 像素个数阈值，如果色块像素数量小于这个值，会被过滤掉 merge 合并，如果设置为True，那么合并所有重叠的blob为一个。 注意：这会合并所有的blob，无论是什么颜色的。", "subpage_snippet": "", "source": "blog.csdn.net", "link": "https://blog.csdn.net/jiejiemcu/article/details/80579893", "content": "area_threshold 面积阈值，如果色块被框起来的面积小于这个值，会被过滤掉。 pixels_threshold 像素个数阈值，如果色块像素数量小于这个值，会被过滤掉 merge 合并，如果设置为True，那么合并所有重叠的blob为一个。 注意：这会合并所有的blob，无论是什么颜色的。"}
+{"idx": 8, "title": "cvp_detailed.ipynb - Colab", "date": "", "ddg_snippet": "The min_area and max_area parameters here can help to look at a different set of plaques within the size range of the default value of these parameters can be used.", "subpage_snippet": "", "source": "colab.research.google.com", "link": "https://colab.research.google.com/github/plaque2/PyPlaque/blob/master/notebooks/cvp_detailed.ipynb", "content": "The min_area and max_area parameters here can help to look at a different set of plaques within the size range of the default value of these parameters can be used."}
+{"idx": 9, "title": "Exact Meaning of the parameters given to initialize MSER in OpenCV 2.4 ...", "date": "", "ddg_snippet": "OpenCV reference manual (2.4.x) states that the constructor that initializes MSER requires the following parameters: delta, min_area , max_area , max_variation, min_diversity, max_evolution, area_threshold , min_margin, edge_blur_size. I am dealing with grayscale images. What is the use of the parameters \"delta\", \"max_variation\" and \"min_diversity\"? What property of an MSER do these parameters ...", "subpage_snippet": "", "source": "stackoverflow.com", "link": "https://stackoverflow.com/questions/17647500/exact-meaning-of-the-parameters-given-to-initialize-mser-in-opencv-2-4-x", "content": "OpenCV reference manual (2.4.x) states that the constructor that initializes MSER requires the following parameters: delta, min_area , max_area , max_variation, min_diversity, max_evolution, area_threshold , min_margin, edge_blur_size. I am dealing with grayscale images. What is the use of the parameters \"delta\", \"max_variation\" and \"min_diversity\"? What property of an MSER do these parameters ..."}

data/sampled_jsons/Descriptor-In-Pixel_SCAMP-7_Computation_Time_Breakdown_Table_1_exact_values_numbers_percentages.jsonl

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+{"idx": 0, "title": "PDF Descriptor-In-Pixel : Point-Feature Tracking For Pixel Processor Arrays", "date": "", "ddg_snippet": "A breakdown of the total computation time per frame is given in Table 1 . To put these numbers into perspective, the time taken to out-put a full uncompressed image from the sensor is well over 20000 μs, and even a 4-bit image requires 2700 μs.", "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": "A breakdown of the total computation time per frame is given in Table 1 . To put these numbers into perspective, the time taken to out-put a full uncompressed image from the sensor is well over 20000 μs, and even a 4-bit image requires 2700 μs."}
+{"idx": 1, "title": "PDF Live Demonstration: SCAMP-7 - GitHub Pages", "date": "", "ddg_snippet": "The program development environment will be demonstrated alongside discussion of specific programming techniques for pixel parallel processor arrays and the new features of the SCAMP-7 device. Figure 1 . SCAMP-5 system vs SCAMP-7 system.", "subpage_snippet": "", "source": "tub-rip.github.io", "link": "https://tub-rip.github.io/eventvision2023/papers/2023CVPRW_Live_Demonstration_Scamp-7.pdf", "content": "The program development environment will be demonstrated alongside discussion of specific programming techniques for pixel parallel processor arrays and the new features of the SCAMP-7 device. Figure 1 . SCAMP-5 system vs SCAMP-7 system."}
+{"idx": 2, "title": "SCAMP Vision Sensor - University of Manchester", "date": "", "ddg_snippet": "The SCAMP Vision Sensor integrates a massively parallel SIMD processor array into the pixels of the image sensor device. Unlike a conventional image sensor, it does not output raw images, but rather the results of on-sensor computations , for instance a feature map, optic flow map and/or address-events describing locations of pixels of interest. The device is fully programmable, to execute a ...", "subpage_snippet": "", "source": "personalpages.manchester.ac.uk", "link": "https://personalpages.manchester.ac.uk/staff/p.dudek/scamp/", "content": "The SCAMP Vision Sensor integrates a massively parallel SIMD processor array into the pixels of the image sensor device. Unlike a conventional image sensor, it does not output raw images, but rather the results of on-sensor computations , for instance a feature map, optic flow map and/or address-events describing locations of pixels of interest. The device is fully programmable, to execute a ..."}
+{"idx": 3, "title": "Live Demonstration: SCAMP-7 - IEEE Xplore", "date": "", "ddg_snippet": "We propose to demonstrate the next generation of the SCAMP vision sensor, SCAMP-7 , whose architecture embeds programmable processing cores into each pixel . This IC allows various computer vision tasks to be performed \"on-sensor\" at high speeds while avoiding the slow and power hungry transfer of image data off the device. Through in-pixel computations over the image array, visual information ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/10208514", "content": "We propose to demonstrate the next generation of the SCAMP vision sensor, SCAMP-7 , whose architecture embeds programmable processing cores into each pixel . This IC allows various computer vision tasks to be performed \"on-sensor\" at high speeds while avoiding the slow and power hungry transfer of image data off the device. Through in-pixel computations over the image array, visual information ..."}
+{"idx": 4, "title": "Bose Descriptor-In-Pixel Point-Feature Tracking For Pixel Processor ...", "date": "", "ddg_snippet": "This paper introduces a novel method for point-feature detection and tracking using Pixel Processor Array (PPA) vision sensors, which enables in-pixel computation and significantly reduces data transfer requirements. The proposed Descriptor-In-Pixel paradigm allows for efficient processing at over 3000 FPS, making it suitable for high-speed applications while maintaining low latency. By ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/890539401/Bose-Descriptor-In-Pixel-Point-Feature-Tracking-for-Pixel-Processor-Arrays-CVPR-2025-Paper", "content": "This paper introduces a novel method for point-feature detection and tracking using Pixel Processor Array (PPA) vision sensors, which enables in-pixel computation and significantly reduces data transfer requirements. The proposed Descriptor-In-Pixel paradigm allows for efficient processing at over 3000 FPS, making it suitable for high-speed applications while maintaining low latency. By ..."}
+{"idx": 5, "title": "Live Demonstration: SCAMP-7 - computer.org", "date": "", "ddg_snippet": "We propose to demonstrate the next generation of the SCAMP vision sensor, SCAMP-7 , whose architecture embeds programmable processing cores into each pixel . This IC allows various computer vision tasks to be performed", "subpage_snippet": "", "source": "www.computer.org", "link": "https://www.computer.org/csdl/proceedings-article/cvprw/2023/024900d995/1PBy0sv9HtC", "content": "We propose to demonstrate the next generation of the SCAMP vision sensor, SCAMP-7 , whose architecture embeds programmable processing cores into each pixel . This IC allows various computer vision tasks to be performed"}
+{"idx": 6, "title": "SCAMP Vision Sensor", "date": "", "ddg_snippet": "The SCAMP vision sensor integrates a massively parallel SIMD processor array into the pixels of the image sensor device. It does not output raw images, like a conventional camera, but rather the results of on-sensor computations , for instance a feature map, optic flow map and/or address-events describing locations of pixels of interest. As costly early vision computations are done entirely on ...", "subpage_snippet": "", "source": "www.scamp-vision-chip.org", "link": "https://www.scamp-vision-chip.org/", "content": "The SCAMP vision sensor integrates a massively parallel SIMD processor array into the pixels of the image sensor device. It does not output raw images, like a conventional camera, but rather the results of on-sensor computations , for instance a feature map, optic flow map and/or address-events describing locations of pixels of interest. As costly early vision computations are done entirely on ..."}
+{"idx": 7, "title": "Descriptor In Pixel : Point Feature Tracking for Pixel ... - YouTube", "date": "", "ddg_snippet": "Instead of standard pixels , PPA sensors consists of thousands of \" pixel -processors\", enabling massive parallel computation of visual data at the point of light capture.", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=HIdQtf6mFSs", "content": "Instead of standard pixels , PPA sensors consists of thousands of \" pixel -processors\", enabling massive parallel computation of visual data at the point of light capture."}
+{"idx": 8, "title": "Live Demonstration: CNN Inference on the Focal Plane with a Pixel ...", "date": "", "ddg_snippet": "We present a novel method of CNN inference on a pixel processor array device, demonstrating it using a handwritten digit (digits 0-9) classification task, with all steps of the neural network computation performed on the focal plane. The vision chip that we deploy ( SCAMP-7 ) has a 256×256 array of processor elements (PE) integrated within the image sensor. The algorithm runs at over 3000 ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/9180959", "content": "We present a novel method of CNN inference on a pixel processor array device, demonstrating it using a handwritten digit (digits 0-9) classification task, with all steps of the neural network computation performed on the focal plane. The vision chip that we deploy ( SCAMP-7 ) has a 256×256 array of processor elements (PE) integrated within the image sensor. The algorithm runs at over 3000 ..."}
+{"idx": 9, "title": "Descriptor-In-Pixel : Point-Feature Tracking For Pixel Processor Arrays", "date": "", "ddg_snippet": "To achieve this we store feature descriptors inside every pixel -processor, adjusting the layout of these descriptors every frame. The PPA's architecture enables us to compute the response of every stored descriptor in parallel. This \"response map\" is utilized for both detection and tracking of point-features across the pixel -processor array.", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/32867", "content": "To achieve this we store feature descriptors inside every pixel -processor, adjusting the layout of these descriptors every frame. The PPA's architecture enables us to compute the response of every stored descriptor in parallel. This \"response map\" is utilized for both detection and tracking of point-features across the pixel -processor array."}

data/sampled_jsons/DnCNN_GitHub_official_year_2017.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "GitHub - cszn/DnCNN: Beyond a Gaussian Denoiser: Residual Learning of ...", "date": "", "ddg_snippet": "The parameters in DnCNN are mainly representing the image priors (task-independent), thus it is possible to learn a single model for different tasks, such as image denoising, image super-resolution and JPEG image deblocking. The left is the input image corrupted by different degradations, the right is the restored image by DnCNN-3.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/cszn/DnCNN", "content": "The parameters in DnCNN are mainly representing the image priors (task-independent), thus it is possible to learn a single model for different tasks, such as image denoising, image super-resolution and JPEG image deblocking. The left is the input image corrupted by different degradations, the right is the restored image by DnCNN-3."}
+{"idx": 1, "title": "DnCNN/README.md at master · cszn/DnCNN · GitHub", "date": "", "ddg_snippet": "The parameters in DnCNN are mainly representing the image priors (task-independent), thus it is possible to learn a single model for different tasks, such as image denoising, image super-resolution and JPEG image deblocking. The left is the input image corrupted by different degradations, the right is the restored image by DnCNN-3.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/cszn/DnCNN/blob/master/README.md", "content": "The parameters in DnCNN are mainly representing the image priors (task-independent), thus it is possible to learn a single model for different tasks, such as image denoising, image super-resolution and JPEG image deblocking. The left is the input image corrupted by different degradations, the right is the restored image by DnCNN-3."}
+{"idx": 2, "title": "GitHub - SaoYan/DnCNN-PyTorch: PyTorch implementation of the TIP2017 ...", "date": "", "ddg_snippet": "PyTorch implementation of the TIP2017 paper \"Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising\" - SaoYan/ DnCNN -PyTorch", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/SaoYan/DnCNN-PyTorch", "content": "PyTorch implementation of the TIP2017 paper \"Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising\" - SaoYan/ DnCNN -PyTorch"}
+{"idx": 3, "title": "GitHub - PuffannXu/DnCNN", "date": "", "ddg_snippet": "Contribute to PuffannXu/ DnCNN development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/PuffannXu/DnCNN", "content": "Contribute to PuffannXu/ DnCNN development by creating an account on GitHub ."}
+{"idx": 4, "title": "dncnn · GitHub Topics · GitHub", "date": "", "ddg_snippet": "GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/topics/dncnn?o=desc&s=updated", "content": "GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects."}
+{"idx": 5, "title": "build minimal library · Tencent/ncnn Wiki · GitHub", "date": "", "ddg_snippet": "For some reason, if you're not happy with the binary size of the ncnn library, then here is the cheatsheet that helps you to build a minimal ncnn :P cmake -DNCNN_DISABLE_RTTI=ON -DNCNN_DISABLE_EXCEPTION=ON .. Cannot use RTTI and Exceptions when ncnn functions are called. cmake -DNCNN_PIXEL_DRAWING ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Tencent/ncnn/wiki/build-minimal-library", "content": "For some reason, if you're not happy with the binary size of the ncnn library, then here is the cheatsheet that helps you to build a minimal ncnn :P cmake -DNCNN_DISABLE_RTTI=ON -DNCNN_DISABLE_EXCEPTION=ON .. Cannot use RTTI and Exceptions when ncnn functions are called. cmake -DNCNN_PIXEL_DRAWING ..."}
+{"idx": 6, "title": "DnCNN - Aditya Rastogi, PhD", "date": "", "ddg_snippet": "DnCNN This repository contains the codes for the implementation of the paper - Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. This was done as part of a course project. Introduction During the past decade, convolutional neural networks have shown great success in handling various low-level vision tasks. Image denoising is one such long-standing problem in ...", "subpage_snippet": "", "source": "adityarastogi2k12.github.io", "link": "https://adityarastogi2k12.github.io/Projects/NNLS/", "content": "DnCNN This repository contains the codes for the implementation of the paper - Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. This was done as part of a course project. Introduction During the past decade, convolutional neural networks have shown great success in handling various low-level vision tasks. Image denoising is one such long-standing problem in ..."}
+{"idx": 7, "title": "DnCNN - Image noise remover - atikul-islam-sajib.github.io", "date": "", "ddg_snippet": "DnCNN - Residual Learning of Deep CNN for Image Denoising The DnCNN (Denoising Convolutional Neural Network) is a deep learning model designed for image denoising tasks, offering state-of-the-art performance by learning end-to-end mappings from noisy to clean images. It employs a deep architecture consisting of several convolutional layers without any fully connected layers, enabling it to ...", "subpage_snippet": "", "source": "atikul-islam-sajib.github.io", "link": "https://atikul-islam-sajib.github.io/DnCNN-deploy/", "content": "DnCNN - Residual Learning of Deep CNN for Image Denoising The DnCNN (Denoising Convolutional Neural Network) is a deep learning model designed for image denoising tasks, offering state-of-the-art performance by learning end-to-end mappings from noisy to clean images. It employs a deep architecture consisting of several convolutional layers without any fully connected layers, enabling it to ..."}
+{"idx": 8, "title": "Charts - DnCNN - Image noise remover", "date": "", "ddg_snippet": "A class used to represent and perform operations for model visualization, including selecting the best model based on loss, loading data, normalizing images, creating GIFs from training images, and plotting comparison images (noisy, clean, predicted) using Matplotlib.", "subpage_snippet": "", "source": "atikul-islam-sajib.github.io", "link": "https://atikul-islam-sajib.github.io/DnCNN-deploy/charts/", "content": "A class used to represent and perform operations for model visualization, including selecting the best model based on loss, loading data, normalizing images, creating GIFs from training images, and plotting comparison images (noisy, clean, predicted) using Matplotlib."}
+{"idx": 9, "title": "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image ...", "date": "", "ddg_snippet": "With the residual learning strategy, DnCNN implicitly removes the latent clean image in the hidden layers. This property motivates us to train a single DnCNN model to tackle with several general image denoising tasks such as Gaussian denoising, single image super-resolution and JPEG image deblocking.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1608.03981", "content": "With the residual learning strategy, DnCNN implicitly removes the latent clean image in the hidden layers. This property motivates us to train a single DnCNN model to tackle with several general image denoising tasks such as Gaussian denoising, single image super-resolution and JPEG image deblocking."}

