arxiv_id string | pwc_url string | status int64 | found bool | pwc_id string | title string | url_abs string | repositories list | project_pages list | hf_models list | hf_datasets list | hf_spaces list |
|---|---|---|---|---|---|---|---|---|---|---|---|
2506.07085 | https://paperswithcode.co/api/v1/papers/arxiv/2506.07085?include_resources=true | 200 | true | 87137 | State Entropy Regularization for Robust Reinforcement Learning | https://arxiv.org/abs/2506.07085 | [] | [] | [] | [] | [] |
2511.17378 | https://paperswithcode.co/api/v1/papers/arxiv/2511.17378?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2402.15751 | https://paperswithcode.co/api/v1/papers/arxiv/2402.15751?include_resources=true | 200 | true | 27925 | Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning | https://arxiv.org/abs/2402.15751 | [] | [] | [] | [] | [] |
2503.01739 | https://paperswithcode.co/api/v1/papers/arxiv/2503.01739?include_resources=true | 200 | true | 45350 | VideoUFO: A Million-Scale User-Focused Dataset for Text-to-Video Generation | https://arxiv.org/abs/2503.01739v2 | [
{
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"owner": "WangWenhao0716",
"name": "BenchUFO",
"stars": 4,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2506.11849 | https://paperswithcode.co/api/v1/papers/arxiv/2506.11849?include_resources=true | 200 | true | 85878 | Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values | https://arxiv.org/abs/2506.11849 | [] | [] | [] | [] | [] |
2506.01213 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01213?include_resources=true | 200 | true | 87187 | On the Stability of Graph Convolutional Neural Networks: a Probabilistic Perspective | https://arxiv.org/abs/2506.01213 | [] | [] | [] | [] | [] |
2511.01169 | https://paperswithcode.co/api/v1/papers/arxiv/2511.01169?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2504.10097 | https://paperswithcode.co/api/v1/papers/arxiv/2504.10097?include_resources=true | 200 | true | 73518 | STaRFormer: Semi-Supervised Task-Informed Representation Learning via Dynamic Attention-Based Regional Masking for Sequential Data | https://arxiv.org/abs/2504.10097 | [] | [] | [] | [] | [] |
2502.09969 | https://paperswithcode.co/api/v1/papers/arxiv/2502.09969?include_resources=true | 200 | true | 44185 | Data Valuation using Neural Networks for Efficient Instruction Fine-Tuning | https://arxiv.org/abs/2502.09969 | [
{
"url": "https://github.com/agarwalishika/nn-cift",
"owner": "agarwalishika",
"name": "NN-CIFT",
"stars": 6,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2405.07914 | https://paperswithcode.co/api/v1/papers/arxiv/2405.07914?include_resources=true | 200 | true | 86262 | Distribution Learning Meets Graph Structure Sampling | https://arxiv.org/abs/2405.07914 | [] | [] | [] | [] | [] |
2510.18824 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18824?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2410.06019 | https://paperswithcode.co/api/v1/papers/arxiv/2410.06019?include_resources=true | 200 | true | 86081 | Unveiling Transformer Perception by Exploring Input Manifolds | https://arxiv.org/abs/2410.06019 | [] | [] | [] | [] | [] |
2505.13344 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13344?include_resources=true | 200 | true | 49052 | RoPECraft: Training-Free Motion Transfer with Trajectory-Guided RoPE Optimization on Diffusion Transformers | https://arxiv.org/abs/2505.13344 | [
{
"url": "https://github.com/berkegokmen1/ropecraft",
"owner": "berkegokmen1",
"name": "RoPECraft",
"stars": 47,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://berkegokmen1.github.io/RoPECraft/",
"is_official": true
},
{
"url": "https://berkegokmen1.github.io/RoPECraft",
"is_official": true
}
] | [] | [] | [] |
2501.16312 | https://paperswithcode.co/api/v1/papers/arxiv/2501.16312?include_resources=true | 200 | true | 86224 | LinPrim: Linear Primitives for Differentiable Volumetric Rendering | https://arxiv.org/abs/2501.16312 | [] | [] | [] | [] | [] |
2505.05522 | https://paperswithcode.co/api/v1/papers/arxiv/2505.05522?include_resources=true | 200 | true | 48548 | Continuous Thought Machines | https://arxiv.org/abs/2505.05522v2 | [
{
"url": "https://github.com/sakanaai/continuous-thought-machines",
"owner": "SakanaAI",
"name": "continuous-thought-machines",
"stars": 1642,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://pub.sakana.ai/ctm/",
"is_official": true
}
] | [] | [] | [] |
2410.20445 | https://paperswithcode.co/api/v1/papers/arxiv/2410.20445?include_resources=true | 200 | true | 86378 | TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration | https://arxiv.org/abs/2410.20445 | [] | [] | [] | [] | [] |
2409.03817 | https://paperswithcode.co/api/v1/papers/arxiv/2409.03817?include_resources=true | 200 | true | 85975 | Neural Entropy | https://arxiv.org/abs/2409.03817 | [] | [] | [] | [] | [] |
2510.12119 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12119?include_resources=true | 200 | true | 87113 | ImageSentinel: Protecting Visual Datasets from Unauthorized Retrieval-Augmented Image Generation | https://arxiv.org/abs/2510.12119 | [