data/sampled_jsons/Do_Not_Trust_What_They_Tell_Exposing_Malicious_Accomplices_in_Tor_Section_4.3_Equation_8_conn(a,b)_a.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Do Not Trust What They Tell: Exposing Malicious Accomplices in Tor via ...", "date": "", "ddg_snippet": "This paper presents a novel approach for detecting anomalous circuits in the Tor network, and for the first time provides a more comprehensive identification of potential malicious accomplice nodes in Tor by taking roles of nodes in anomalous circuits into consideration.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3696410.3714767", "content": "This paper presents a novel approach for detecting anomalous circuits in the Tor network, and for the first time provides a more comprehensive identification of potential malicious accomplice nodes in Tor by taking roles of nodes in anomalous circuits into consideration."}
+{"idx": 1, "title": "PDF Do Not Trust What They Tell: Exposing Malicious Accomplices in Tor via ...", "date": "", "ddg_snippet": "Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection. In Proceedings of the ACM Web Conference 2025 (WWW '25), April 28-May 2, 2025, Sydney, NSW, Australia.", "subpage_snippet": "", "source": "cse.seu.edu.cn", "link": "https://cse.seu.edu.cn/_upload/article/files/82/36/84188a1a47a79fe2b6dc589a1c39/a6db7ad8-3fef-4518-8046-480a6ac64280.pdf", "content": "Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection. In Proceedings of the ACM Web Conference 2025 (WWW '25), April 28-May 2, 2025, Sydney, NSW, Australia."}
+{"idx": 2, "title": "通过异常电路检测揭露Tor中的恶意同伙 - 安全内参 | 决策者的网络安全知识库", "date": "", "ddg_snippet": "提出了一种方法来检测Tor网络中的异常电路，通过考虑节点在异常电路中的角色，首次提供了一个更全面的方法识别tor中的 ...", "subpage_snippet": "", "source": "www.secrss.com", "link": "https://www.secrss.com/articles/76608", "content": "提出了一种方法来检测Tor网络中的异常电路，通过考虑节点在异常电路中的角色，首次提供了一个更全面的方法识别tor中的 ..."}
+{"idx": 3, "title": "PDF Defending Against Malicious Cyber Activity Originating from Tor - CISA", "date": "", "ddg_snippet": "Defending Against Malicious Cyber Activity Originating from Tor This advisory—written by the Cybersecurity Security and Infrastructure Security Agency (CISA) with contributions from the Federal Bureau of Investigation (FBI)—highlights risks associated with Tor , along with technical details and recommendations for mitigation. Cyber threat actors can use Tor software and network ...", "subpage_snippet": "", "source": "www.cisa.gov", "link": "https://www.cisa.gov/sites/default/files/publications/AA20-183A_Defending_Against_Malicious_Cyber_Activity_Originating_from_Tor_S508C.pdf", "content": "Defending Against Malicious Cyber Activity Originating from Tor This advisory—written by the Cybersecurity Security and Infrastructure Security Agency (CISA) with contributions from the Federal Bureau of Investigation (FBI)—highlights risks associated with Tor , along with technical details and recommendations for mitigation. Cyber threat actors can use Tor software and network ..."}
+{"idx": 4, "title": "通过异常电路检测揭露tor中的恶意同伙", "date": "", "ddg_snippet": "原文标题： Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection 原文作者：Yixuan Yao, Ming Yang, Zixia Liu, Kai Dong, Xiaodan-Gu, Chunmian Wang", "subpage_snippet": "", "source": "sechub.in", "link": "https://sechub.in/view/3027398", "content": "原文标题： Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection 原文作者：Yixuan Yao, Ming Yang, Zixia Liu, Kai Dong, Xiaodan-Gu, Chunmian Wang"}
+{"idx": 5, "title": "Do Not Trust What They Tell: Exposing Malicious Accomplices in Tor via ...", "date": "", "ddg_snippet": "This feature describes the rela-tionship of two nodes in term of their abnormal behavioral patterns, which can be identified through the method in Section 4.2. We intro-(, ) duce a connectivity metric in Equation ( 8 ) to quantify this relationship between nodes and .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=qcnePVejeV", "content": "This feature describes the rela-tionship of two nodes in term of their abnormal behavioral patterns, which can be identified through the method in Section 4.2. We intro-(, ) duce a connectivity metric in Equation ( 8 ) to quantify this relationship between nodes and ."}
+{"idx": 6, "title": "Spoiled Onions: Exposing Malicious Tor Exit Relays", "date": "", "ddg_snippet": "Tor exit relays are operated by volunteers and together push more than 1 GiB/s of network traffic. By design, these volunteers are able to inspect and modify the anonymized network traffic. In this paper, we seek to expose such malicious exit relays and document...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/chapter/10.1007/978-3-319-08506-7_16", "content": "Tor exit relays are operated by volunteers and together push more than 1 GiB/s of network traffic. By design, these volunteers are able to inspect and modify the anonymized network traffic. In this paper, we seek to expose such malicious exit relays and document..."}
+{"idx": 7, "title": "Submissions | OpenReview", "date": "", "ddg_snippet": "Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection Yixuan Yao, Ming Yang, Zixia Liu, Kai Dong, Xiaodan-Gu, Chunmian Wang", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/submissions?venue=ACM.org/TheWebConf/2025/Conference", "content": "Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection Yixuan Yao, Ming Yang, Zixia Liu, Kai Dong, Xiaodan-Gu, Chunmian Wang"}
+{"idx": 8, "title": "PDF DEF CON 24 Hacking Conference", "date": "", "ddg_snippet": "Abstract—Tor is a widely used anonymity network that protects users' privacy and identity from corporations, agencies and governments. However, Tor remains a practical system with a variety of limitations which can be subverted [1]. In particular, Tor's security relies on the fact that a substantial number of its nodes do not misbehave.", "subpage_snippet": "", "source": "media.defcon.org", "link": "https://media.defcon.org/DEF+CON+24/DEF+CON+24+presentations/DEF+CON+24+-+Guevara-Noubir-Amirali-Sanatinia-Honey-Onions-Exposing-Snooping-Tor-Hsdir-Relays-WP.pdf", "content": "Abstract—Tor is a widely used anonymity network that protects users' privacy and identity from corporations, agencies and governments. However, Tor remains a practical system with a variety of limitations which can be subverted [1]. In particular, Tor's security relies on the fact that a substantial number of its nodes do not misbehave."}
+{"idx": 9, "title": "Xiaodan Gu - dblp", "date": "", "ddg_snippet": "Yixuan Yao, Ming Yang, Zixia Liu, Kai Dong, Xiaodan Gu, Chunmian Wang: Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection. WWW 2025: 2959-2968", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/pid/148/7260", "content": "Yixuan Yao, Ming Yang, Zixia Liu, Kai Dong, Xiaodan Gu, Chunmian Wang: Do Not Trust What They Tell : Exposing Malicious Accomplices in Tor via Anomalous Circuit Detection. WWW 2025: 2959-2968"}

data/sampled_jsons/ETHICS_dataset_reasons_context-aware_ethical_alignment_empirical_evaluation.jsonl

@@ -0,0 +1,6 @@
+{"idx": 0, "title": "Daily Papers - Hugging Face", "date": "", "ddg_snippet": "Ethical Reasoning over Moral Alignment : A Case and Framework for In- Context Ethical Policies in LLMs.With the ETHICS dataset , we find that current language models have a promising but incomplete ability to predict basic human ethical judgements.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=ethical+verification+framework", "content": "Ethical Reasoning over Moral Alignment : A Case and Framework for In- Context Ethical Policies in LLMs.With the ETHICS dataset , we find that current language models have a promising but incomplete ability to predict basic human ethical judgements."}
+{"idx": 1, "title": "(PDF) On the Trustworthiness of Generative Foundation Models...", "date": "", "ddg_snippet": "In constructing the dynamic dataset for testing LLM ethics , the following ethical considerations. and procedures are observed: (a) Initially, the metadata curator utilizes a dataset pool derived from several key.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/389176427_On_the_Trustworthiness_of_Generative_Foundation_Models_Guideline_Assessment_and_Perspective", "content": "In constructing the dynamic dataset for testing LLM ethics , the following ethical considerations. and procedures are observed: (a) Initially, the metadata curator utilizes a dataset pool derived from several key."}
+{"idx": 2, "title": "Daily Papers - Hugging Face", "date": "", "ddg_snippet": "To address the need for ethical judgment in CIR, we present the QA- ETHICS dataset , adapted from the ETHICS benchmark, which serves as an evaluation tool by unifying scenarios and label meanings.", "subpage_snippet": "", "source": "hf.qhduan.com", "link": "https://hf.qhduan.com/papers?q=code+retrieval", "content": "To address the need for ethical judgment in CIR, we present the QA- ETHICS dataset , adapted from the ETHICS benchmark, which serves as an evaluation tool by unifying scenarios and label meanings."}
+{"idx": 3, "title": "Daily Papers", "date": "", "ddg_snippet": "6 days ago — Our empirical evaluation demonstrates that our approach leads to a ... To this end, we introduce a workflow that integrates ethical alignment , ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=objection+detection", "content": "6 days ago — Our empirical evaluation demonstrates that our approach leads to a ... To this end, we introduce a workflow that integrates ethical alignment , ..."}
+{"idx": 4, "title": "Daily Papers", "date": "", "ddg_snippet": "A comprehensive empirical evaluation exhibits ... ETHICS dataset , adapted from the ETHICS benchmark ... Our research provides a practical method for introducing ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers?q=Conversational+QA", "content": "A comprehensive empirical evaluation exhibits ... ETHICS dataset , adapted from the ETHICS benchmark ... Our research provides a practical method for introducing ..."}
+{"idx": 5, "title": "On the Trustworthiness of Generative Foundation Models", "date": "", "ddg_snippet": "7 Nov 2024 — ethical alignment ... detailed logging of decision pathways [1788], and context-aware explanations [1789] can illuminate where and why . 231 pages", "subpage_snippet": "", "source": "howiehwong.github.io", "link": "https://howiehwong.github.io/TrustGen.pdf", "content": "7 Nov 2024 — ethical alignment ... detailed logging of decision pathways [1788], and context-aware explanations [1789] can illuminate where and why . 231 pages"}

data/sampled_jsons/EntityErasure_arxiv_IoS_intersection_over_segmentation_equation_threshold.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Jaccard index - Wikipedia", "date": "", "ddg_snippet": "The Jaccard index is a statistic used for gauging the similarity and diversity of sample sets. It is defined in general taking the ratio of two sizes, the intersection size divided by the union size, also called intersection over union.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Jaccard_index", "content": "The Jaccard index is a statistic used for gauging the similarity and diversity of sample sets. It is defined in general taking the ratio of two sizes, the intersection size divided by the union size, also called intersection over union."}
+{"idx": 1, "title": "EntityErasure: Erasing Entity Cleanly via Amodal Entity ...", "date": "", "ddg_snippet": "As shown Fig. 4, we use the pre-trained state-of-the-art open-world segmentation model EntitySeg [30] to predict the en-tity segmentation of the generated result, and then calculate the Intersection over Self ( IoS ) between each entity with in-painting mask by:", "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": "As shown Fig. 4, we use the pre-trained state-of-the-art open-world segmentation model EntitySeg [30] to predict the en-tity segmentation of the generated result, and then calculate the Intersection over Self ( IoS ) between each entity with in-painting mask by:"}
+{"idx": 2, "title": "EntityErasure: Erasing Entity Cleanly via Amodal Entity ...", "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/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 ..."}
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data/sampled_jsons/EventPS_Real-time_photometric_stereo_using_an_event_camera_CVPR_2022_Yu_year_2022.jsonl

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+{"idx": 2, "title": "FlowDec | A flow -based full-band general audio codec with high...", "date": "", "ddg_snippet": "For FlowDec , DAC, and DAC - 75 , we show both examples at a higher bitrate (7.0 - 7.75 kbps ) as well as at a lower bitrate (4.3 - 4 . 5 kbps ). You can choose between Speech, Music and Audio Files.", "subpage_snippet": "", "source": "sp-uhh.github.io", "link": "https://sp-uhh.github.io/FlowDec/", "content": "For FlowDec , DAC, and DAC - 75 , we show both examples at a higher bitrate (7.0 - 7.75 kbps ) as well as at a lower bitrate (4.3 - 4 . 5 kbps ). You can choose between Speech, Music and Audio Files."}
+{"idx": 3, "title": "Математика 4 класс Моро. Часть 1. Страница 18 Номер 2", "date": "", "ddg_snippet": "Часть 1. Страница 18 Номер 2 900 − 2 * 50 + 140; 600 + 90 : 3 − 200; 700 − 25 * 2 + 100; 120 − 75 : 3 * 4 + 65; 200 − 80 : 4 * 5 − 35; 108 − 54 : 9 * 6 + 58; 342 : 3; 564 : 2; 721 : 7.", "subpage_snippet": "", "source": "Reshalka.com", "link": "https://Reshalka.com/uchebniki/4-klass/matematika/moro/95", "content": "Часть 1. Страница 18 Номер 2 900 − 2 * 50 + 140; 600 + 90 : 3 − 200; 700 − 25 * 2 + 100; 120 − 75 : 3 * 4 + 65; 200 − 80 : 4 * 5 − 35; 108 − 54 : 9 * 6 + 58; 342 : 3; 564 : 2; 721 : 7."}
+{"idx": 4, "title": "Дмитрий Никотин – Telegram", "date": "", "ddg_snippet": "Про политику, простым языком о сложном. Контрпропаганда и интерпретация новостей.", "subpage_snippet": "", "source": "t.me", "link": "https://t.me/s/dmitrynikotin", "content": "Про политику, простым языком о сложном. Контрпропаганда и интерпретация новостей."}
+{"idx": 5, "title": "ГДЗ по математике 5 класс учебник Виленкин 2 часть – номер 6.365", "date": "", "ddg_snippet": "Найдите корень уравнения: а) 2,442 : (6, 8 - х) = 8 ,14; б) 3,6 ∙ (1,3 + у) = 7,56; в) 0,3n + 1,6n - 0,31 = 0,45; г) 8 ,3m - 4m - 1, 8 m + 4,25 = 8 . Ответ", "subpage_snippet": "", "source": "gdz-raketa.ru", "link": "https://gdz-raketa.ru/matematika/5-klass/uchebnik-vilenkin/2-chast-nomer-6-365/", "content": "Найдите корень уравнения: а) 2,442 : (6, 8 - х) = 8 ,14; б) 3,6 ∙ (1,3 + у) = 7,56; в) 0,3n + 1,6n - 0,31 = 0,45; г) 8 ,3m - 4m - 1, 8 m + 4,25 = 8 . Ответ"}
+{"idx": 6, "title": "Составь программу действий и вычисли: a) 4045 : 5 + 451 * 75 ...", "date": "", "ddg_snippet": "Выполним вычитание в скобках: 729 - 642 = 87. Выполним деление: 4045 : 5 = 809. Выполним умножение: 451 * 75 = 33825.", "subpage_snippet": "", "source": "www.euroki.org", "link": "https://www.euroki.org/koza/sostav-programmu-deystviy-i-vychisli-a------------b", "content": "Выполним вычитание в скобках: 729 - 642 = 87. Выполним деление: 4045 : 5 = 809. Выполним умножение: 451 * 75 = 33825."}
+{"idx": 7, "title": "Как решить: Ореховая смесь из фундука и миндаля имеет массу...", "date": "", "ddg_snippet": "После съедения 25% миндаля осталось: 0. 75 (692−x). Составим уравнение по условиюОстаток миндаля: 0. 75 ⋅652=489 г. Разница: 489−14=475 г. автор вопроса выбрал этот ответ лучшим.", "subpage_snippet": "", "source": "www.bolshoyvopros.ru", "link": "https://www.bolshoyvopros.ru/questions/4608232-kak-reshit-orehovaja-smes-iz-funduka-i-mindalja-imeet-massu-692-g.html", "content": "После съедения 25% миндаля осталось: 0. 75 (692−x). Составим уравнение по условиюОстаток миндаля: 0. 75 ⋅652=489 г. Разница: 489−14=475 г. автор вопроса выбрал этот ответ лучшим."}
+{"idx": 8, "title": "Выбираем смартфон до 15000 рублей | сравнение...", "date": "", "ddg_snippet": "ООО \"Алибаба.ком (ру)\" ИНН 7703380158. Сегодня мы сравним новый POCO M7 Pro 5G и защищенный бюджетник Realme C 75 . POCO мощнее и получил лучшие возможности камер, зато Realme имеет сертификат IP69 и готов выдерживать любые невзгоды.", "subpage_snippet": "", "source": "vk.com", "link": "https://vk.com/video-94973034_456239955", "content": "ООО \"Алибаба.ком (ру)\" ИНН 7703380158. Сегодня мы сравним новый POCO M7 Pro 5G и защищенный бюджетник Realme C 75 . POCO мощнее и получил лучшие возможности камер, зато Realme имеет сертификат IP69 и готов выдерживать любые невзгоды."}
+{"idx": 9, "title": "Почему так дешево? Экстремальная распаковка и обзор игрового...", "date": "", "ddg_snippet": "Экстремальная распаковка и обзор игрового монитора Thunderobot F23H 75 » на канале «Обзоры и тесты игровых устройств» в хорошем качестве и бесплатно, опубликованное 29 декабря 2023 года в 17:18, длительностью 00:12:46, на видеохостинге RUTUBE.", "subpage_snippet": "", "source": "rutube.ru", "link": "https://rutube.ru/video/8ffc944c4385ae5343cda60132a8a2e4/", "content": "Экстремальная распаковка и обзор игрового монитора Thunderobot F23H 75 » на канале «Обзоры и тесты игровых устройств» в хорошем качестве и бесплатно, опубликованное 29 декабря 2023 года в 17:18, длительностью 00:12:46, на видеохостинге RUTUBE."}

data/sampled_jsons/Foret_et_al._2021_Sharpness-Aware_Minimization_SAM_abstract.jsonl

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+{"idx": 0, "title": "QUERY function - Google Docs Editors Help", "date": "", "ddg_snippet": "QUERY function Runs a Google Visualization API Query Language query across data. Sample Usage QUERY(A2:E6,\"select avg(A) pivot B\") QUERY(A2:E6,F2,FALSE) Syntax QUERY(data, query, [headers]) data - The range of cells to perform the query on. Each column of data can only hold boolean, numeric (including date/time types) or string values.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/docs/answer/3093343?hl=en", "content": "QUERY function Runs a Google Visualization API Query Language query across data. Sample Usage QUERY(A2:E6,\"select avg(A) pivot B\") QUERY(A2:E6,F2,FALSE) Syntax QUERY(data, query, [headers]) data - The range of cells to perform the query on. Each column of data can only hold boolean, numeric (including date/time types) or string values."}
+{"idx": 1, "title": "QUERY function - Google Docs Editors Help", "date": "", "ddg_snippet": "QUERY function Runs a Google Visualisation API Query Language query across data. Sample usage QUERY(A2:E6,'select avg(A) pivot B') QUERY(A2:E6,F2,FALSE) Syntax QUERY(data, query, [headers]) data – The range of cells to perform the query on. Each column of data can only hold boolean, numeric (including date/time types) or string values.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/docs/answer/3093343?hl=en-GB", "content": "QUERY function Runs a Google Visualisation API Query Language query across data. Sample usage QUERY(A2:E6,'select avg(A) pivot B') QUERY(A2:E6,F2,FALSE) Syntax QUERY(data, query, [headers]) data – The range of cells to perform the query on. Each column of data can only hold boolean, numeric (including date/time types) or string values."}
+{"idx": 2, "title": "[video] [GOOGLE SHEETS] FUNCIÓN QUERY: FUNCIONES DE AGREGACIÓN:...", "date": "", "ddg_snippet": "Ver en [GOOGLE SHEETS] FUNCIÓN QUERY: FUNCIONES DE AGREGACIÓN: SUM, AVG, COUNT, MIN y MAX 35 mil visualizaciones 6 votos a favor", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/docs/community-video/231737600/google-sheets-funciÓn-query-funciones-de-agregaciÓn-sum-avg-count-min-y-max?hl=es", "content": "Ver en [GOOGLE SHEETS] FUNCIÓN QUERY: FUNCIONES DE AGREGACIÓN: SUM, AVG, COUNT, MIN y MAX 35 mil visualizaciones 6 votos a favor"}
+{"idx": 3, "title": "Refine searches in Gmail - Computer - Gmail Help - Google Help", "date": "", "ddg_snippet": "Use a search operator On your computer, go to Gmail. At the top, click the search box. Enter a search operator. Tips: After you search, you can use the results to set up a filter for these messages. When using numbers as part of your query, a space or a dash (-) will separate a number while a dot (.) will be a decimal. For example, 01.2047-100 is considered 2 numbers: 01.2047 and 100.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/mail/answer/7190?hl=en&co=GENIE.Platform=Desktop", "content": "Use a search operator On your computer, go to Gmail. At the top, click the search box. Enter a search operator. Tips: After you search, you can use the results to set up a filter for these messages. When using numbers as part of your query, a space or a dash (-) will separate a number while a dot (.) will be a decimal. For example, 01.2047-100 is considered 2 numbers: 01.2047 and 100."}
+{"idx": 4, "title": "Google payments center help", "date": "", "ddg_snippet": "Official Google payments center Help Center where you can find tips and tutorials on using Google payments center and other answers to frequently asked questions.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/paymentscenter/?hl=en", "content": "Official Google payments center Help Center where you can find tips and tutorials on using Google payments center and other answers to frequently asked questions."}
+{"idx": 5, "title": "QUERY - Google 文件編輯器說明", "date": "", "ddg_snippet": "QUERY(A2:E6,F2,FALSE) 語法 QUERY(資料, 查詢, [標題]) 資料 - 查詢作業針對的儲存格範圍。 Each column of data can only hold boolean, numeric (including date/time types) or string values. In case of mixed data types in a single column, the majority data type determines the data type of the column for query purposes.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/docs/answer/3093343?hl=zh-Hant", "content": "QUERY(A2:E6,F2,FALSE) 語法 QUERY(資料, 查詢, [標題]) 資料 - 查詢作業針對的儲存格範圍。 Each column of data can only hold boolean, numeric (including date/time types) or string values. In case of mixed data types in a single column, the majority data type determines the data type of the column for query purposes."}
+{"idx": 6, "title": "Set default search engine and site search shortcuts", "date": "", "ddg_snippet": "Enter the web address for the search engine's results page, and use %s where the query would go. To find and edit the web address of the results page: Copy and paste the web address of the search results page into the URL field. The address for the search results page is different from the website address.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/chrome/answer/95426?hl=en&co=GENIE.Platform=Desktop", "content": "Enter the web address for the search engine's results page, and use %s where the query would go. To find and edit the web address of the results page: Copy and paste the web address of the search results page into the URL field. The address for the search results page is different from the website address."}
+{"idx": 7, "title": "BigQuery - Google Cloud Platform Console Help", "date": "", "ddg_snippet": "Use a variety of third-party tools to access data on BigQuery, such as tools that load or visualize your data. Use datasets to organize and control access to tables, and construct jobs for BigQuery to execute (load, export, query, or copy data). Find BigQuery in the left side menu of the Google Cloud Platform Console, under Big Data.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/cloud/answer/6255052?hl=en", "content": "Use a variety of third-party tools to access data on BigQuery, such as tools that load or visualize your data. Use datasets to organize and control access to tables, and construct jobs for BigQuery to execute (load, export, query, or copy data). Find BigQuery in the left side menu of the Google Cloud Platform Console, under Big Data."}
+{"idx": 8, "title": "Url with %s in place of query - Google Chrome Community", "date": "", "ddg_snippet": "Url with %s in place of query What is google chrome's query link? I know this sounds stupid but is there a search engine called Google chrome instead of google, I told my friend about my search engine situation and he said that Google search engine is the problem and that I should get Google chrome, but I already have google chrome.", "subpage_snippet": "", "source": "support.google.com", "link": "https://support.google.com/chrome/thread/171175871/url-with-s-in-place-of-query?hl=en", "content": "Url with %s in place of query What is google chrome's query link? I know this sounds stupid but is there a search engine called Google chrome instead of google, I told my friend about my search engine situation and he said that Google search engine is the problem and that I should get Google chrome, but I already have google chrome."}
+{"idx": 9, "title": "Query on/in/about/regarding... | WordReference Forums", "date": "", "ddg_snippet": "Jan 21, 2017 · Good afternoon all, I was wondering if I could use the following prepositions or prepositional phrases with \"query\" I have a question in this matter I have a question on this matter I have a question about this matter I have a question regarding / with regard to / concerning / other similar...", "subpage_snippet": "", "source": "forum.wordreference.com", "link": "https://forum.wordreference.com/threads/query-on-in-about-regarding.3278284/", "content": "Jan 21, 2017 · Good afternoon all, I was wondering if I could use the following prepositions or prepositional phrases with \"query\" I have a question in this matter I have a question on this matter I have a question about this matter I have a question regarding / with regard to / concerning / other similar..."}

data/sampled_jsons/GUI-Xplore_Empowering_Generalizable_GUI_Agents_Table_4_rule-based_GPT-based_clustering_year_2024.jsonl

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+{"idx": 0, "title": "Empowering Generalizable GUI Agents with One Exploration", "date": "", "ddg_snippet": "by Y Sun · 2025 · Cited by 9 — Xplore - Agent encodes GUI modeling-generated linear se- quences into a GUI Transition Graph through GUI clus- tering, where clustering accuracy is critical for ... 10 pages", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Sun_GUI-Xplore_Empowering_Generalizable_GUI_Agents_with_One_Exploration_CVPR_2025_paper.pdf", "content": "by Y Sun · 2025 · Cited by 9 — Xplore - Agent encodes GUI modeling-generated linear se- quences into a GUI Transition Graph through GUI clus- tering, where clustering accuracy is critical for ... 10 pages"}
+{"idx": 1, "title": "Empowering Generalizable GUI Agents with One Exploration", "date": "", "ddg_snippet": "22 Mar 2025 — We introduce GUI-Xplore , a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.17709v1", "content": "22 Mar 2025 — We introduce GUI-Xplore , a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework."}
+{"idx": 2, "title": "Graphs Meet AI Agents: Taxonomy, Progress, and Future ...", "date": "", "ddg_snippet": "22 Jun 2025 — This survey presents a first systematic review of how graphs can empower AI agents . Specifically, we explore the integration of graph techniques with core ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.18019v1", "content": "22 Jun 2025 — This survey presents a first systematic review of how graphs can empower AI agents . Specifically, we explore the integration of graph techniques with core ..."}
+{"idx": 3, "title": "GUI-Xplore: Empowering Generalizable GUI Agents with One ... GitHub - 921112343/GUI-Xplore: [CVPR 2025] GUI-Xplore ... CVPR 2025 Open Access Repository GUI-Xplore: Empowering Generalizable GUI Agents with One ... GUI-Xplore: Empowering Generalizable GUI Agents with One ... GUI-Xplore/README.md at main · 921112343/GUI-Xplore · GitHub GitHub - 921112343/ GUI-Xplore : [CVPR 2025] GUI-Xplore : Empowering GUI -Xplore: Empowering Generalizable GUI Agents with One Exploration GUI - Xplore : Empowering Generalizable GUI Agents with One Exploratio… GUI -Xplore: Empowering Generalizable GUI Agents with One Exploration GUI -Xplore: Empowering Generalizable GUI Agents with One Exploration GUI - Xplore : Empowering Generalizable GUI Agents with One Exploratio… GUI-Xplore: Empowering Generalizable GUI Agents with One ...", "date": "", "ddg_snippet": "Mar 22, 2025 · To address these challenges, we introduce GUI - Xplore , a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework. Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation. To address these challenges, we introduce GUI - Xplore , a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework. To address these challenges, we in-troduce GUI - Xplore , a dataset meticulously designed to en-hance cross-application and cross-task generalization via an exploration-and-reasoning framework. Abstract: GUI agents hold significant potential to enhance the experience and efficiency of human-device interaction. However, current methods face challenges in generalizing across applications (apps) and tasks, primarily due to two fundamental limitations in existing datasets. Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation. What is GUI-Xplore dataset? GUI-Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation. [2025-03-18] Initial release of GUI-Xplore dataset and benchmark. What is GUI-Xplore? To address these challenges, we introduce GUI-Xplore, a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework. What are the challenges of GUI-Xplore app exploration? The App Exploration task in the GUI-Xplore dataset presents challenges due to its information density and the multi-layered nature of the downstream tasks . To address these challenges, we introduce a two-stage framework for GUI agents, as shown in Fig 3. What is GUI-Xplore agent? To fully exploit GUI-Xplore's unique features, we propose Xplore-Agent, a GUI agent framework that combines Action-aware GUI Modeling with Graph-Guided Environment Reasoning. What is GUI Xplore? GUI-Xplore integrates pre-recorded exploration videos providing contextual insights, alongside five hierarchically structured downstream tasks designed to comprehensively evaluate GUI agent capabilities. Do task discrepancies affect cross-app generalization? In the Cross-App Generalization experiment, to mitigate the impact of task discrepancies when comparing against exist-ing GUI agent methods, we constructed a Cross-App Au-tomation test set based on the Application Usage task from GUI - Xplore dataset. While GUI - Xplore represents a significant advancement in GUI agents , several limitations deserve consideration. First, the exploration phase still requires substantial computational resources and time, which could limit practical applications in resource-constrained environments.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.17709", "content": "Mar 22, 2025 · To address these challenges, we introduce GUI - Xplore , a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework. Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation. To address these challenges, we introduce GUI - Xplore , a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework. To address these challenges, we in-troduce GUI - Xplore , a dataset meticulously designed to en-hance cross-application and cross-task generalization via an exploration-and-reasoning framework. Abstract: GUI agents hold significant potential to enhance the experience and efficiency of human-device interaction. However, current methods face challenges in generalizing across applications (apps) and tasks, primarily due to two fundamental limitations in existing datasets. Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation. What is GUI-Xplore dataset? GUI-Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation. [2025-03-18] Initial release of GUI-Xplore dataset and benchmark. What is GUI-Xplore? To address these challenges, we introduce GUI-Xplore, a dataset meticulously designed to enhance cross-application and cross-task generalization via an exploration-and-reasoning framework. What are the challenges of GUI-Xplore app exploration? The App Exploration task in the GUI-Xplore dataset presents challenges due to its information density and the multi-layered nature of the downstream tasks . To address these challenges, we introduce a two-stage framework for GUI agents, as shown in Fig 3. What is GUI-Xplore agent? To fully exploit GUI-Xplore's unique features, we propose Xplore-Agent, a GUI agent framework that combines Action-aware GUI Modeling with Graph-Guided Environment Reasoning. What is GUI Xplore? GUI-Xplore integrates pre-recorded exploration videos providing contextual insights, alongside five hierarchically structured downstream tasks designed to comprehensively evaluate GUI agent capabilities. Do task discrepancies affect cross-app generalization? In the Cross-App Generalization experiment, to mitigate the impact of task discrepancies when comparing against exist-ing GUI agent methods, we constructed a Cross-App Au-tomation test set based on the Application Usage task from GUI - Xplore dataset. While GUI - Xplore represents a significant advancement in GUI agents , several limitations deserve consideration. First, the exploration phase still requires substantial computational resources and time, which could limit practical applications in resource-constrained environments."}
+{"idx": 4, "title": "GitHub - 921112343/GUI-Xplore: [CVPR 2025] GUI-Xplore ...", "date": "", "ddg_snippet": "Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/921112343/GUI-Xplore", "content": "Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation."}
+{"idx": 5, "title": "GUI-Xplore: Empowering Generalizable GUI Agents with One ...", "date": "", "ddg_snippet": "To address these challenges, we in-troduce GUI - Xplore , a dataset meticulously designed to en-hance cross-application and cross-task generalization via an exploration-and-reasoning framework.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.17709", "content": "To address these challenges, we in-troduce GUI - Xplore , a dataset meticulously designed to en-hance cross-application and cross-task generalization via an exploration-and-reasoning framework."}
+{"idx": 6, "title": "GUI-Xplore: Empowering Generalizable GUI Agents with One ...", "date": "", "ddg_snippet": "Abstract: GUI agents hold significant potential to enhance the experience and efficiency of human-device interaction. However, current methods face challenges in generalizing across applications (apps) and tasks, primarily due to two fundamental limitations in existing datasets.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2503.17709v1", "content": "Abstract: GUI agents hold significant potential to enhance the experience and efficiency of human-device interaction. However, current methods face challenges in generalizing across applications (apps) and tasks, primarily due to two fundamental limitations in existing datasets."}
+{"idx": 7, "title": "GUI-Xplore/README.md at main · 921112343/GUI-Xplore · GitHub", "date": "", "ddg_snippet": "Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/921112343/GUI-Xplore/blob/main/README.md", "content": "Feb 27, 2025 · GUI - Xplore is a novel dataset designed to enhance cross-application and cross-task generalization for GUI agents . It provides exploration videos for diverse applications, combined with five structured downstream tasks, aiming to push the boundaries of generalizable GUI automation."}
+{"idx": 8, "title": "GUI-Xplore: Empowering Generalizable GUI Agents with One ...", "date": "", "ddg_snippet": "While GUI - Xplore represents a significant advancement in GUI agents , several limitations deserve consideration. First, the exploration phase still requires substantial computational resources and time, which could limit practical applications in resource-constrained environments.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/gui-xplore-empowering-generalizable-gui-agents-one", "content": "While GUI - Xplore represents a significant advancement in GUI agents , several limitations deserve consideration. First, the exploration phase still requires substantial computational resources and time, which could limit practical applications in resource-constrained environments."}
+{"idx": 9, "title": "Transformation of industrial robotics with natural language ...", "date": "", "ddg_snippet": "by Z Yu · 2026 — Rule - based interactive natural language processing, combined with 3D visual perception for environmental mapping and rule-scene matching to translate human ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S073658452500167X", "content": "by Z Yu · 2026 — Rule - based interactive natural language processing, combined with 3D visual perception for environmental mapping and rule-scene matching to translate human ..."}

data/sampled_jsons/Grassmannian_cluster_algebra_148658_S18_characters_100000_training_examples.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Grassmannian - Wikipedia", "date": "", "ddg_snippet": "In mathematics, the Grassmannian (named in honour of Hermann Grassmann) is a differentiable manifold that parameterizes the set of all - dimensional linear subspaces of an -dimensional vector space over a field that has a differentiable structure.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Grassmannian", "content": "In mathematics, the Grassmannian (named in honour of Hermann Grassmann) is a differentiable manifold that parameterizes the set of all - dimensional linear subspaces of an -dimensional vector space over a field that has a differentiable structure."}
+{"idx": 1, "title": "[math/0311148] Grassmannians and Cluster Algebras - arXiv.org", "date": "", "ddg_snippet": "Nov 10, 2003 · This paper demonstrates that the homogeneous coordinate ring of the Grassmannian G(k, n) is a {\\it cluster algebra of geometric type} - as defined by S. Fomin and A. Zelevinsky. Grassmannians having {\\it finite cluster type} are classified and the associated cluster variables are studied in connection with the geometry of configurations of points in RP2.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/math/0311148", "content": "Nov 10, 2003 · This paper demonstrates that the homogeneous coordinate ring of the Grassmannian G(k, n) is a {\\it cluster algebra of geometric type} - as defined by S. Fomin and A. Zelevinsky. Grassmannians having {\\it finite cluster type} are classified and the associated cluster variables are studied in connection with the geometry of configurations of points in RP2."}
+{"idx": 2, "title": "Lecture Notes Introduction to Cluster Algebra", "date": "", "ddg_snippet": "The cluster algebra structure of the Grassmannian leads to the notion of \\Positive Grassmannian \", where each cluster gives a \\total positivity cri-terion\" on the positive variety of Gr(k; n), generalizing the results for total positivity of matrices.", "subpage_snippet": "", "source": "www.math.hkust.edu.hk", "link": "https://www.math.hkust.edu.hk/~ivanip/teaching/cluster/Lecture11-Grassmannian.pdf", "content": "The cluster algebra structure of the Grassmannian leads to the notion of \\Positive Grassmannian \", where each cluster gives a \\total positivity cri-terion\" on the positive variety of Gr(k; n), generalizing the results for total positivity of matrices."}
+{"idx": 3, "title": "Grassmannians and Cluster Structures - PMC Grassmannian categories of infinite rank - joint with Jenny ... Grassmannian - Wikipedia Clustering cluster algebras with clusters - LIMS Lecture Notes Introduction to Cluster Algebra Grassmannian - Wikipedia Lecture Notes Introduction to Cluster Algebra Grassmannian - Wikipedia Grassmannian - Wikipedia Grassmannian - Wikipedia GRASSMANNIANS AND CLUSTER ALGEBRAS - University of Bath", "date": "", "ddg_snippet": "Apr 22, 2021 · In the finite types, both the cluster algebra and the cluster category are determined. However, in general, the categories F k, n are of infinite type and so far not well understood. In these lectures, we recall the cluster algebras and cluster categories of the Grassmannian and some of the key ingredients for studying them. Grassmannian cluster algebras of Theorem (Scott 2006) nite rank Maximal sets of compatible Plucker coordinates are ( examples of) clusters. In mathematics, the Grassmannian (named in honour of Hermann Grassmann) is a differentiable manifold that parameterizes the set of all - dimensional linear subspaces of an -dimensional vector space over a field that has a differentiable structure. For example , in mathematics, cluster variables in Grassmannian clus-ter algebras C[Gr(k, n)] correspond to real prime modules of the quantum affine algebra modules in Grassmannian cluster categories [9]. Is Grassmannian a cluster algebra? In this lecture, we will look at the general Grassmannian Gr(k; n), and show that it also prosesses a cluster algebra structure of geometric type . We will follow [Scott]. Remark 10.1. Is Grassmannian an algebraic group? More generally, over a ground field , the group is an algebraic group , and this construction shows that the Grassmannian is a non-singular algebraic variety. It follows from the existence of the Plücker embedding that the Grassmannian is complete as an algebraic variety. In particular, is a parabolic subgroup of . What is a positive Grassmannian? We will follow [Scott]. Remark 10.1. The cluster algebra structure of the Grassmannian leads to the notion of \\Positive Grassmannian\", where each cluster gives a otal positivity cri-terion \" on the positive variety of Gr(k; n), generalizing the results for total positivity of matrices. What is an example of a Grassmannian? For example, the Grassmannian is the space of lines through the origin in , so it is the same as the projective space of one dimension lower than . When is a real or complex vector space, Grassmannians are compact smooth manifolds, of dimension . In general they have the structure of a nonsingular projective algebraic variety. What is integral cohomology of Grassmannians? The integral cohomology of the Grassmannians is generated, as a ring , by the Chern classes of . In particular, all of the integral cohomology is at even degree as in the case of a projective space. These generators are subject to a set of relations, which defines the ring. What is the Plücker embedding of the Grassmannian? The Plücker embedding of the Grassmannian satisfies a set of simple quadratic relations called the Plücker relations . These show that the Grassmannian embeds as a nonsingular projective algebraic subvariety of the projectivization of the th exterior power of and give another method for constructing the Grassmannian. A cluster algebra is of finite type if it possess only finitely many cluster variables. We have already seen an example , namely the homogeneous coordinate ring of the Grassmannian (2, n).", "subpage_snippet": "", "source": "www.ncbi.nlm.nih.gov", "link": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8641944/", "content": "Apr 22, 2021 · In the finite types, both the cluster algebra and the cluster category are determined. However, in general, the categories F k, n are of infinite type and so far not well understood. In these lectures, we recall the cluster algebras and cluster categories of the Grassmannian and some of the key ingredients for studying them. Grassmannian cluster algebras of Theorem (Scott 2006) nite rank Maximal sets of compatible Plucker coordinates are ( examples of) clusters. In mathematics, the Grassmannian (named in honour of Hermann Grassmann) is a differentiable manifold that parameterizes the set of all - dimensional linear subspaces of an -dimensional vector space over a field that has a differentiable structure. For example , in mathematics, cluster variables in Grassmannian clus-ter algebras C[Gr(k, n)] correspond to real prime modules of the quantum affine algebra modules in Grassmannian cluster categories [9]. Is Grassmannian a cluster algebra? In this lecture, we will look at the general Grassmannian Gr(k; n), and show that it also prosesses a cluster algebra structure of geometric type . We will follow [Scott]. Remark 10.1. Is Grassmannian an algebraic group? More generally, over a ground field , the group is an algebraic group , and this construction shows that the Grassmannian is a non-singular algebraic variety. It follows from the existence of the Plücker embedding that the Grassmannian is complete as an algebraic variety. In particular, is a parabolic subgroup of . What is a positive Grassmannian? We will follow [Scott]. Remark 10.1. The cluster algebra structure of the Grassmannian leads to the notion of \\Positive Grassmannian\", where each cluster gives a otal positivity cri-terion \" on the positive variety of Gr(k; n), generalizing the results for total positivity of matrices. What is an example of a Grassmannian? For example, the Grassmannian is the space of lines through the origin in , so it is the same as the projective space of one dimension lower than . When is a real or complex vector space, Grassmannians are compact smooth manifolds, of dimension . In general they have the structure of a nonsingular projective algebraic variety. What is integral cohomology of Grassmannians? The integral cohomology of the Grassmannians is generated, as a ring , by the Chern classes of . In particular, all of the integral cohomology is at even degree as in the case of a projective space. These generators are subject to a set of relations, which defines the ring. What is the Plücker embedding of the Grassmannian? The Plücker embedding of the Grassmannian satisfies a set of simple quadratic relations called the Plücker relations . These show that the Grassmannian embeds as a nonsingular projective algebraic subvariety of the projectivization of the th exterior power of and give another method for constructing the Grassmannian. A cluster algebra is of finite type if it possess only finitely many cluster variables. We have already seen an example , namely the homogeneous coordinate ring of the Grassmannian (2, n)."}
+{"idx": 4, "title": "Grassmannian categories of infinite rank - joint with Jenny ...", "date": "", "ddg_snippet": "Grassmannian cluster algebras of Theorem (Scott 2006) nite rank Maximal sets of compatible Plucker coordinates are ( examples of) clusters.", "subpage_snippet": "", "source": "dept.math.lsa.umich.edu", "link": "https://dept.math.lsa.umich.edu/~speyer/DimerConference2020/slides/Schroll.pdf", "content": "Grassmannian cluster algebras of Theorem (Scott 2006) nite rank Maximal sets of compatible Plucker coordinates are ( examples of) clusters."}
+{"idx": 5, "title": "Clustering cluster algebras with clusters - LIMS", "date": "", "ddg_snippet": "For example , in mathematics, cluster variables in Grassmannian clus-ter algebras C[Gr(k, n)] correspond to real prime modules of the quantum affine algebra modules in Grassmannian cluster categories [9].", "subpage_snippet": "", "source": "lims.ac.uk", "link": "https://lims.ac.uk/documents/undefined-6.pdf", "content": "For example , in mathematics, cluster variables in Grassmannian clus-ter algebras C[Gr(k, n)] correspond to real prime modules of the quantum affine algebra modules in Grassmannian cluster categories [9]."}
+{"idx": 6, "title": "GRASSMANNIANS AND CLUSTER ALGEBRAS - University of Bath", "date": "", "ddg_snippet": "A cluster algebra is of finite type if it possess only finitely many cluster variables. We have already seen an example , namely the homogeneous coordinate ring of the Grassmannian (2, n).", "subpage_snippet": "", "source": "people.bath.ac.uk", "link": "https://people.bath.ac.uk/masadk/zzz/scott06.pdf", "content": "A cluster algebra is of finite type if it possess only finitely many cluster variables. We have already seen an example , namely the homogeneous coordinate ring of the Grassmannian (2, n)."}
+{"idx": 7, "title": "[1309.7301] A categorification of Grassmannian cluster algebras", "date": "", "ddg_snippet": "View a PDF of the paper titled A categorification of Grassmannian cluster algebras , by Bernt Tore Jensen and 1 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1309.7301", "content": "View a PDF of the paper titled A categorification of Grassmannian cluster algebras , by Bernt Tore Jensen and 1 other authors."}
+{"idx": 8, "title": "A categorification of Grassmannian cluster algebras - the University...", "date": "", "ddg_snippet": "More precisely, there is a cluster character dened on the category which maps the rigid indecomposable objects to the cluster variables and the maximal rigid objects to clusters .Dive into the research topics of 'A categorification of Grassmannian cluster algebras '.", "subpage_snippet": "", "source": "researchportal.bath.ac.uk", "link": "https://researchportal.bath.ac.uk/en/publications/a-categorification-of-grassmannian-cluster-algebras", "content": "More precisely, there is a cluster character dened on the category which maps the rigid indecomposable objects to the cluster variables and the maximal rigid objects to clusters .Dive into the research topics of 'A categorification of Grassmannian cluster algebras '."}
+{"idx": 9, "title": "A categorification of Grassmannian cluster algebras | Request PDF", "date": "", "ddg_snippet": "[18,Section 5]. In fact, the Grassmannian cluster category MCM μ n R (k,n) is stably equivalent to the category SubQ k studied by Geiß et al.The Jacobian algebra of this dual graph gives a categorification of the Grassmannian G(2, 10) in the example , see [JKS16].", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/305315125_A_categorification_of_Grassmannian_cluster_algebras", "content": "[18,Section 5]. In fact, the Grassmannian cluster category MCM μ n R (k,n) is stably equivalent to the category SubQ k studied by Geiß et al.The Jacobian algebra of this dual graph gives a categorification of the Grassmannian G(2, 10) in the example , see [JKS16]."}