{
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"owner": "luo-ziyuan",
"name": "imagesentinel",
"stars": 3,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2505.18752 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18752?include_resources=true | 200 | true | 87315 | Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning | https://arxiv.org/abs/2505.18752 | [] | [] | [] | [] | [] |
2510.17545 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17545?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.08132 | https://paperswithcode.co/api/v1/papers/arxiv/2510.08132?include_resources=true | 200 | true | 66732 | Approximate Domain Unlearning for Vision-Language Models | https://arxiv.org/abs/2510.08132 | [
{
"url": "https://github.com/kodaikawamura/domain-unlearning",
"owner": "kodaikawamura",
"name": "domain-unlearning",
"stars": 0,
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"source": "hf_api"
}
] | [
{
"url": "https://kodaikawamura.github.io/Domain_Unlearning/",
"is_official": true
}
] | [] | [] | [] |
2504.02433 | https://paperswithcode.co/api/v1/papers/arxiv/2504.02433?include_resources=true | 200 | true | 47223 | OmniTalker: Real-Time Text-Driven Talking Head Generation with In-Context Audio-Visual Style Replication | https://arxiv.org/abs/2504.02433 | [] | [] | [] | [] | [] |
2505.19850 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19850?include_resources=true | 200 | true | 85841 | DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning | https://arxiv.org/abs/2505.19850 | [] | [] | [] | [] | [] |
2505.19297 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19297?include_resources=true | 200 | true | 49716 | Alchemist: Turning Public Text-to-Image Data into Generative Gold | https://arxiv.org/abs/2505.19297 | [] | [
{
"url": "https://huggingface.co/datasets/yandex/alchemist",
"is_official": true
}
] | [] | [] | [] |
2507.00814 | https://paperswithcode.co/api/v1/papers/arxiv/2507.00814?include_resources=true | 200 | true | 86664 | Many LLMs Are More Utilitarian Than One | https://arxiv.org/abs/2507.00814 | [] | [] | [] | [] | [] |
2510.23285 | https://paperswithcode.co/api/v1/papers/arxiv/2510.23285?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.05238 | https://paperswithcode.co/api/v1/papers/arxiv/2507.05238?include_resources=true | 200 | true | 86599 | Bridging Expressivity and Scalability with Adaptive Unitary SSMs | https://arxiv.org/abs/2507.05238 | [] | [] | [] | [] | [] |
2506.20100 | https://paperswithcode.co/api/v1/papers/arxiv/2506.20100?include_resources=true | 200 | true | 71731 | MIRAGE: A Benchmark for Multimodal Information-Seeking and Reasoning in
Agricultural Expert-Guided Conversations | https://arxiv.org/abs/2506.20100 | [
{
"url": "https://github.com/MIRAGE-Benchmark/MIRAGE-Benchmark",
"owner": "MIRAGE-Benchmark",
"name": "MIRAGE-Benchmark",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://mirage-benchmark.github.io/",
"is_official": true
}
] | [] | [] | [] |
2506.15838 | https://paperswithcode.co/api/v1/papers/arxiv/2506.15838?include_resources=true | 200 | true | 71957 | EchoShot: Multi-Shot Portrait Video Generation | https://arxiv.org/abs/2506.15838 | [] | [] | [] | [] | [] |
2509.17429 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17429?include_resources=true | 200 | true | 85837 | Multi-scale Temporal Prediction via Incremental Generation and Multi-agent Collaboration | https://arxiv.org/abs/2509.17429 | [] | [] | [] | [] | [] |
2506.14087 | https://paperswithcode.co/api/v1/papers/arxiv/2506.14087?include_resources=true | 200 | true | 86359 | Multi-Scale Finetuning for Encoder-based Time Series Foundation Models | https://arxiv.org/abs/2506.14087 | [
{
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"owner": "zqiao11",
"name": "msft",
"stars": 17,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2601.10124 | https://paperswithcode.co/api/v1/papers/arxiv/2601.10124?include_resources=true | 200 | true | 55347 | VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentation | https://arxiv.org/abs/2601.10124 | [
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"url": "https://github.com/script-Yang/VQ-Seg",
"owner": "script-Yang",
"name": "VQ-Seg",
"stars": 13,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://github.com/script-Yang/VQ-Seg",
"is_official": true
}
] | [] | [] | [] |
2511.06094 | https://paperswithcode.co/api/v1/papers/arxiv/2511.06094?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.21998 | https://paperswithcode.co/api/v1/papers/arxiv/2511.21998?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.06938 | https://paperswithcode.co/api/v1/papers/arxiv/2509.06938?include_resources=true | 200 | true | 52698 | From Noise to Narrative: Tracing the Origins of Hallucinations in Transformers | https://arxiv.org/abs/2509.06938 | [] | [] | [] | [] | [] |