data/sampled_jsons/Gumiho_speculative_decoding_Figure_4_serial_head_depth_accepted_tokens_speedup_year_2024.jsonl

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+{"idx": 0, "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. The target LLM verifies the predicted sequence and accepts aligned tokens , enabling efficient multi- token generation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.10135", "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. The target LLM verifies the predicted sequence and accepts aligned tokens , enabling efficient multi- token generation ..."}
+{"idx": 1, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "Unlike existing methods that treat all tokens within a generated sequence as equally important, Gumiho is based on the theoretical finding that initial tokens in the draft sequence have a more significant impact on the overall accepted length. Gumiho employs a hybrid head design that combines serial and parallel components.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/AMD-AGI/Gumiho", "content": "Unlike existing methods that treat all tokens within a generated sequence as equally important, Gumiho is based on the theoretical finding that initial tokens in the draft sequence have a more significant impact on the overall accepted length. Gumiho employs a hybrid head design that combines serial and parallel components."}
+{"idx": 2, "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": 3, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in...", "date": "", "ddg_snippet": "This paper proposes Gumiho , a hybrid architecture for speculative decoding in Large Language Models. The core idea is motivated by the insight that early tokens in a draft sequence are more critical for the overall acceptance rate than later ones. Gumiho operationalizes this by using a more accurate, serial Transformer-based head for early tokens and faster parallel MLP-based heads for later ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0ObGn4e1IS", "content": "This paper proposes Gumiho , a hybrid architecture for speculative decoding in Large Language Models. The core idea is motivated by the insight that early tokens in a draft sequence are more critical for the overall acceptance rate than later ones. Gumiho operationalizes this by using a more accurate, serial Transformer-based head for early tokens and faster parallel MLP-based heads for later ..."}
+{"idx": 4, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "To address this, Gumiho proposes an innovative hybrid model that integrates both serial and parallel heads . 🔍 Key Features: - Early Tokens : Utilizes an advanced Transformer architecture in a ...", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/abdullah-kasri_gumiho-a-hybrid-architecture-to-prioritize-activity-7306519551876161536-HoDU", "content": "To address this, Gumiho proposes an innovative hybrid model that integrates both serial and parallel heads . 🔍 Key Features: - Early Tokens : Utilizes an advanced Transformer architecture in a ..."}
+{"idx": 5, "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": 6, "title": "Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch ...", "date": "", "ddg_snippet": "Recently, speculative decoding (SD) has emerged as a promising technique to ac- celerate LLM inference by employing a small draft model to propose draft tokens in advance, and validating them in parallel with the large target model. However, the existing SD methods still remain fundamentally constrained by their serialized execution, which causes the mutual waiting bubbles between the draft ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2506.01979", "content": "Recently, speculative decoding (SD) has emerged as a promising technique to ac- celerate LLM inference by employing a small draft model to propose draft tokens in advance, and validating them in parallel with the large target model. However, the existing SD methods still remain fundamentally constrained by their serialized execution, which causes the mutual waiting bubbles between the draft ..."}
+{"idx": 7, "title": "Geralt-Targaryen/Awesome-Speculative-Decoding - GitHub", "date": "", "ddg_snippet": "\" Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding \" [2025-03] [paper] EAGLE for the first two draft tokens , Medusa for the next 5.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Geralt-Targaryen/Awesome-Speculative-Decoding", "content": "\" Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding \" [2025-03] [paper] EAGLE for the first two draft tokens , Medusa for the next 5."}
+{"idx": 8, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative ...", "date": "", "ddg_snippet": "View recent discussion. 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 multiple 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 ...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2503.10135v2", "content": "View recent discussion. 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 multiple 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 ..."}
+{"idx": 9, "title": "Accelerating LLMs with Smarter Token Prioritization", "date": "", "ddg_snippet": "Combines serial and parallel processing for optimal token generation Prioritizes early tokens that have higher likelihood of being correct Achieves up to 1.6x speedup over baseline speculative decoding methods Offers flexible deployment options with minimal overhead", "subpage_snippet": "", "source": "www.zerna.io", "link": "https://www.zerna.io/page/engineering/presentation_set/engineering-llm-research/presentation/engineering-model-optimization/slide/engineering-paper-2503_10135", "content": "Combines serial and parallel processing for optimal token generation Prioritizes early tokens that have higher likelihood of being correct Achieves up to 1.6x speedup over baseline speculative decoding methods Offers flexible deployment options with minimal overhead"}

data/sampled_jsons/Gumiho_speculative_decoding_Table_3_wall_time_tradeoff_openreview_year_2024.jsonl

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+{"idx": 0, "title": "Gumiho: A Hybrid Architecture to Prioritize ... - OpenReview", "date": "", "ddg_snippet": "May 1, 2025 · This paper proposes a new speculative decoding method called Gumiho . It combines the parallel draft head architecture and sequential draft head architecture to derive a hybrid architecture.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0ObGn4e1IS", "content": "May 1, 2025 · This paper proposes a new speculative decoding method called Gumiho . It combines the parallel draft head architecture and sequential draft head architecture to derive a hybrid architecture."}
+{"idx": 1, "title": "[2503.10135] Gumiho: A Hybrid Architecture to Prioritize ... GitHub - AMD-AGI/Gumiho: Official Implementation of \"Gumiho ... (PDF) Gumiho: A Hybrid Architecture to Prioritize Early ... Gumiho: A Hybrid Architecture to Prioritize Early Tokens in ... Gumiho: A Hybrid Architecture to Prioritize Early Tokens in ... Gumiho: A Hybrid Architecture to Prioritize Early Tokens in ...", "date": "", "ddg_snippet": "Mar 13, 2025 · 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. The target LLM verifies the predicted sequence and accepts aligned tokens, enabling efficient multi-token generation ... Jul 11, 2025 · 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 ... Mar 13, 2025 · PDF | Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). In the following, we define yt+1 = ML(yt) ≜ ML(yt, kv<t) and ignore kv<t for simplicity. Speculative Decoding Auto-regressive text generation in LLMs is time -consuming. Speculative decoding addresses this limitation by employing a smaller, faster draft model MS to generate candidate tokens ahead of time . Abstract Gumiho , a hybrid model combining serial and parallel heads with varying architectures, improves speculative decoding for large language models by prioritizing accuracy for early tokens. Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding Jinze Li · Yixing Xu · Haiduo Huang · Xuanwu Yin · Dong Li · Edith Ngai · Emad Barsoum", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.10135", "content": "Mar 13, 2025 · 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. The target LLM verifies the predicted sequence and accepts aligned tokens, enabling efficient multi-token generation ... Jul 11, 2025 · 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 ... Mar 13, 2025 · PDF | Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). In the following, we define yt+1 = ML(yt) ≜ ML(yt, kv<t) and ignore kv<t for simplicity. Speculative Decoding Auto-regressive text generation in LLMs is time -consuming. Speculative decoding addresses this limitation by employing a smaller, faster draft model MS to generate candidate tokens ahead of time . Abstract Gumiho , a hybrid model combining serial and parallel heads with varying architectures, improves speculative decoding for large language models by prioritizing accuracy for early tokens. Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding Jinze Li · Yixing Xu · Haiduo Huang · Xuanwu Yin · Dong Li · Edith Ngai · Emad Barsoum"}
+{"idx": 2, "title": "GitHub - AMD-AGI/Gumiho: Official Implementation of \"Gumiho ...", "date": "", "ddg_snippet": "Jul 11, 2025 · 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": "Jul 11, 2025 · 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": 3, "title": "(PDF) Gumiho: A Hybrid Architecture to Prioritize Early ...", "date": "", "ddg_snippet": "Mar 13, 2025 · PDF | Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM).", "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": "Mar 13, 2025 · PDF | Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM)."}
+{"idx": 4, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in ...", "date": "", "ddg_snippet": "In the following, we define yt+1 = ML(yt) ≜ ML(yt, kv<t) and ignore kv<t for simplicity. Speculative Decoding Auto-regressive text generation in LLMs is time -consuming. Speculative decoding addresses this limitation by employing a smaller, faster draft model MS to generate candidate tokens ahead of time .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=0ObGn4e1IS", "content": "In the following, we define yt+1 = ML(yt) ≜ ML(yt, kv<t) and ignore kv<t for simplicity. Speculative Decoding Auto-regressive text generation in LLMs is time -consuming. Speculative decoding addresses this limitation by employing a smaller, faster draft model MS to generate candidate tokens ahead of time ."}
+{"idx": 5, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in ...", "date": "", "ddg_snippet": "Abstract Gumiho , a hybrid model combining serial and parallel heads with varying architectures, improves speculative decoding for large language models by prioritizing accuracy for early tokens.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2503.10135", "content": "Abstract Gumiho , a hybrid model combining serial and parallel heads with varying architectures, improves speculative decoding for large language models by prioritizing accuracy for early tokens."}
+{"idx": 6, "title": "Gumiho: A Hybrid Architecture to Prioritize Early Tokens in ...", "date": "", "ddg_snippet": "Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding Jinze Li · Yixing Xu · Haiduo Huang · Xuanwu Yin · Dong Li · Edith Ngai · Emad Barsoum", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46686", "content": "Gumiho : A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding Jinze Li · Yixing Xu · Haiduo Huang · Xuanwu Yin · Dong Li · Edith Ngai · Emad Barsoum"}
+{"idx": 7, "title": "Policy-driven collaborative decoding for latency tradeoff | OpenReview", "date": "", "ddg_snippet": "Speculative decoding has shown promising improvements in decode times .In this paper, we propose to extend speculative decoding by learning a dynamic decoding policy that considers the trade - off between smaller and more complex models for generation and verification.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=_G6L10mWQkP", "content": "Speculative decoding has shown promising improvements in decode times .In this paper, we propose to extend speculative decoding by learning a dynamic decoding policy that considers the trade - off between smaller and more complex models for generation and verification."}
+{"idx": 8, "title": "Reducing AI Inference Latency With Speculative Decoding", "date": "", "ddg_snippet": "Explore how speculative decoding techniques, including EAGLE- 3 , reduce latency and enhance efficiency in AI inference, optimizing large language model performance on NVIDIA GPUs.", "subpage_snippet": "", "source": "digiitallife.com", "link": "https://digiitallife.com/reducing-ai-inference-latency-with-speculative-decoding/", "content": "Explore how speculative decoding techniques, including EAGLE- 3 , reduce latency and enhance efficiency in AI inference, optimizing large language model performance on NVIDIA GPUs."}
+{"idx": 9, "title": "timewall.io", "date": "", "ddg_snippet": "لموقع time wall .", "subpage_snippet": "", "source": "timewall.io", "link": "https://timewall.io/", "content": "لموقع time wall ."}

data/sampled_jsons/HDT_history-driven_target_empirical_measure_LRU_cache_implementation_memory_reduction.jsonl

@@ -0,0 +1,8 @@
+{"idx": 0, "title": "Beyond Self-Repellent Kernels: History - Driven Target Towards...", "date": "", "ddg_snippet": "Scalable Implementation for Large Graphs: We implement an LRU ( Least Recently Used ) cache scheme to manage. 𝐱{\\mathbf{x}}bold_x. with limited memory .In this paper, we propose a history - driven target ( HDT ) framework for MCMC sampling on general graphs.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.18300v3", "content": "Scalable Implementation for Large Graphs: We implement an LRU ( Least Recently Used ) cache scheme to manage. 𝐱{\\mathbf{x}}bold_x. with limited memory .In this paper, we propose a history - driven target ( HDT ) framework for MCMC sampling on general graphs."}
+{"idx": 1, "title": "Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient ...", "date": "", "ddg_snippet": "To handle memory limitations, we introduce a Least Recently Used ( LRU ) cache scheme, enabling partial tracking of the empirical measure without loss in sampling efficiency.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.18300v1", "content": "To handle memory limitations, we introduce a Least Recently Used ( LRU ) cache scheme, enabling partial tracking of the empirical measure without loss in sampling efficiency."}
+{"idx": 2, "title": "Beyond Self-Repellent Kernels: History-Driven Target ... - 道客巴巴", "date": "", "ddg_snippet": "To overcome theselimitations, instead of direct modif ication of tran-sition kernel, HDT introduces a history-dependenttarget distribution π [x] to replace the original tar-get µ in any graph sampler, where x representsthe empirical measure of past visits.", "subpage_snippet": "", "source": "www.doc88.com", "link": "https://www.doc88.com/p-28437834991562.html", "content": "To overcome theselimitations, instead of direct modif ication of tran-sition kernel, HDT introduces a history-dependenttarget distribution π [x] to replace the original tar-get µ in any graph sampler, where x representsthe empirical measure of past visits."}
+{"idx": 3, "title": "論文の概要: Beyond Self-Repellent Kernels: History-Driven Target Towards ...", "date": "", "ddg_snippet": "To overcome these limitations, instead of direct modification of transition kernel, HDT introduces a history-dependent target distribution $\\boldsymbol {\\pi} [\\mathbf {x}]$ to replace the original target $\\boldsymbol {\\mu}$ in any graph sampler, where $\\mathbf {x}$ represents the empirical measure of past visits.", "subpage_snippet": "", "source": "fugumt.com", "link": "https://fugumt.com/fugumt/paper_check/2505.18300v1", "content": "To overcome these limitations, instead of direct modification of transition kernel, HDT introduces a history-dependent target distribution $\\boldsymbol {\\pi} [\\mathbf {x}]$ to replace the original target $\\boldsymbol {\\mu}$ in any graph sampler, where $\\mathbf {x}$ represents the empirical measure of past visits."}
+{"idx": 4, "title": "Beyond Self-Repellent Kernels: History-Driven Target ...", "date": "", "ddg_snippet": "by J Hu — We propose a * history-driven target ( HDT )* framework in Markov Chain ... empirical measure of past visits. This design preserves ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0yzOEMbShU", "content": "by J Hu — We propose a * history-driven target ( HDT )* framework in Markov Chain ... empirical measure of past visits. This design preserves ..."}
+{"idx": 5, "title": "History-Driven Target Towards Efficient Nonlinear MCMC ...", "date": "", "ddg_snippet": "This findings open a possibility that we may only requires an approximated empirical measure to implement HDT -MCMC while remaining fast convergence.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46659", "content": "This findings open a possibility that we may only requires an approximated empirical measure to implement HDT -MCMC while remaining fast convergence."}
+{"idx": 6, "title": "Track: Poster Session 5 East", "date": "", "ddg_snippet": "17 Jul 2025 — We propose a * history-driven target ( HDT )* framework in Markov Chain ... empirical measure of past visits. This design preserves ...", "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 Markov Chain ... empirical measure of past visits. This design preserves ..."}
+{"idx": 7, "title": "Jie Hu", "date": "", "ddg_snippet": "Abstract:We propose a history-driven target ( HDT ) framework in Markov Chain ... empirical measure of past visits. This design preserves lightweight ...", "subpage_snippet": "", "source": "www.catalyzex.com", "link": "https://www.catalyzex.com/author/Jie+Hu", "content": "Abstract:We propose a history-driven target ( HDT ) framework in Markov Chain ... empirical measure of past visits. This design preserves lightweight ..."}

data/sampled_jsons/HTML_is_Better_Than_Plain_Text_for_Modeling_Retrieved_Knowledge_in_RAG_Systems_Table_4_Prune-Gen_LLM_year_2024.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "To alleviate this problem, we propose HtmlRAG, which uses HTML instead of plain text as the format of retrieved knowledge in RAG . We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML . However, utilizing HTML presents new challenges.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.02959", "content": "To alleviate this problem, we propose HtmlRAG, which uses HTML instead of plain text as the format of retrieved knowledge in RAG . We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML . However, utilizing HTML presents new challenges."}
+{"idx": 1, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieval Results ...", "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": 2, "title": "Understanding HtmlRAG: HTML is Better Than Plain Text for Modeling ...", "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). This approach preserves essential data structure, improving LLM performance and accuracy.", "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). This approach preserves essential data structure, improving LLM performance and accuracy."}
+{"idx": 3, "title": "Implementing HtmlRAG: Enhancing Retrieval-Augmented ... - Dev Genius", "date": "", "ddg_snippet": "Retrieval-Augmented Generation ( RAG ) systems have gained significant traction in enhancing the knowledge capabilities of Large Language Models (LLMs) and mitigating issues like hallucinations. 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 ...", "subpage_snippet": "", "source": "blog.devgenius.io", "link": "https://blog.devgenius.io/implementing-htmlrag-enhancing-retrieval-augmented-generation-with-html-knowledge-91cdd6278e23", "content": "Retrieval-Augmented Generation ( RAG ) systems have gained significant traction in enhancing the knowledge capabilities of Large Language Models (LLMs) and mitigating issues like hallucinations. 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 ..."}
+{"idx": 4, "title": "Table 4 from HtmlRAG: HTML is Better Than Plain Text for Modeling ...", "date": "", "ddg_snippet": "Table 4 : Analysis of inference cost on ELI5 dataset We compare the chunking-based refiner using BGE (BGE), the two HTML pruning steps basing on the text embedding (PruneEmbed) and the generative model ( Prune -Gen) in HtmlRAG, and LLM chatting (LLM Chat) by model parameters, storage, average input tokens, and average output tokens.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/HtmlRAG:-HTML-is-Better-Than-Plain-Text-for-in-RAG-Tan-Dou/7cfd2426ca908c8c5a81bd7c7ca01f914a972de4/figure/6", "content": "Table 4 : Analysis of inference cost on ELI5 dataset We compare the chunking-based refiner using BGE (BGE), the two HTML pruning steps basing on the text embedding (PruneEmbed) and the generative model ( Prune -Gen) in HtmlRAG, and LLM chatting (LLM Chat) by model parameters, storage, average input tokens, and average output tokens."}
+{"idx": 5, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML . However, utilizing HTML presents new challenges. HTML contains additional content such as tags, JavaScript, and CSS specifications, which bring extra input tokens and noise to the RAG system .", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/abs/10.1145/3696410.3714546", "content": "We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML . However, utilizing HTML presents new challenges. HTML contains additional content such as tags, JavaScript, and CSS specifications, which bring extra input tokens and noise to the RAG system ."}
+{"idx": 6, "title": "HTML > Plain Text for RAG - by Pascal Biese - LLM Watch", "date": "", "ddg_snippet": "HtmlRAG addresses this issue by using HTML instead of plain text as the format for retrieved knowledge in RAG systems . The authors believe that HTML is better suited for modeling knowledge in external documents, and most LLMs have robust capabilities to understand HTML .", "subpage_snippet": "", "source": "www.llmwatch.com", "link": "https://www.llmwatch.com/p/html-plain-text-for-rag", "content": "HtmlRAG addresses this issue by using HTML instead of plain text as the format for retrieved knowledge in RAG systems . The authors believe that HTML is better suited for modeling knowledge in external documents, and most LLMs have robust capabilities to understand HTML ."}
+{"idx": 7, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "To alleviate this problem, we propose HtmlRAG, which uses HTML instead of plain text as the format of retrieved knowledge in RAG . We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML . However, utilizing HTML presents new chal-lenges.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2411.02959v1", "content": "To alleviate this problem, we propose HtmlRAG, which uses HTML instead of plain text as the format of retrieved knowledge in RAG . We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML . However, utilizing HTML presents new chal-lenges."}
+{"idx": 8, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems Jiejun Tan, Zhicheng Dou, Wen Wang, Mang Wang, Weipeng Chen, Ji-Rong Wen", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=leCEFyMyxg", "content": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems Jiejun Tan, Zhicheng Dou, Wen Wang, Mang Wang, Weipeng Chen, Ji-Rong Wen"}
+{"idx": 9, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved ...", "date": "", "ddg_snippet": "HTML contains a lot of intrinsic information, so we propose taking HTML as the format of retrieved knowledge in RAG systems , and design HTML cleaning and block-tree-based HTML pruning to shorten the length and preserve information.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2411.02959", "content": "HTML contains a lot of intrinsic information, so we propose taking HTML as the format of retrieved knowledge in RAG systems , and design HTML cleaning and block-tree-based HTML pruning to shorten the length and preserve information."}

data/sampled_jsons/Here_we_introduce_trial-by-trial_error_consistency,_a_quantitative_analysis_for_measuring_whether_tw.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2006.16736] Beyond accuracy: quantifying trial - by - trial behaviour of...", "date": "", "ddg_snippet": "Here we introduce trial - by - trial error consistency , a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2006.16736", "content": "Here we introduce trial - by - trial error consistency , a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 1, "title": "Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and ...", "date": "", "ddg_snippet": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2020/hash/9f6992966d4c363ea0162a056cb45fe5-Abstract.html", "content": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 2, "title": "Psychophysical experiment. A fixation cross is presented for 500 ms....", "date": "", "ddg_snippet": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/figure/Psychophysical-experiment-A-fixation-cross-is-presented-for-500-ms-Then-an-image-is_fig2_264038033", "content": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 3, "title": "Beyond accuracy: quantifying trial - by - trial behaviour of CNNs and...", "date": "", "ddg_snippet": "Here we introduce trial - by - trial error consistency , a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "papertalk.org", "link": "https://papertalk.org/papertalks/10006", "content": "Here we introduce trial - by - trial error consistency , a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 4, "title": "Beyond accuracy: quantifying trial - by - trial behaviour of CNNs and...", "date": "", "ddg_snippet": "Here we introduce trial - by - trial error consistency , a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/342587815_Beyond_accuracy_quantifying_trial-by-trial_behaviour_of_CNNs_and_humans_by_measuring_error_consistency", "content": "Here we introduce trial - by - trial error consistency , a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 5, "title": "Beyond accuracy | Proceedings of the 34th International Conference on ...", "date": "", "ddg_snippet": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3495724.3496889", "content": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 6, "title": "arXiv:2006.16736v3 [cs.CV] 18 Dec 2020", "date": "", "ddg_snippet": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs. Making consistent errors on a trial-by-trial basis is a necessary condition if we want to ascertain similar processing strategies between decision makers.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2006.16736v3", "content": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs. Making consistent errors on a trial-by-trial basis is a necessary condition if we want to ascertain similar processing strategies between decision makers."}
+{"idx": 7, "title": "New conference paper accepted at NeurIPS 2020", "date": "", "ddg_snippet": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "uni-tuebingen.de", "link": "https://uni-tuebingen.de/en/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/neuronale-informationsverarbeitung/news/newsfullview-archive/article/new-conference-paper-accepted-at-neurips-2020/", "content": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 8, "title": "New arcticle updoaded to arXiv - Universität Tübingen", "date": "", "ddg_snippet": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "uni-tuebingen.de", "link": "https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/neuronale-informationsverarbeitung/news/newsfullview-archive/article/new-arcticle-updoaded-to-arxiv/", "content": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}
+{"idx": 9, "title": "New conference paper accepted at NeurIPS 2020 - Universität Tübingen", "date": "", "ddg_snippet": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs.", "subpage_snippet": "", "source": "uni-tuebingen.de", "link": "https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/neuronale-informationsverarbeitung/news/newsfullview-aktuell/article/new-conference-paper-accepted-at-neurips-2020/", "content": "Here we introduce trial-by-trial error consistency, a quantitative analysis for measuring whether two decision making systems systematically make errors on the same inputs."}

data/sampled_jsons/Hierarchical_Overlapping_Clustering_on_Graphs.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "ICML Poster Hierarchical Overlapping Clustering on Graphs : Cost...", "date": "", "ddg_snippet": "Overlap and hierarchy are two prevalent phenomena in clustering , and usually coexist in a single system.To address this issue, we initiate the study of hierarchical overlapping clustering on graphs by introducing a new cost function for it.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46447", "content": "Overlap and hierarchy are two prevalent phenomena in clustering , and usually coexist in a single system.To address this issue, we initiate the study of hierarchical overlapping clustering on graphs by introducing a new cost function for it."}
+{"idx": 1, "title": "Hierarchical Single-Linkage Clustering for Community Detection with...", "date": "", "ddg_snippet": "Keywords Graph Clustering , Community Detection, Edge Clustering , Overlapping Clustering , Hierarchical Clustering . 1 Introduction.For overlapping clusters , we use ABCD+o2 [21] graphs that have both outliers and overlapping ground truth clusters .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2509.02334", "content": "Keywords Graph Clustering , Community Detection, Edge Clustering , Overlapping Clustering , Hierarchical Clustering . 1 Introduction.For overlapping clusters , we use ABCD+o2 [21] graphs that have both outliers and overlapping ground truth clusters ."}
+{"idx": 2, "title": "Overlapping community detection in weighted networks via...", "date": "", "ddg_snippet": "4 Proposed algorithm for overlapping hierarchical community detection in weighted networks. Hierarchical agglomerative clustering on the graph (GHAC) detects nested communities in a network using novel dissimilarity.", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11515960/", "content": "4 Proposed algorithm for overlapping hierarchical community detection in weighted networks. Hierarchical agglomerative clustering on the graph (GHAC) detects nested communities in a network using novel dissimilarity."}
+{"idx": 3, "title": "(PDF) Overlapping community detection in weighted networks via...", "date": "", "ddg_snippet": "In this work, we propose an algorithm for hierarchical overlapping community detection in weighted networks. The overlap between clusters is realized via maximal cliques that are used as base elements for hierarchical agglomerative clustering on the graph (GHAC).", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/385311779_Overlapping_community_detection_in_weighted_networks_via_hierarchical_clustering", "content": "In this work, we propose an algorithm for hierarchical overlapping community detection in weighted networks. The overlap between clusters is realized via maximal cliques that are used as base elements for hierarchical agglomerative clustering on the graph (GHAC)."}
+{"idx": 4, "title": "Overlapping Hierarchical Clustering (OHC) | SpringerLink", "date": "", "ddg_snippet": "In this paper we propose a new method that allows clusters to overlap until a strong cluster attraction is reached, based on a density criterion. The resulting hierarchical structure, called a quasi-dendrogram, is represented as a directed acyclic graph and combines the advantages of...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/chapter/10.1007/978-3-030-44584-3_21", "content": "In this paper we propose a new method that allows clusters to overlap until a strong cluster attraction is reached, based on a density criterion. The resulting hierarchical structure, called a quasi-dendrogram, is represented as a directed acyclic graph and combines the advantages of..."}
+{"idx": 5, "title": "Overlapping Hierarchical Clustering (OHC)", "date": "", "ddg_snippet": "Overlapping Hierarchical Clustering (OHC). Ian Jeantet, Zoltan Miklos, David Gross-Amblard. Overlapping Hierarchical Clustering (OHC). IDA 2020, April 27 – 29 13 / 11. Cluster growth. How are the clusters growing? Let’s start with this (δi = 2.23)-neighbourhood graph .", "subpage_snippet": "", "source": "inria.hal.science", "link": "https://inria.hal.science/hal-02452729/file/55_Overlapping_Hierarchical_Clustering_IDA_2020.pdf", "content": "Overlapping Hierarchical Clustering (OHC). Ian Jeantet, Zoltan Miklos, David Gross-Amblard. Overlapping Hierarchical Clustering (OHC). IDA 2020, April 27 – 29 13 / 11. Cluster growth. How are the clusters growing? Let’s start with this (δi = 2.23)-neighbourhood graph ."}
+{"idx": 6, "title": "Finding communities by clustering a graph into overlapping subgraphs", "date": "", "ddg_snippet": "In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics.", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/54240030/Finding_communities_by_clustering_a_graph_into_overlapping_subgraphs", "content": "In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics."}
+{"idx": 7, "title": "Unsupervised Clustering : A Guide | Built In", "date": "", "ddg_snippet": "A hierarchical clustering algorithm is based on the union between the two nearest clusters . The beginning condition is realized by setting every data point as a cluster . After a few iterations it reaches the final clusters wanted.", "subpage_snippet": "", "source": "builtin.com", "link": "https://builtin.com/articles/unsupervised-clustering", "content": "A hierarchical clustering algorithm is based on the union between the two nearest clusters . The beginning condition is realized by setting every data point as a cluster . After a few iterations it reaches the final clusters wanted."}
+{"idx": 8, "title": "Overview of overlapping partitional clustering", "date": "", "ddg_snippet": "Basically, the existing overlapping clustering methods are extensions from usual clustering models such as hierarchical , generative, graph -based or partitional mod-els. Graph -based data clustering with overlaps . Discrete Optimization, 8(1):2–17.", "subpage_snippet": "", "source": "www.larodec.com", "link": "https://www.larodec.com/download/file/fid/432", "content": "Basically, the existing overlapping clustering methods are extensions from usual clustering models such as hierarchical , generative, graph -based or partitional mod-els. Graph -based data clustering with overlaps . Discrete Optimization, 8(1):2–17."}
+{"idx": 9, "title": "An Edge-Based Approach to Partitioning and Overlapping Graph ...", "date": "", "ddg_snippet": "Graph clustering is an NP-class problem [9] that can be classified into three distinct categories, partitioning, overlapping , and hierarchical clustering [2]. Section 3 elaborates on this further.", "subpage_snippet": "", "source": "www.mdpi.com", "link": "https://www.mdpi.com/2076-3417/14/1/380", "content": "Graph clustering is an NP-class problem [9] that can be classified into three distinct categories, partitioning, overlapping , and hierarchical clustering [2]. Section 3 elaborates on this further."}

data/sampled_jsons/HtmlRAG_LLM_Chat.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling ...", "date": "", "ddg_snippet": "To alleviate this problem, we propose HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG. We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.02959v1", "content": "To alleviate this problem, we propose HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG. We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML."}
+{"idx": 1, "title": "Table 4 from HtmlRAG: HTML is Better Than Plain Text for ...", "date": "", "ddg_snippet": "HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG, and designs a two-step block-tree-based pruning method that prunes useless HTML blocks and keeps only the relevant part of the HTML.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/HtmlRAG:-HTML-is-Better-Than-Plain-Text-for-in-RAG-Tan-Dou/7cfd2426ca908c8c5a81bd7c7ca01f914a972de4/figure/6", "content": "HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG, and designs a two-step block-tree-based pruning method that prunes useless HTML blocks and keeps only the relevant part of the HTML."}
+{"idx": 2, "title": "HtmlRAG: HTML is Better Than Plain Text for Modeling ...", "date": "", "ddg_snippet": "To alleviate this problem, we propose HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG. We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2411.02959v1", "content": "To alleviate this problem, we propose HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG. We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML."}
+{"idx": 3, "title": "Htmlrag: HTML Is Better Than Plain Text For Modeling ...", "date": "", "ddg_snippet": "To address this issue, we propose HTML cleaning, ( RAG ) utilizes a retrieval system to fetch external knowledge and. compression, and pruning strategies, to shorten the HTML while augment the LLM . It has proved effective in mitigating hallucina- minimizing the loss of information. Specifically, we design a two- tions of LLMs [41, 76].", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/788595083/2411-02959v1", "content": "To address this issue, we propose HTML cleaning, ( RAG ) utilizes a retrieval system to fetch external knowledge and. compression, and pruning strategies, to shorten the HTML while augment the LLM . It has proved effective in mitigating hallucina- minimizing the loss of information. Specifically, we design a two- tions of LLMs [41, 76]."}
+{"idx": 4, "title": "[2411.02959] HtmlRAG: HTML is Better Than Plain Text for ...", "date": "", "ddg_snippet": "To alleviate this problem, we propose HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG. We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML.", "subpage_snippet": "", "source": "ar5iv.labs.arxiv.org", "link": "https://ar5iv.labs.arxiv.org/html/2411.02959", "content": "To alleviate this problem, we propose HtmlRAG , which uses HTML instead of plain text as the format of retrieved knowledge in RAG. We believe HTML is better than plain text in modeling knowledge in external documents, and most LLMs possess robust capacities to understand HTML."}
+{"idx": 5, "title": "LLM Research Papers: The 2024 List", "date": "", "ddg_snippet": "In the meantime, I want to share my running bookmark list of many fascinating (mostly LLM -related) papers I stumbled upon in 2024.", "subpage_snippet": "", "source": "magazine.sebastianraschka.com", "link": "https://magazine.sebastianraschka.com/p/llm-research-papers-the-2024-list", "content": "In the meantime, I want to share my running bookmark list of many fascinating (mostly LLM -related) papers I stumbled upon in 2024."}
+{"idx": 6, "title": "LLM Research Papers: The 2024 List", "date": "", "ddg_snippet": "I still plan to do so, but in the meantime, I want to share my running bookmark list of many fascinating (mostly LLM - related) papers I stumbled upon ...", "subpage_snippet": "", "source": "sebastianraschka.com", "link": "https://sebastianraschka.com/blog/2024/llm-research-papers-the-2024-list.html", "content": "I still plan to do so, but in the meantime, I want to share my running bookmark list of many fascinating (mostly LLM - related) papers I stumbled upon ..."}
+{"idx": 7, "title": "HtmlRAG論文読んでみた - Zenn", "date": "", "ddg_snippet": "Nov 24, 2024 · その中でも H tml RA G と呼ばれる手法の提案がおもしろそうだったので読んでみました。 そこで備忘録がてら記事にして投稿してみようと思った次第です。", "subpage_snippet": "", "source": "zenn.dev", "link": "https://zenn.dev/argus1/articles/06319726c51874", "content": "Nov 24, 2024 · その中でも H tml RA G と呼ばれる手法の提案がおもしろそうだったので読んでみました。 そこで備忘録がてら記事にして投稿してみようと思った次第です。"}
+{"idx": 8, "title": "‘ML dataset’ directory · Gwern.net", "date": "", "ddg_snippet": "... Memorization in Multiple-Choice LLM ... HtmlRAG : HTML Is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems ”, Tan et al 2024", "subpage_snippet": "", "source": "gwern.net", "link": "https://gwern.net/doc/ai/dataset/index", "content": "... Memorization in Multiple-Choice LLM ... HtmlRAG : HTML Is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems ”, Tan et al 2024"}
+{"idx": 9, "title": "‘retrieval AI’ directory · Gwern.net", "date": "", "ddg_snippet": "How ChatGPT Remembers You: A Deep ... HtmlRAG : HTML Is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems ”, Tan et al 2024", "subpage_snippet": "", "source": "gwern.net", "link": "https://gwern.net/doc/ai/nn/retrieval/index", "content": "How ChatGPT Remembers You: A Deep ... HtmlRAG : HTML Is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems ”, Tan et al 2024"}