2511.00885 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00885?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.15178 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15178?include_resources=true | 200 | true | 52866 | Unleashing the Potential of Multimodal LLMs for Zero-Shot
Spatio-Temporal Video Grounding | https://arxiv.org/abs/2509.15178 | [
{
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"owner": "zaiquanyang",
"name": "LLaVA_Next_STVG",
"stars": 15,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2509.23639 | https://paperswithcode.co/api/v1/papers/arxiv/2509.23639?include_resources=true | 200 | true | 85916 | LightFair: Towards an Efficient Alternative for Fair T2I Diffusion via Debiasing Pre-trained Text Encoders | https://arxiv.org/abs/2509.23639 | [
{
"url": "https://github.com/boyuh/lightfair",
"owner": "boyuh",
"name": "lightfair",
"stars": 7,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2503.09271 | https://paperswithcode.co/api/v1/papers/arxiv/2503.09271?include_resources=true | 200 | true | 87172 | DitHub: A Modular Framework for Incremental Open-Vocabulary Object Detection | https://arxiv.org/abs/2503.09271 | [] | [
{
"url": "https://aimagelab.github.io/DitHub/",
"is_official": true
}
] | [] | [] | [] |
2408.12798 | https://paperswithcode.co/api/v1/papers/arxiv/2408.12798?include_resources=true | 200 | true | 36163 | BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks and Defenses on Large Language Models | https://arxiv.org/abs/2408.12798v2 | [
{
"url": "https://github.com/bboylyg/backdoorllm",
"owner": "bboylyg",
"name": "backdoorllm",
"stars": 258,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2503.18430 | https://paperswithcode.co/api/v1/papers/arxiv/2503.18430?include_resources=true | 200 | true | 46629 | CQ-DINO: Mitigating Gradient Dilution via Category Queries for Vast Vocabulary Object Detection | https://arxiv.org/abs/2503.18430v3 | [
{
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"owner": "RedAIGC",
"name": "CQ-DINO",
"stars": 8,
"is_official": true,
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] | [] | [] | [] | [] |
2509.16549 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16549?include_resources=true | 200 | true | 86734 | Efficient Rectified Flow for Image Fusion | https://arxiv.org/abs/2509.16549 | [
{
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"owner": "zirui0625",
"name": "rffusion",
"stars": 25,
"is_official": true,
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}
] | [] | [] | [] | [] |
2505.16993 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16993?include_resources=true | 200 | true | 86331 | Native Segmentation Vision Transformers | https://arxiv.org/abs/2505.16993 | [] | [
{
"url": "https://research.nvidia.com/labs/dvl/projects/native-segmentation/",
"is_official": true
}
] | [] | [] | [] |
2505.11210 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11210?include_resources=true | 200 | true | 86727 | Minimizing False-Positive Attributions in Explanations of Non-Linear Models | https://arxiv.org/abs/2505.11210 | [] | [] | [] | [] | [] |
2509.15791 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15791?include_resources=true | 200 | true | 86219 | Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization | https://arxiv.org/abs/2509.15791 | [] | [] | [] | [] | [] |
2509.26240 | https://paperswithcode.co/api/v1/papers/arxiv/2509.26240?include_resources=true | 200 | true | 85924 | A Single-Loop Gradient Algorithm for Pessimistic Bilevel Optimization via Smooth Approximation | https://arxiv.org/abs/2509.26240 | [] | [] | [] | [] | [] |
2511.02123 | https://paperswithcode.co/api/v1/papers/arxiv/2511.02123?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.13563 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13563?include_resources=true | 200 | true | 86108 | Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression | https://arxiv.org/abs/2505.13563 | [
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"stars": 11,
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] | [] | [] | [] | [] |
2510.27432 | https://paperswithcode.co/api/v1/papers/arxiv/2510.27432?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.11293 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11293?include_resources=true | 200 | true | 48853 | Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch Mining | https://arxiv.org/abs/2505.11293 | [
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"owner": "raghavlite",
"name": "b3",
"stars": 35,
"is_official": true,
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] | [] | [] | [] | [] |
2505.20411 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20411?include_resources=true | 200 | true | 49877 | SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents | https://arxiv.org/abs/2505.20411 | [
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"owner": "swe-rebench",
"name": "swe-bench-fork",
"stars": 13,
"is_official": true,
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] | [
{
"url": "https://swe-rebench.com",
"is_official": true
}
] | [] | [] | [] |