data/sampled_jsons/ICML_2025_Normalizing_Flows_papers.jsonl

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+{"idx": 0, "title": "ICML 2025 Normalizing Flows are Capable Generative Models Oral", "date": "", "ddg_snippet": "Oral Normalizing Flows are Capable Generative Models Shuangfei Zhai · Ruixiang Zhang · Preetum Nakkiran · David Berthelot · Jiatao Gu · Huangjie Zheng · Tianrong Chen · Miguel Angel Bautista Martin · Navdeep Jaitly · Joshua M Susskind West Ballroom A [ Abstract ] [ Visit Oral 6B Deep Learning Architectures ] Thu 17 Jul 4 p.m. — 4:15 ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/oral/47266", "content": "Oral Normalizing Flows are Capable Generative Models Shuangfei Zhai · Ruixiang Zhang · Preetum Nakkiran · David Berthelot · Jiatao Gu · Huangjie Zheng · Tianrong Chen · Miguel Angel Bautista Martin · Navdeep Jaitly · Joshua M Susskind West Ballroom A [ Abstract ] [ Visit Oral 6B Deep Learning Architectures ] Thu 17 Jul 4 p.m. — 4:15 ..."}
+{"idx": 1, "title": "[2412.06329] Normalizing Flows are Capable Generative Models", "date": "", "ddg_snippet": "View a PDF of the paper titled Normalizing Flows are Capable Generative Models, by Shuangfei Zhai and 9 other authors", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2412.06329", "content": "View a PDF of the paper titled Normalizing Flows are Capable Generative Models, by Shuangfei Zhai and 9 other authors"}
+{"idx": 2, "title": "Normalizing Flows are Capable Generative Models - Apple Machine ...", "date": "", "ddg_snippet": "Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative modeling tasks, but have received relatively little attention in recent years. In this work, we demonstrate that NFs are more powerful than previously believed. We present TarFlow: a simple and scalable architecture that enables highly ...", "subpage_snippet": "", "source": "machinelearning.apple.com", "link": "https://machinelearning.apple.com/research/normalizing-flows", "content": "Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative modeling tasks, but have received relatively little attention in recent years. In this work, we demonstrate that NFs are more powerful than previously believed. We present TarFlow: a simple and scalable architecture that enables highly ..."}
+{"idx": 3, "title": "ICML 2025 Accepted Paper List - Paper Copilot", "date": "", "ddg_snippet": "How to use the paper list below:- Overview: This table presents papers from the ICML conference, year 2025 .- Filtering: By default, the table loads the first 100 records. You can use the filter box under each column header to search within these loaded entries.", "subpage_snippet": "", "source": "papercopilot.com", "link": "https://papercopilot.com/paper-list/icml-paper-list/icml-2025-paper-list/", "content": "How to use the paper list below:- Overview: This table presents papers from the ICML conference, year 2025 .- Filtering: By default, the table loads the first 100 records. You can use the filter box under each column header to search within these loaded entries."}
+{"idx": 4, "title": "ICML.2025 | Cool Papers - Immersive Paper Discovery", "date": "", "ddg_snippet": "The list of accepted papers for ICML.2025 , including titles, authors, and abstracts, with support for paper interpretation based on Kimi AI.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/ICML.2025", "content": "The list of accepted papers for ICML.2025 , including titles, authors, and abstracts, with support for paper interpretation based on Kimi AI."}
+{"idx": 5, "title": "ICML 2025 Papers", "date": "", "ddg_snippet": "Enable Javascript in your browser to see the papers page.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/papers.html?search=agent", "content": "Enable Javascript in your browser to see the papers page."}
+{"idx": 6, "title": "[2505.23527] Normalizing Flows are Capable Models for RL", "date": "", "ddg_snippet": "View a PDF of the paper titled Normalizing Flows are Capable Models for RL, by Raj Ghugare and Benjamin Eysenbach", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2505.23527", "content": "View a PDF of the paper titled Normalizing Flows are Capable Models for RL, by Raj Ghugare and Benjamin Eysenbach"}
+{"idx": 7, "title": "GitHub - serendipityerr/Diffusion-Papers-ICML-2025", "date": "", "ddg_snippet": "INRFlow: Flow Matching for INRs in Ambient Space. [pdf] Ensemble Distribution Distillation via Flow Matching. [pdf] Flexible Tails for Normalizing Flows . [pdf] Wasserstein Flow Matching: Generative Modeling Over Families of Distributions. [pdf] SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations. [pdf]", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/serendipityerr/Diffusion-Papers-ICML-2025", "content": "INRFlow: Flow Matching for INRs in Ambient Space. [pdf] Ensemble Distribution Distillation via Flow Matching. [pdf] Flexible Tails for Normalizing Flows . [pdf] Wasserstein Flow Matching: Generative Modeling Over Families of Distributions. [pdf] SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations. [pdf]"}
+{"idx": 8, "title": "Stanford AI Lab Papers and Talks at ICML 2025 | SAIL Blog", "date": "", "ddg_snippet": "The Forty-Second International Conference on Machine Learning ( ICML ) 2025 is being hosted in Vancouver from July 13 to July 19. We're excited to share all the work from SAIL that's being presented, and you'll find links to papers , videos and blogs below.", "subpage_snippet": "", "source": "ai.stanford.edu", "link": "https://ai.stanford.edu/blog/icml-2025/", "content": "The Forty-Second International Conference on Machine Learning ( ICML ) 2025 is being hosted in Vancouver from July 13 to July 19. We're excited to share all the work from SAIL that's being presented, and you'll find links to papers , videos and blogs below."}
+{"idx": 9, "title": "Normalizing Flows are Capable Generative Models - OpenReview", "date": "", "ddg_snippet": "Published: 01 May 2025 , Last Modified: 23 Jul 2025 ICML 2025 oral Everyone Revisions BibTeX CC BY 4.0 TL;DR: We show that normalizing flows can work great as a generative modeling principle, and propose a simple architecture and set of techniques to achieve it.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=2uheUFcFsM", "content": "Published: 01 May 2025 , Last Modified: 23 Jul 2025 ICML 2025 oral Everyone Revisions BibTeX CC BY 4.0 TL;DR: We show that normalizing flows can work great as a generative modeling principle, and propose a simple architecture and set of techniques to achieve it."}

data/sampled_jsons/Intervention_and_Conditioning_in_Causal_Bayesian_Networks_year_None.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Watch Intervention Full Episodes, Video & More | A&E", "date": "", "ddg_snippet": "The Emmy award-winning series “Intervention” profiles people whose uncontrollable addiction to drugs, alcohol or compulsive behavior has brought them to the brink of destruction and has …", "subpage_snippet": "", "source": "www.aetv.com", "link": "https://www.aetv.com/shows/intervention", "content": "The Emmy award-winning series “Intervention” profiles people whose uncontrollable addiction to drugs, alcohol or compulsive behavior has brought them to the brink of destruction and has …"}
+{"idx": 1, "title": "INTERVENTION | English meaning - Cambridge Dictionary", "date": "", "ddg_snippet": "INTERVENTION definition: 1. intentional action to change a situation, with the aim of improving it or preventing it from…. Learn more.", "subpage_snippet": "", "source": "dictionary.cambridge.org", "link": "https://dictionary.cambridge.org/dictionary/english/intervention", "content": "INTERVENTION definition: 1. intentional action to change a situation, with the aim of improving it or preventing it from…. Learn more."}
+{"idx": 2, "title": "INTERVENTION Definition & Meaning - Merriam-Webster", "date": "", "ddg_snippet": "The meaning of INTERVENTION is the act or an instance of intervening. How to use intervention in a sentence.", "subpage_snippet": "", "source": "www.merriam-webster.com", "link": "https://www.merriam-webster.com/dictionary/intervention", "content": "The meaning of INTERVENTION is the act or an instance of intervening. How to use intervention in a sentence."}
+{"idx": 3, "title": "INTERVENTION Definition & Meaning | Dictionary.com", "date": "", "ddg_snippet": "Intervention definition: the act or fact of coming or occurring between two people, things, or times.. See examples of INTERVENTION used in a sentence.", "subpage_snippet": "", "source": "www.dictionary.com", "link": "https://www.dictionary.com/browse/intervention", "content": "Intervention definition: the act or fact of coming or occurring between two people, things, or times.. See examples of INTERVENTION used in a sentence."}
+{"idx": 4, "title": "Intervention - Definition, Meaning & Synonyms | Vocabulary.com", "date": "", "ddg_snippet": "An intervention is the act of inserting one thing between others, like a person trying to help. You could be the subject of a school intervention if your teachers call your parents about the bad …", "subpage_snippet": "", "source": "www.vocabulary.com", "link": "https://www.vocabulary.com/dictionary/intervention", "content": "An intervention is the act of inserting one thing between others, like a person trying to help. You could be the subject of a school intervention if your teachers call your parents about the bad …"}
+{"idx": 5, "title": "INTERVENTION definition and meaning | Collins English Dictionary", "date": "", "ddg_snippet": "An intervention is an occasion when friends or family tell someone who has a serious problem that they need to get help. Finally, his wife staged an intervention and he agreed to go into rehab. …", "subpage_snippet": "", "source": "www.collinsdictionary.com", "link": "https://www.collinsdictionary.com/dictionary/english/intervention", "content": "An intervention is an occasion when friends or family tell someone who has a serious problem that they need to get help. Finally, his wife staged an intervention and he agreed to go into rehab. …"}
+{"idx": 6, "title": "Intervention - definition of intervention by The Free Dictionary", "date": "", "ddg_snippet": "The act or process of intervening: a nation's military interventions in neighboring countries; a politician opposed to government intervention in the market economy.", "subpage_snippet": "", "source": "www.thefreedictionary.com", "link": "https://www.thefreedictionary.com/intervention", "content": "The act or process of intervening: a nation's military interventions in neighboring countries; a politician opposed to government intervention in the market economy."}
+{"idx": 7, "title": "intervention , n. meanings, etymology and more | Oxford English …", "date": "", "ddg_snippet": "intervention, n. meanings, etymology, pronunciation and more in the Oxford English Dictionary", "subpage_snippet": "", "source": "www.oed.com", "link": "https://www.oed.com/dictionary/intervention_n", "content": "intervention, n. meanings, etymology, pronunciation and more in the Oxford English Dictionary"}
+{"idx": 8, "title": "Intervention : Meaning, Definition, and Practical Applications", "date": "", "ddg_snippet": "Nov 3, 2024 · Meaning of the Word Intervention refers to the action or process of intervening in a situation, often to change or influence the outcome. It involves stepping into a situation with …", "subpage_snippet": "", "source": "meaningdictionary.com", "link": "https://meaningdictionary.com/intervention-meaning-definition-and-practical-applications/", "content": "Nov 3, 2024 · Meaning of the Word Intervention refers to the action or process of intervening in a situation, often to change or influence the outcome. It involves stepping into a situation with …"}
+{"idx": 9, "title": "Early Intervention | Learn the Signs. Act Early. | CDC", "date": "", "ddg_snippet": "Early Intervention... Is the term used to describe services and supports available to babies and young children with developmental delays and disabilities and their families. May include …", "subpage_snippet": "", "source": "www.cdc.gov", "link": "https://www.cdc.gov/act-early/early-intervention/index.html", "content": "Early Intervention... Is the term used to describe services and supports available to babies and young children with developmental delays and disabilities and their families. May include …"}

data/sampled_jsons/LAuReL_arxiv.org_LAUREL-LR_equation_implementation_formula.jsonl

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+{"idx": 0, "title": "arXiv . org e-Print archive", "date": "", "ddg_snippet": "Help Improve arXiv . arXiv is working with academic researchers to investigate ways to improve the service for our users. This requires a rich dataset to better inform the research. Users who wish to contribute to the future of arXiv may opt in to all...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/", "content": "Help Improve arXiv . arXiv is working with academic researchers to investigate ways to improve the service for our users. This requires a rich dataset to better inform the research. Users who wish to contribute to the future of arXiv may opt in to all..."}
+{"idx": 1, "title": "Markup for Rich Contents (The Org Manual)", "date": "", "ddg_snippet": "Or you may need to insert a formula or image in your writing. Org offers syntax for all of this and more. Used in conjunction with the export framework (see Exporting), you can author beautiful documents in Org —like the fine manual you are currently reading.", "subpage_snippet": "", "source": "orgmode.org", "link": "https://orgmode.org/manual/Markup-for-Rich-Contents.html", "content": "Or you may need to insert a formula or image in your writing. Org offers syntax for all of this and more. Used in conjunction with the export framework (see Exporting), you can author beautiful documents in Org —like the fine manual you are currently reading."}
+{"idx": 2, "title": "Winlator, Новый эмулятор для запуска Windows (ПК) игр для Android", "date": "", "ddg_snippet": "DXVK_ENABLE_D3D12=0: Disables the translation of DirectX 12 calls. Setting it to 0 can be useful for compatibility if a game has issues with DXVK's D3D12 implementation , forcing it to use D3D11 instead.", "subpage_snippet": "", "source": "4pda.to", "link": "https://4pda.to/forum/index.php?showtopic=1073499&st=27980", "content": "DXVK_ENABLE_D3D12=0: Disables the translation of DirectX 12 calls. Setting it to 0 can be useful for compatibility if a game has issues with DXVK's D3D12 implementation , forcing it to use D3D11 instead."}
+{"idx": 3, "title": "Aman's AI Journal • Papers List", "date": "", "ddg_snippet": "chrF Score Formula LAUREL -RW+ LR +PA: 75.25% (+2.40% params), outperforming naive scaling with fewer parameters. 1B LLM Pretraining (LLM-1)", "subpage_snippet": "", "source": "aman.ai", "link": "https://aman.ai/papers/", "content": "chrF Score Formula LAUREL -RW+ LR +PA: 75.25% (+2.40% params), outperforming naive scaling with fewer parameters. 1B LLM Pretraining (LLM-1)"}
+{"idx": 4, "title": "Анимированные курсоры для Windows (200+)", "date": "", "ddg_snippet": "Наборы с преобладанием анимированных (подвижных) указателей Windows в формате ani. Для тех, кто любит подолгу залипать на курсор.", "subpage_snippet": "", "source": "VSThemes.org", "link": "https://VSThemes.org/cursors/animated/", "content": "Наборы с преобладанием анимированных (подвижных) указателей Windows в формате ani. Для тех, кто любит подолгу залипать на курсор."}
+{"idx": 5, "title": "Ulysses | The Poetry Foundation", "date": "", "ddg_snippet": "We are not now that strength which in old daysOne equal temper of heroic hearts", "subpage_snippet": "", "source": "www.poetryfoundation.org", "link": "https://www.poetryfoundation.org/poems/45392/ulysses", "content": "We are not now that strength which in old daysOne equal temper of heroic hearts"}
+{"idx": 6, "title": "SimPlaza – MSFS 2020 Aircraft & More", "date": "", "ddg_snippet": "SimPlaza Recommended, iniBuilds, MSFS 2020 Aircraft, MSFS 2020 Airliner. PMDG – Boeing 777–200 LR v2.0.128.", "subpage_snippet": "", "source": "simplaza.org", "link": "https://simplaza.org/", "content": "SimPlaza Recommended, iniBuilds, MSFS 2020 Aircraft, MSFS 2020 Airliner. PMDG – Boeing 777–200 LR v2.0.128."}
+{"idx": 7, "title": "Angular Material UI Component Library", "date": "", "ddg_snippet": "UI component infrastructure and Material Design components for mobile and desktop Angular web applications.", "subpage_snippet": "", "source": "material.angular.dev", "link": "https://material.angular.dev/components/datepicker/overview", "content": "UI component infrastructure and Material Design components for mobile and desktop Angular web applications."}
+{"idx": 8, "title": "Ancient Grome - TV Tropes", "date": "", "ddg_snippet": "A sister trope to Mayincatec, Spexico, Far East and Scotireland, a tendency for writers to overlap the Greek and Roman civilizations and confuse aspects of the two Classical civilizations, e.g. Roman numerals in an otherwise Greek setting, Greek …", "subpage_snippet": "", "source": "tvtropes.org", "link": "https://tvtropes.org/pmwiki/pmwiki.php/Main/AncientGrome", "content": "A sister trope to Mayincatec, Spexico, Far East and Scotireland, a tendency for writers to overlap the Greek and Roman civilizations and confuse aspects of the two Classical civilizations, e.g. Roman numerals in an otherwise Greek setting, Greek …"}
+{"idx": 9, "title": "On the Theoretical Limitations of Embedding-Based Retrieval | alphaXiv", "date": "", "ddg_snippet": "View 1 comments: 严格正交 (Orthogonal)：在 n 维欧几里得空间 R^n 中，一个向量组如果两两严格正交（夹角精确为90°，或点积为0），那么这个向量组的大小（基数）最多为 n。这构成了该空间的一组正交基。近似正交 (Almost/Nearly Orthogonal)：如果我们...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/pdf/2508.21038", "content": "View 1 comments: 严格正交 (Orthogonal)：在 n 维欧几里得空间 R^n 中，一个向量组如果两两严格正交（夹角精确为90°，或点积为0），那么这个向量组的大小（基数）最多为 n。这构成了该空间的一组正交基。近似正交 (Almost/Nearly Orthogonal)：如果我们..."}

data/sampled_jsons/LUNO_Linearization_Neural_Operators_Magnani_2022_Related_Work_section_FNO.jsonl

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+{"idx": 0, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian ...", "date": "", "ddg_snippet": "More closely related to our work , Magnani et al. ( 2022 ) developed uncer-tainty estimates for graph neural operators using Laplace approximation, though their approach does not extend to FNOs , nor does it consider function space formulations.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=4Z04wVQ9FY", "content": "More closely related to our work , Magnani et al. ( 2022 ) developed uncer-tainty estimates for graph neural operators using Laplace approximation, though their approach does not extend to FNOs , nor does it consider function space formulations."}
+{"idx": 1, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian ...", "date": "", "ddg_snippet": "Spotlight Poster Linearization Turns Neural Operators into Function-Valued Gaussian Processes Emilia Magnani · Marvin Pförtner · Tobias Weber · Philipp Hennig East Exhibition Hall A-B #E-1207", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46474", "content": "Spotlight Poster Linearization Turns Neural Operators into Function-Valued Gaussian Processes Emilia Magnani · Marvin Pförtner · Tobias Weber · Philipp Hennig East Exhibition Hall A-B #E-1207"}
+{"idx": 2, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian ...", "date": "", "ddg_snippet": "We introduce LUNO , a novel framework for approximate Bayesian uncertainty quantification in trained neural operators . Our approach leverages model linearization to push (Gaussian) weight-space uncertainty forward to the neural operator's predictions.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2406.05072", "content": "We introduce LUNO , a novel framework for approximate Bayesian uncertainty quantification in trained neural operators . Our approach leverages model linearization to push (Gaussian) weight-space uncertainty forward to the neural operator's predictions."}
+{"idx": 3, "title": "LUNO: Linearized Predictive Uncertainty in Neural Operators", "date": "", "ddg_snippet": "luno - Linearized Uncertainty for Neural Operators This repository contains the main algorithm of the paper \" Linearization Turns Neural Operators into Function-Valued Gaussian Processes\" by Magnani et al. (2025).", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/MethodsOfMachineLearning/luno", "content": "luno - Linearized Uncertainty for Neural Operators This repository contains the main algorithm of the paper \" Linearization Turns Neural Operators into Function-Valued Gaussian Processes\" by Magnani et al. (2025)."}
+{"idx": 4, "title": "(PDF) Linearization Turns Neural Operators into Function-Valued ...", "date": "", "ddg_snippet": "Neural operators are deep neural networks designed to learn nontrivial solution operators of such differential equations from data.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381294298_Linearization_Turns_Neural_Operators_into_Function-Valued_Gaussian_Processes", "content": "Neural operators are deep neural networks designed to learn nontrivial solution operators of such differential equations from data."}
+{"idx": 5, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian ...", "date": "", "ddg_snippet": "In Section 4, we discuss prior work on operator learning and related uncertainty quantifica-tion. Finally, we demonstrate in Section 5 the effectiveness of LUNO in common PDE learning settings.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.05072v2", "content": "In Section 4, we discuss prior work on operator learning and related uncertainty quantifica-tion. Finally, we demonstrate in Section 5 the effectiveness of LUNO in common PDE learning settings."}
+{"idx": 6, "title": "PDF Abstract Linearization Turns Neural Operators into ... - ResearchGate", "date": "", "ddg_snippet": "Abstract Modeling dynamical systems, e.g. in climate and engineering sciences, often ne-cessitates solving partial differential equations. Neural operators are deep neural networks designed to ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381294298_Linearization_Turns_Neural_Operators_into_Function-Valued_Gaussian_Processes/fulltext/6666938685a4ee7261b375f0/Linearization-Turns-Neural-Operators-into-Function-Valued-Gaussian-Processes.pdf", "content": "Abstract Modeling dynamical systems, e.g. in climate and engineering sciences, often ne-cessitates solving partial differential equations. Neural operators are deep neural networks designed to ..."}
+{"idx": 7, "title": "Experiments for the paper \"Linearization Turns Neural Operators into ...", "date": "", "ddg_snippet": "Experiments for the paper ` Linearization Turns Neural Operators Into Function-Valued Gaussian Processes` - 2bys/ luno -experiments", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/2bys/luno-experiments", "content": "Experiments for the paper ` Linearization Turns Neural Operators Into Function-Valued Gaussian Processes` - 2bys/ luno -experiments"}
+{"idx": 8, "title": "A comprehensive and fair comparison of two neural operators (with ...", "date": "", "ddg_snippet": "Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0045782522001207", "content": "Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering."}
+{"idx": 9, "title": "deeponet-fno/README.md at main · lu-group/deeponet-fno", "date": "", "ddg_snippet": "A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data - lu-group/deeponet- fno", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/lu-group/deeponet-fno/blob/main/README.md?plain=1", "content": "A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data - lu-group/deeponet- fno"}

data/sampled_jsons/Langevin_unlearning_A_new_perspective_of_noisy_gradient_descent_for_machine_unlearning_Chien_et_al.__year_2024.jsonl

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+{"idx": 0, "title": "Langevin Unlearning: A New Perspective of Noisy Gradient ... Langevin unlearning | Proceedings of the 38th International ... Graph-COM/Langevin_unlearning - GitHub dblp: Langevin Unlearning: A New Perspective of Noisy ... LANGEVIN UNLEARNING - OpenReview Certified Machine Unlearning via Noisy Stochastic Gradient ... The Challenge of Machine Unlearning in Data Privacy", "date": "", "ddg_snippet": "Jan 18, 2024 · We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. Jun 5, 2025 · We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . By Eli Chien , Haoyu Wang, Ziang Chen and Pan Li. Please also check our NeurIPS 2024 paper. Certified Machine Unlearning via Noisy Stochastic Gradient Descent. The code is runnable under the following enveironment: Feb 13, 2025 · dblp: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . For some months now, the dblp team has been receiving an exceptionally high number of support and error correction requests from the community. We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate un- learning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. 4 days ago · Title: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning Abstract : Machine unlearning has raised significant interest with the adoption of laws ensuring the ``right to be forgotten''.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2401.10371", "content": "Jan 18, 2024 · We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. Jun 5, 2025 · We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . By Eli Chien , Haoyu Wang, Ziang Chen and Pan Li. Please also check our NeurIPS 2024 paper. Certified Machine Unlearning via Noisy Stochastic Gradient Descent. The code is runnable under the following enveironment: Feb 13, 2025 · dblp: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . For some months now, the dblp team has been receiving an exceptionally high number of support and error correction requests from the community. We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate un- learning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits. 4 days ago · Title: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning Abstract : Machine unlearning has raised significant interest with the adoption of laws ensuring the ``right to be forgotten''."}
+{"idx": 1, "title": "Langevin unlearning | Proceedings of the 38th International ...", "date": "", "ddg_snippet": "Jun 5, 2025 · We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3737916.3740446", "content": "Jun 5, 2025 · We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits."}
+{"idx": 2, "title": "Graph-COM/Langevin_unlearning - GitHub", "date": "", "ddg_snippet": "Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . By Eli Chien , Haoyu Wang, Ziang Chen and Pan Li. Please also check our NeurIPS 2024 paper. Certified Machine Unlearning via Noisy Stochastic Gradient Descent. The code is runnable under the following enveironment:", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Graph-COM/Langevin_unlearning", "content": "Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . By Eli Chien , Haoyu Wang, Ziang Chen and Pan Li. Please also check our NeurIPS 2024 paper. Certified Machine Unlearning via Noisy Stochastic Gradient Descent. The code is runnable under the following enveironment:"}
+{"idx": 3, "title": "dblp: Langevin Unlearning: A New Perspective of Noisy ...", "date": "", "ddg_snippet": "Feb 13, 2025 · dblp: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . For some months now, the dblp team has been receiving an exceptionally high number of support and error correction requests from the community.", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/nips/ChienWCL24a", "content": "Feb 13, 2025 · dblp: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning . For some months now, the dblp team has been receiving an exceptionally high number of support and error correction requests from the community."}
+{"idx": 4, "title": "LANGEVIN UNLEARNING - OpenReview", "date": "", "ddg_snippet": "We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate un- learning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=VRrdtaaYiy", "content": "We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate un- learning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits."}
+{"idx": 5, "title": "Certified Machine Unlearning via Noisy Stochastic Gradient ...", "date": "", "ddg_snippet": "We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits.", "subpage_snippet": "", "source": "bohrium.dp.tech", "link": "https://bohrium.dp.tech/paper/arxiv/2403.17105", "content": "We propose Langevin unlearning , an unlearning framework based on noisy gradient descent with privacy guarantees for approximate unlearning problems. Langevin unlearning unifies the DP learning process and the privacy-certified unlearning process with many algorithmic benefits."}
+{"idx": 6, "title": "The Challenge of Machine Unlearning in Data Privacy", "date": "", "ddg_snippet": "4 days ago · Title: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning Abstract : Machine unlearning has raised significant interest with the adoption of laws ensuring the ``right to be forgotten''.", "subpage_snippet": "", "source": "scisimple.com", "link": "https://scisimple.com/en/articles/2025-09-16-the-challenge-of-machine-unlearning-in-data-privacy--ak2m4j1", "content": "4 days ago · Title: Langevin Unlearning : A New Perspective of Noisy Gradient Descent for Machine Unlearning Abstract : Machine unlearning has raised significant interest with the adoption of laws ensuring the ``right to be forgotten''."}
+{"idx": 7, "title": "Certified Unlearning for Neural Networks", "date": "", "ddg_snippet": "Recent works aim to achieve certified unlearning for non-convex tasks (Golatkar et al ., 2020 ; Chourasia & Shah, 2023 ; Chien et al ., 2024 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.06985v2", "content": "Recent works aim to achieve certified unlearning for non-convex tasks (Golatkar et al ., 2020 ; Chourasia & Shah, 2023 ; Chien et al ., 2024 ..."}
+{"idx": 8, "title": "Towards Reliable Forgetting: A Survey on Machine Unlearning", "date": "", "ddg_snippet": "... for privacy protection, security, and legal compliance ( e .g., GDPR), machine unlearning has emerged as a critical technique for ensuring the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.15115v1", "content": "... for privacy protection, security, and legal compliance ( e .g., GDPR), machine unlearning has emerged as a critical technique for ensuring the ..."}
+{"idx": 9, "title": "Distributional Unlearning: Forgetting Distributions, Not Just", "date": "", "ddg_snippet": "While these lines of work tackle important aspects of unlearning or robustness, they do not provide a unified, distribution‑level forgetting ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.15112v1", "content": "While these lines of work tackle important aspects of unlearning or robustness, they do not provide a unified, distribution‑level forgetting ..."}

data/sampled_jsons/Learning_stochastic_dynamics_snapshots_regularized_unbalanced_optimal_transport_Theorem_4.1_Fisher_i.jsonl

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+{"idx": 0, "title": "Learning stochastic dynamics from snapshots through regularized ...", "date": "", "ddg_snippet": "regularized unbalanced optimal transport ; Schrödinger bridge; trajectory inference; deep learning .In this section, we first introduce the RUOT problem, then derive the Fisher regularization form of RUOT, and discuss its connections with existing literature.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.00844v1", "content": "regularized unbalanced optimal transport ; Schrödinger bridge; trajectory inference; deep learning .In this section, we first introduce the RUOT problem, then derive the Fisher regularization form of RUOT, and discuss its connections with existing literature."}
+{"idx": 1, "title": "(PDF) Learning Stochastic Dynamics from Snapshots through...", "date": "", "ddg_snippet": "regularized unbalanced optimal transport (RUOT) and continuous unbalanced stochas-. tic dynamics from time-series snapshot data. By leveraging Fisher regularization , our. method transforms a stochastic differential equation (SDE) problem into an ordinary.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/384563451_Learning_Stochastic_Dynamics_from_Snapshots_through_Regularized_Unbalanced_Optimal_Transport", "content": "regularized unbalanced optimal transport (RUOT) and continuous unbalanced stochas-. tic dynamics from time-series snapshot data. By leveraging Fisher regularization , our. method transforms a stochastic differential equation (SDE) problem into an ordinary."}
+{"idx": 2, "title": "Learning stochastic dynamics from snapshots through regularized ...", "date": "", "ddg_snippet": "Reconstructing dynamics using samples from sparsely time-resolved snapshots is an important problem in both natural sciences and machine learning . Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT)...", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/Learning-Stochastic-Dynamics-from-Snapshots-through-Regularized-Unbalanced-Optimal-Transport-39225f33-522f-44ce-b836-70679229a4ab", "content": "Reconstructing dynamics using samples from sparsely time-resolved snapshots is an important problem in both natural sciences and machine learning . Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT)..."}
+{"idx": 3, "title": "Learning stochastic dynamics from snapshots through regularized ...", "date": "", "ddg_snippet": "Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT) and inferring continuous unbalanced stochastic dynamics from observed snapshots .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=gQlxd3Mtru", "content": "Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT) and inferring continuous unbalanced stochastic dynamics from observed snapshots ."}
+{"idx": 4, "title": "Learning Stochastic Dynamics from Snapshots through...", "date": "", "ddg_snippet": "Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT) and inferring continuous unbalanced stochastic dynamics from observed snapshots .", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/arxiv/2410.00844", "content": "Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT) and inferring continuous unbalanced stochastic dynamics from observed snapshots ."}
+{"idx": 5, "title": "Learning Stochastic Dynamics from Snapshots through...", "date": "", "ddg_snippet": "This paper presents a method for learning stochastic dynamics from snapshot data using regularized unbalanced optimal transport .", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/learning-stochastic-dynamics-from-snapshots-through-regularized", "content": "This paper presents a method for learning stochastic dynamics from snapshot data using regularized unbalanced optimal transport ."}
+{"idx": 6, "title": "GitHub - zhenyiizhang/DeepRUOT: Learning stochastic dynamics ...", "date": "", "ddg_snippet": "Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport . The Thirteenth International Conference on Learning Representations.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/zhenyiizhang/DeepRUOT", "content": "Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport . The Thirteenth International Conference on Learning Representations."}
+{"idx": 7, "title": "ICLR 2025 Learning stochastic dynamics from snapshots through...", "date": "", "ddg_snippet": "Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT) and inferring continuous unbalanced stochastic dynamics from observed snapshots .", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2025/oral/31800", "content": "Here, we introduce a new deep learning approach for solving regularized unbalanced optimal transport (RUOT) and inferring continuous unbalanced stochastic dynamics from observed snapshots ."}
+{"idx": 8, "title": "On the Relation Between Optimal Transport and Schrödinger... | CoLab", "date": "", "ddg_snippet": "We take a new look at the relation between the optimal transport problem and the Schrödinger bridge problem from a stochastic control perspective.", "subpage_snippet": "", "source": "colab.ws", "link": "https://colab.ws/articles/10.1007/s10957-015-0803-z", "content": "We take a new look at the relation between the optimal transport problem and the Schrödinger bridge problem from a stochastic control perspective."}
+{"idx": 9, "title": "Manifold Interpolating Optimal - Transport Flows... | Connected Papers", "date": "", "ddg_snippet": "TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics .Action Matching: Learning Stochastic Dynamics from Samples.", "subpage_snippet": "", "source": "www.connectedpapers.com", "link": "https://www.connectedpapers.com/main/b18d4ee8e80c5669e046ad76ff15da3b2f6d835e/Manifold-Interpolating-Optimal+Transport-Flows-for-Trajectory-Inference/graph", "content": "TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics .Action Matching: Learning Stochastic Dynamics from Samples."}

data/sampled_jsons/Likelihood_Based_Approach_to_Distribution_Regression_Using_Conditional_Deep_Generative_Models_PDF_ar.jsonl

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+{"idx": 0, "title": "Graphical model - Wikipedia", "date": "", "ddg_snippet": "Generally, probabilistic graphical models use a graph- based representation as the foundation for encoding a distribution over a multi-dimensional ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Graphical_model", "content": "Generally, probabilistic graphical models use a graph- based representation as the foundation for encoding a distribution over a multi-dimensional ..."}
+{"idx": 1, "title": "Generative model - Wikipedia", "date": "", "ddg_snippet": "... generative model \" is also used to describe models that generate instances of output variables in a way that has no clear relationship to probability ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Generative_model", "content": "... generative model \" is also used to describe models that generate instances of output variables in a way that has no clear relationship to probability ..."}
+{"idx": 2, "title": "Flow-based generative model - Wikipedia", "date": "", "ddg_snippet": "... based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Flow-based_generative_model", "content": "... based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow ..."}
+{"idx": 3, "title": "Generative adversarial network - Wikipedia", "date": "", "ddg_snippet": "The generator's task is to approach G ref {\\displaystyle \\mu _{G}\\approx \\mu _{\\text{ref}}} , that is, to match its own output distribution as ...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Generative_adversarial_network", "content": "The generator's task is to approach G ref {\\displaystyle \\mu _{G}\\approx \\mu _{\\text{ref}}} , that is, to match its own output distribution as ..."}
+{"idx": 4, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "Oct 2, 2024 · In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.02025", "content": "Oct 2, 2024 · In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ..."}
+{"idx": 5, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "Conclusion This paper presents an innovative likelihood - based approach for distribution regression using conditional deep generative models . The key contributions are the principled formulation, efficient inference, and demonstrated improvements over existing methods in terms of predictive performance and uncertainty quantification.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/likelihood-based-approach-to-distribution-regression-using", "content": "Conclusion This paper presents an innovative likelihood - based approach for distribution regression using conditional deep generative models . The key contributions are the principled formulation, efficient inference, and demonstrated improvements over existing methods in terms of predictive performance and uncertainty quantification."}
+{"idx": 6, "title": "A LIKELIHOOD BASED APPROACH TO DISTRIBUTION REGRESSION USING ...", "date": "", "ddg_snippet": "In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the re-sponse variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=V6hhhXoTSq", "content": "In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the re-sponse variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ..."}
+{"idx": 7, "title": "ICML Poster A Likelihood Based Approach to Distribution ...", "date": "", "ddg_snippet": "In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46645", "content": "In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ..."}
+{"idx": 8, "title": "A Likelihood Approach to Nonparametric Estimation of a ... Conditional Diffusion Models are Minimax-Optimal and Manifold ... A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "We investigate statistical properties of a likelihood approach to nonparametric estimation of a singular distribution using deep generative models . More speci cally, a deep generative model is used to model high-dimensional data that are assumed to concentrate around some low-dimensional structure. Estimating the distribution supported on this low-... See full list on jmlr.org is the Hellinger convergence rate of the sieve MLE of p , and See full list on jmlr.org decreases as increases because becomes smoother while See full list on jmlr.org Our main theoretical results are given in this section. We rst present assumptions on the data-generating distribution P . Then, we derive the convergence rate of a sieve MLE for p with respect to the Hellinger distance in the deep generative model. We next obtain the convergence rate of the corresponding sieve MLE of Q under the Wasserstein distan... See full list on jmlr.org n where C = C(q; d; t; ; K; D; max; ; ). As one can see, the dimension d in the convergence rate of Corollary 4 is replaced by the intrinsic dimension t . If t is much smaller than d, the improvement from the structural assumption would be signi cant. See full list on jmlr.org In this section, we empirically demonstrate that the data perturbation method proposed in Section 3.4 plays an important role to improve the performance of a sieve MLE of deep generative models . In addition, we illustrate that deep generative models can detect low-dimensional structures well. Numerical studies are carried out by analyzing various s... See full list on jmlr.org Assume that the generator f = f is parametrized by . With a slight abuse of notation, let ; = pf ; , that is, Z ; (x) = See full list on jmlr.org The model is trained after perturbing the training data by an arti cial noise e For each data set, we consider various values of . e See full list on jmlr.org Abstract:In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating ... 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) of the response given predictors in the Hellinger (Wasserstein) metric.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume24/21-1099/21-1099.pdf", "content": "We investigate statistical properties of a likelihood approach to nonparametric estimation of a singular distribution using deep generative models . More speci cally, a deep generative model is used to model high-dimensional data that are assumed to concentrate around some low-dimensional structure. Estimating the distribution supported on this low-... See full list on jmlr.org is the Hellinger convergence rate of the sieve MLE of p , and See full list on jmlr.org decreases as increases because becomes smoother while See full list on jmlr.org Our main theoretical results are given in this section. We rst present assumptions on the data-generating distribution P . Then, we derive the convergence rate of a sieve MLE for p with respect to the Hellinger distance in the deep generative model. We next obtain the convergence rate of the corresponding sieve MLE of Q under the Wasserstein distan... See full list on jmlr.org n where C = C(q; d; t; ; K; D; max; ; ). As one can see, the dimension d in the convergence rate of Corollary 4 is replaced by the intrinsic dimension t . If t is much smaller than d, the improvement from the structural assumption would be signi cant. See full list on jmlr.org In this section, we empirically demonstrate that the data perturbation method proposed in Section 3.4 plays an important role to improve the performance of a sieve MLE of deep generative models . In addition, we illustrate that deep generative models can detect low-dimensional structures well. Numerical studies are carried out by analyzing various s... See full list on jmlr.org Assume that the generator f = f is parametrized by . With a slight abuse of notation, let ; = pf ; , that is, Z ; (x) = See full list on jmlr.org The model is trained after perturbing the training data by an arti cial noise e For each data set, we consider various values of . e See full list on jmlr.org Abstract:In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating ... 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) of the response given predictors in the Hellinger (Wasserstein) metric."}
+{"idx": 9, "title": "Conditional Diffusion Models are Minimax-Optimal and Manifold ...", "date": "", "ddg_snippet": "Abstract:In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating ...", "subpage_snippet": "", "source": "bohrium.dp.tech", "link": "https://bohrium.dp.tech/paper/arxiv/2409.20124", "content": "Abstract:In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating ..."}

data/sampled_jsons/Linear_convergence_Sinkhorn's_algorithm_generalized_static_Schrödinger_bridge_Theorem_2.7_tameness_c.jsonl