2505.13438 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13438?include_resources=true | 200 | true | 49067 | Optimizing Anytime Reasoning via Budget Relative Policy Optimization | https://arxiv.org/abs/2505.13438 | [
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"owner": "sail-sg",
"name": "AnytimeReasoner",
"stars": 50,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2405.13846 | https://paperswithcode.co/api/v1/papers/arxiv/2405.13846?include_resources=true | 200 | true | 87347 | Regression Trees Know Calculus | https://arxiv.org/abs/2405.13846 | [] | [] | [] | [] | [] |
2505.14547 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14547?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.15152 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15152?include_resources=true | 200 | true | 86197 | Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation | https://arxiv.org/abs/2505.15152 | [] | [] | [] | [] | [] |
2504.13180 | https://paperswithcode.co/api/v1/papers/arxiv/2504.13180?include_resources=true | 200 | true | 47876 | PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding | https://arxiv.org/abs/2504.13180 | [
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"name": "perception_models",
"stars": 1940,
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"url": "https://ai.meta.com/research/publications/perceptionlm-open-access-data-and-models-for-detailed-visual-understanding/",
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{
"url": "https://ai.meta.com/blog/meta-fair-updates-perception-localization-reasoning/",
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] | [
"https://huggingface.co/models?other=arxiv:2504.13180"
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2511.21928 | https://paperswithcode.co/api/v1/papers/arxiv/2511.21928?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2501.19216 | https://paperswithcode.co/api/v1/papers/arxiv/2501.19216?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.21236 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21236?include_resources=true | 200 | true | 72646 | Breaking the Performance Ceiling in Complex Reinforcement Learning
requires Inference Strategies | https://arxiv.org/abs/2505.21236 | [] | [
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2502.04465 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04465?include_resources=true | 200 | true | 43793 | FocalCodec: Low-Bitrate Speech Coding via Focal Modulation Networks | https://arxiv.org/abs/2502.04465 | [
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"url": "https://lucadellalib.github.io/focalcodec-web/",
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2509.16546 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16546?include_resources=true | 200 | true | 86983 | Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks | https://arxiv.org/abs/2509.16546 | [] | [] | [] | [] | [] |
2512.10978 | https://paperswithcode.co/api/v1/papers/arxiv/2512.10978?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.09833 | https://paperswithcode.co/api/v1/papers/arxiv/2511.09833?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.16806 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16806?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.13227 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13227?include_resources=true | 200 | true | 49038 | Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis | https://arxiv.org/abs/2505.13227v2 | [
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"stars": 135,
"is_official": true,
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{
"url": "https://osworld-grounding.github.io",
"is_official": true
}
] | [] | [] | [] |
2507.04447 | https://paperswithcode.co/api/v1/papers/arxiv/2507.04447?include_resources=true | 200 | true | 51698 | DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge | https://arxiv.org/abs/2507.04447v2 | [
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"owner": "Zhangwenyao1",
"name": "DreamVLA",
"stars": 261,
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"url": "https://zhangwenyao1.github.io/DreamVLA/",
"is_official": true
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2506.02635 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02635?include_resources=true | 200 | true | 86339 | Efficient Quadratic Corrections for Frank-Wolfe Algorithms | https://arxiv.org/abs/2506.02635 | [] | [] | [] | [] | [] |
2506.03028 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03028?include_resources=true | 200 | true | 86014 | Protein Inverse Folding From Structure Feedback | https://arxiv.org/abs/2506.03028 | [] | [] | [] | [] | [] |
2509.01328 | https://paperswithcode.co/api/v1/papers/arxiv/2509.01328?include_resources=true | 200 | true | 68879 | Can Large Language Models Master Complex Card Games? | https://arxiv.org/abs/2509.01328 | [
{
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"owner": "THUDM",