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+{"idx": 0, "title": "Linear convergence of Sinkhorn's algorithm for generalized ...", "date": "", "ddg_snippet": "1 May 2025 — This paper studies the generalized static Schrödinger bridge (SSB) problem, which extends the classical SSB by replacing the entropy divergence ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0hrkN07DuO&noteId=O4YQkrxppf", "content": "1 May 2025 — This paper studies the generalized static Schrödinger bridge (SSB) problem, which extends the classical SSB by replacing the entropy divergence ..."}
+{"idx": 1, "title": "Linear convergence of Sinkhorn's algorithm for generalized ...", "date": "", "ddg_snippet": "16 Jul 2025 — We establish Kantorovich duality and linear convergence of Sinkhorn's algorithm for the generalized SSB problem under mild conditions . Our ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46671", "content": "16 Jul 2025 — We establish Kantorovich duality and linear convergence of Sinkhorn's algorithm for the generalized SSB problem under mild conditions . Our ..."}
+{"idx": 2, "title": "Linear Convergence of Sinkhorn's Algorithm for Generalized ...", "date": "", "ddg_snippet": "Linear Convergence of Sinkhorn's Algorithm for. Generalized Static Schrödinger Bridge ... 21 ... condition for tameness for similar but more general cases.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/a644c39247d5073d97fae0bbd2c5b921800516ea.pdf", "content": "Linear Convergence of Sinkhorn's Algorithm for. Generalized Static Schrödinger Bridge ... 21 ... condition for tameness for similar but more general cases."}
+{"idx": 3, "title": "large random matrices with given margins", "date": "", "ddg_snippet": "ABSTRACT. We study large random matrices with i.i.d. entries conditioned to have prescribed row and column sums (margins), a problem connected to relative ...", "subpage_snippet": "", "source": "hanbaeklyu.com", "link": "https://hanbaeklyu.com/wp-content/uploads/2025/08/ct_limit.pdf", "content": "ABSTRACT. We study large random matrices with i.i.d. entries conditioned to have prescribed row and column sums (margins), a problem connected to relative ..."}
+{"idx": 4, "title": "Optimization Methods for Large-Scale Machine Learning", "date": "", "ddg_snippet": "This paper provides a review and commentary on the past, present, and future of numerical optimization algorithms in the context of machine learning ...", "subpage_snippet": "", "source": "epubs.siam.org", "link": "https://epubs.siam.org/doi/10.1137/16M1080173", "content": "This paper provides a review and commentary on the past, present, and future of numerical optimization algorithms in the context of machine learning ..."}
+{"idx": 5, "title": "Review of latest Score Based Generative Modeling papers.", "date": "", "ddg_snippet": "On the Contraction Coefficient of the Schrödinger Bridge for Stochastic Linear Systems. September 12, 2023 Alexis M. H. Teter, Yongxin Chen, Abhishek Halder.", "subpage_snippet": "", "source": "scorebasedgenerativemodeling.github.io", "link": "https://scorebasedgenerativemodeling.github.io/", "content": "On the Contraction Coefficient of the Schrödinger Bridge for Stochastic Linear Systems. September 12, 2023 Alexis M. H. Teter, Yongxin Chen, Abhishek Halder."}
+{"idx": 6, "title": "Mathematics Oct 2023", "date": "", "ddg_snippet": "Title: On Linear Convergence of PI Consensus Algorithm under the Restricted Secant Inequality. Kushal Chakrabarti, Mayank Baranwal. Comments: Accepted for ...", "subpage_snippet": "", "source": "web3.arxiv.org", "link": "https://web3.arxiv.org/list/math/2023-10?skip=25&show=2000", "content": "Title: On Linear Convergence of PI Consensus Algorithm under the Restricted Secant Inequality. Kushal Chakrabarti, Mayank Baranwal. Comments: Accepted for ..."}
+{"idx": 7, "title": "Optimal Transport and Deep Learning - Kilian Fatras", "date": "", "ddg_snippet": "25 Nov 2021 — Ce manuscrit contient tous les travaux de ma thèse qui ont été réalisés de Novembre 2018 à Février 2021.", "subpage_snippet": "", "source": "kilianfatras.github.io", "link": "https://kilianfatras.github.io/pdf/thesis_kf.pdf", "content": "25 Nov 2021 — Ce manuscrit contient tous les travaux de ma thèse qui ont été réalisés de Novembre 2018 à Février 2021."}
+{"idx": 8, "title": "Mathematics Sep 2023", "date": "", "ddg_snippet": "Comments: In this revised version, all typographical errors have been meticulously corrected, enhancing clarity and precision.", "subpage_snippet": "", "source": "arxiv.org", "link": "http://arxiv.org/list/math/2023-09?skip=1050&show=2000", "content": "Comments: In this revised version, all typographical errors have been meticulously corrected, enhancing clarity and precision."}
+{"idx": 9, "title": "Track: Poster Session 2", "date": "", "ddg_snippet": "24 Apr 2025 — This paper addresses these challenges by introducing a novel data augmentation strategy that separately augments observed action sequences and next actions.", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2025/session/31972", "content": "24 Apr 2025 — This paper addresses these challenges by introducing a novel data augmentation strategy that separately augments observed action sequences and next actions."}

data/sampled_jsons/Longpre_2021_EMNLP_entity-based_knowledge_conflicts_NQ-Swap_abstract.jsonl

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+{"idx": 0, "title": "Entity-Based Knowledge Conflicts in Question Answering", "date": "", "ddg_snippet": "by S Longpre · 2021 · Cited by 290 — Entity - based Substitutions Key to our evalua- tion framework is substituting entity names with other plausible entity names. Entity based swap -.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2021.emnlp-main.565.pdf", "content": "by S Longpre · 2021 · Cited by 290 — Entity - based Substitutions Key to our evalua- tion framework is substituting entity names with other plausible entity names. Entity based swap -."}
+{"idx": 1, "title": "Taming Knowledge Conflicts in Language Models", "date": "", "ddg_snippet": "6 Jun 2025 — (2021) Longpre, S., Perisetla, K., Chen, A., Ramesh, N., DuBois, C., and Singh, S. Entity-based knowledge conflicts in question answering .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.10996v2", "content": "6 Jun 2025 — (2021) Longpre, S., Perisetla, K., Chen, A., Ramesh, N., DuBois, C., and Singh, S. Entity-based knowledge conflicts in question answering ."}
+{"idx": 2, "title": "Interweaving Conflicting Knowledge and Reasoning Skills ...", "date": "", "ddg_snippet": "For example, NQ -Swaq requires LLMs to extract conflicting entities from the provided document without solely referring to their parametric knowledge directly ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2404.03577v1", "content": "For example, NQ -Swaq requires LLMs to extract conflicting entities from the provided document without solely referring to their parametric knowledge directly ..."}
+{"idx": 3, "title": "ADACAD: Adaptively Decoding to Balance Conflicts ...", "date": "", "ddg_snippet": "by H Wang · 2025 · Cited by 16 — NQ-SWAP (Longpre et al., 2021 ) introduces synthetic conflicts by swapping entities in the context to challenge the model's ability to manage ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.naacl-long.581.pdf", "content": "by H Wang · 2025 · Cited by 16 — NQ-SWAP (Longpre et al., 2021 ) introduces synthetic conflicts by swapping entities in the context to challenge the model's ability to manage ..."}
+{"idx": 4, "title": "Exploiting Contextual Knowledge in LLMs through V- ...", "date": "", "ddg_snippet": "Nikhil Ramesh, Chris DuBois, and Sameer Singh. 718. 2021 . Entity - based knowledge conflicts in question ... NQ - Swap NQ - Swap is based on the NQ dataset,. 1072.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=B3i76OuS4d", "content": "Nikhil Ramesh, Chris DuBois, and Sameer Singh. 718. 2021 . Entity - based knowledge conflicts in question ... NQ - Swap NQ - Swap is based on the NQ dataset,. 1072."}
+{"idx": 5, "title": "Taming Knowledge Conflicts in Language Models", "date": "", "ddg_snippet": "Abstract . Language Models (LMs) often encounter knowledge conflicts when parametric memory contradicts contextual knowledge ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46677", "content": "Abstract . Language Models (LMs) often encounter knowledge conflicts when parametric memory contradicts contextual knowledge ..."}
+{"idx": 6, "title": "Paper - EMNLP 2023", "date": "", "ddg_snippet": "6 Dec 2023 — I am happy to welcome you to EMNLP -2023 in Singapore! Like EMNLP - 2021 , EMNLP -2022, and other. ACL-related meetings, we decided to host ...", "subpage_snippet": "", "source": "2023.emnlp.org", "link": "https://2023.emnlp.org/downloads/EMNLP-2023-Handbook-Nov-30.pdf", "content": "6 Dec 2023 — I am happy to welcome you to EMNLP -2023 in Singapore! Like EMNLP - 2021 , EMNLP -2022, and other. ACL-related meetings, we decided to host ..."}
+{"idx": 7, "title": "Analysing the Residual Stream of Language Models Under ...", "date": "", "ddg_snippet": "We present the knowledge conflict probing results on Macnoise, NQSwap , ConflictQA using Llama2-. 7B in Figure 4, Figure 5 and Figure 6. The results match the ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/33fc952b58cab08008bc207991f5af7d0d3123a8.pdf", "content": "We present the knowledge conflict probing results on Macnoise, NQSwap , ConflictQA using Llama2-. 7B in Figure 4, Figure 5 and Figure 6. The results match the ..."}
+{"idx": 8, "title": "Fewer Truncations Improve Language Modeling", "date": "", "ddg_snippet": "by H Ding · 2024 · Cited by 33 — Specifically, we evaluate with 5-shot on NQ - Swap ( Longpre et al., 2021 ) ... Entity - based knowledge conflicts in question answering. In Proceedings of ...", "subpage_snippet": "", "source": "assets.amazon.science", "link": "https://assets.amazon.science/be/1e/215dde844d49a13136e70d683d8b/fewer-truncations-improve-language-modeling.pdf", "content": "by H Ding · 2024 · Cited by 33 — Specifically, we evaluate with 5-shot on NQ - Swap ( Longpre et al., 2021 ) ... Entity - based knowledge conflicts in question answering. In Proceedings of ..."}
+{"idx": 9, "title": "Factuality and Large Language Models", "date": "", "ddg_snippet": "by A Chen · 2023 · Cited by 5 — The text in this chapter is based on the publications: • Entity - Based Knowledge Conflicts in Question Answering [97] ( EMNLP 2021 ). The results presented in ...", "subpage_snippet": "", "source": "escholarship.org", "link": "https://escholarship.org/content/qt7542q1d9/qt7542q1d9_noSplash_f1a1efa5375a76a01f6dde7fe8322d5b.pdf", "content": "by A Chen · 2023 · Cited by 5 — The text in this chapter is based on the publications: • Entity - Based Knowledge Conflicts in Question Answering [97] ( EMNLP 2021 ). The results presented in ..."}

data/sampled_jsons/MSVD_frames_sampled_Video-ColBERT_sitearxiv.org_OR_sitethecvf.com.jsonl

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+{"idx": 0, "title": "Contextualized Late Interaction for Text-to-Video Retrieval", "date": "", "ddg_snippet": "24 Mar 2025 — ... MSVD and VATEX, while using 64 frames for DiDeMo and ActivityNet. ... Number of Sampled Frames . Report issue for preceding element. # of Frames ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.19009v1", "content": "24 Mar 2025 — ... MSVD and VATEX, while using 64 frames for DiDeMo and ActivityNet. ... Number of Sampled Frames . Report issue for preceding element. # of Frames ..."}
+{"idx": 1, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}

data/sampled_jsons/Machine_Learning_meets_Algebraic_Combinatorics_Schubert_polynomials_spurious_correlation_length.jsonl

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+{"idx": 0, "title": "Machine - Wikipedia", "date": "", "ddg_snippet": "A machine is a thermodynamic system that uses power to apply forces and control movement to perform an action. The term is commonly applied to artificial devices, such as those employing engines or motors, but also to natural biological macromolecules, such as molecular machines .", "subpage_snippet": "", "source": "en.m.wikipedia.org", "link": "https://en.m.wikipedia.org/wiki/Machine", "content": "A machine is a thermodynamic system that uses power to apply forces and control movement to perform an action. The term is commonly applied to artificial devices, such as those employing engines or motors, but also to natural biological macromolecules, such as molecular machines ."}
+{"idx": 1, "title": "MACHINE Definition & Meaning | Dictionary .com", "date": "", "ddg_snippet": "Machine definition: an apparatus consisting of interrelated parts with separate functions, used in the performance of some kind of work.. See examples of MACHINE used in a sentence.", "subpage_snippet": "", "source": "www.dictionary.com", "link": "https://www.dictionary.com/browse/machine", "content": "Machine definition: an apparatus consisting of interrelated parts with separate functions, used in the performance of some kind of work.. See examples of MACHINE used in a sentence."}
+{"idx": 2, "title": "MACHINE Definition & Meaning - Merriam-Webster", "date": "", "ddg_snippet": "The meaning of MACHINE is a mechanically, electrically, or electronically operated device for performing a task. How to use machine in a sentence.", "subpage_snippet": "", "source": "www.merriam-webster.com", "link": "https://www.merriam-webster.com/dictionary/machine", "content": "The meaning of MACHINE is a mechanically, electrically, or electronically operated device for performing a task. How to use machine in a sentence."}
+{"idx": 3, "title": "Machine | Definition, Mechanisms & Efficiency | Britannica", "date": "", "ddg_snippet": "machine , device, having a unique purpose, that augments or replaces human or animal effort for the accomplishment of physical tasks.", "subpage_snippet": "", "source": "www.britannica.com", "link": "https://www.britannica.com/technology/machine", "content": "machine , device, having a unique purpose, that augments or replaces human or animal effort for the accomplishment of physical tasks."}
+{"idx": 4, "title": "MACHINE | English meaning - Cambridge Dictionary", "date": "", "ddg_snippet": "MACHINE definition: 1. a piece of equipment with several moving parts that uses power to do a particular type of work…. Learn more.", "subpage_snippet": "", "source": "dictionary.cambridge.org", "link": "https://dictionary.cambridge.org/dictionary/english/machine", "content": "MACHINE definition: 1. a piece of equipment with several moving parts that uses power to do a particular type of work…. Learn more."}
+{"idx": 5, "title": "Machine - definition of machine by The Free Dictionary", "date": "", "ddg_snippet": "Of, relating to, or felt to resemble a machine : machine repairs; machine politics.", "subpage_snippet": "", "source": "www.thefreedictionary.com", "link": "https://www.thefreedictionary.com/machine", "content": "Of, relating to, or felt to resemble a machine : machine repairs; machine politics."}
+{"idx": 6, "title": "What Is A Machine ? Its Types and How it Works - Mech Lesson", "date": "", "ddg_snippet": "A machine is a mechanical device that uses power to apply force and control motion to perform work efficiently . Machines range from simple tools like pulleys and levers to complex systems like engines, robots, and manufacturing equipment.", "subpage_snippet": "", "source": "mechlesson.com", "link": "https://mechlesson.com/machine/", "content": "A machine is a mechanical device that uses power to apply force and control motion to perform work efficiently . Machines range from simple tools like pulleys and levers to complex systems like engines, robots, and manufacturing equipment."}
+{"idx": 7, "title": "What is a Machine ? - Computer Hope", "date": "", "ddg_snippet": "Jun 1, 2025 · A machine is a device with several parts that work together to perform a task. A machine can augment or replace the efforts required by an animal or human to make it easier to complete a task. For example, a car is a complex machine that transports humans and other things.", "subpage_snippet": "", "source": "www.computerhope.com", "link": "https://www.computerhope.com/jargon/m/machine.htm", "content": "Jun 1, 2025 · A machine is a device with several parts that work together to perform a task. A machine can augment or replace the efforts required by an animal or human to make it easier to complete a task. For example, a car is a complex machine that transports humans and other things."}
+{"idx": 8, "title": "Machine - New World Encyclopedia", "date": "", "ddg_snippet": "Modern power tools, automated machine tools, and human-operated power machinery are tools that are also machines . Machines used to transform heat or other energy into mechanical energy are known as engines.", "subpage_snippet": "", "source": "www.newworldencyclopedia.org", "link": "https://www.newworldencyclopedia.org/entry/Machine", "content": "Modern power tools, automated machine tools, and human-operated power machinery are tools that are also machines . Machines used to transform heat or other energy into mechanical energy are known as engines."}
+{"idx": 9, "title": "What is Machine ? – An Essential Guide", "date": "", "ddg_snippet": "The machine is a device that has a unique purpose, that augments or replaces human or animal effort for the accomplishment of physical tasks.", "subpage_snippet": "", "source": "www.theengineeringchoice.com", "link": "https://www.theengineeringchoice.com/what-is-machine/", "content": "The machine is a device that has a unique purpose, that augments or replaces human or animal effort for the accomplishment of physical tasks."}