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2603.15871 | https://paperswithcode.co/api/v1/papers/arxiv/2603.15871?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.19648 | https://paperswithcode.co/api/v1/papers/arxiv/2502.19648?include_resources=true | 200 | true | 87307 | Spectral Analysis of Representational Similarity with Limited Neurons | https://arxiv.org/abs/2502.19648 | [] | [] | [] | [] | [] |
2510.17700 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17700?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.09622 | https://paperswithcode.co/api/v1/papers/arxiv/2502.09622?include_resources=true | 200 | true | 44169 | Theoretical Benefit and Limitation of Diffusion Language Model | https://arxiv.org/abs/2502.09622 | [
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2506.17139 | https://paperswithcode.co/api/v1/papers/arxiv/2506.17139?include_resources=true | 200 | true | 71831 | Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based
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2505.01386 | https://paperswithcode.co/api/v1/papers/arxiv/2505.01386?include_resources=true | 200 | true | 87058 | Carbon Aware Transformers Through Joint Model-Hardware Optimization | https://arxiv.org/abs/2505.01386 | [] | [] | [] | [] | [] |
2506.20779 | https://paperswithcode.co/api/v1/papers/arxiv/2506.20779?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.05426 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05426?include_resources=true | 200 | true | 50667 | Mixture-of-Experts Meets In-Context Reinforcement Learning | https://arxiv.org/abs/2506.05426 | [
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2505.15927 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15927?include_resources=true | 200 | true | 72877 | CoT Information: Improved Sample Complexity under Chain-of-Thought
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2505.23864 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23864?include_resources=true | 200 | true | 86073 | Personalized Subgraph Federated Learning with Differentiable Auxiliary Projections | https://arxiv.org/abs/2505.23864 | [
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2510.00303 | https://paperswithcode.co/api/v1/papers/arxiv/2510.00303?include_resources=true | 200 | true | 87461 | Looking Beyond the Known: Towards a Data Discovery Guided Open-World Object Detection | https://arxiv.org/abs/2510.00303 | [] | [] | [] | [] | [] |
2506.15675 | https://paperswithcode.co/api/v1/papers/arxiv/2506.15675?include_resources=true | 200 | true | 51268 | Sekai: A Video Dataset towards World Exploration | https://arxiv.org/abs/2506.15675v2 | [
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2602.20729 | https://paperswithcode.co/api/v1/papers/arxiv/2602.20729?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.21431 | https://paperswithcode.co/api/v1/papers/arxiv/2510.21431?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.27481 | https://paperswithcode.co/api/v1/papers/arxiv/2510.27481?include_resources=true | 200 | true | 65576 | NAUTILUS: A Large Multimodal Model for Underwater Scene Understanding | https://arxiv.org/abs/2510.27481 | [
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2503.04598 | https://paperswithcode.co/api/v1/papers/arxiv/2503.04598?include_resources=true | 200 | true | 45550 | HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization | https://arxiv.org/abs/2503.04598v2 | [
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2505.11132 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11132?include_resources=true | 200 | true | 86058 | Fairness-aware Anomaly Detection via Fair Projection | https://arxiv.org/abs/2505.11132 | [] | [] | [] | [] | [] |
2510.27517 | https://paperswithcode.co/api/v1/papers/arxiv/2510.27517?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.00310 | https://paperswithcode.co/api/v1/papers/arxiv/2507.00310?include_resources=true | 200 | true | 85959 | Open-ended Scientific Discovery via Bayesian Surprise | https://arxiv.org/abs/2507.00310 | [] | [] | [] | [] | [] |
2506.17064 | https://paperswithcode.co/api/v1/papers/arxiv/2506.17064?include_resources=true | 200 | true | 86459 | Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings | https://arxiv.org/abs/2506.17064 | [] | [] | [] | [] | [] |
2510.00441 | https://paperswithcode.co/api/v1/papers/arxiv/2510.00441?include_resources=true | 200 | true | 87479 | Seeing through Uncertainty: Robust Task-Oriented Optimization in Visual Navigation | https://arxiv.org/abs/2510.00441 | [] | [] | [] | [] | [] |
2509.20911 | https://paperswithcode.co/api/v1/papers/arxiv/2509.20911?include_resources=true | 200 | true | 86523 | Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting | https://arxiv.org/abs/2509.20911 | [] | [] | [] | [] | [] |
2505.16916 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16916?include_resources=true | 200 | true | 49458 | Backdoor Cleaning without External Guidance in MLLM Fine-tuning | https://arxiv.org/abs/2505.16916 | [
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2506.10967 | https://paperswithcode.co/api/v1/papers/arxiv/2506.10967?include_resources=true | 200 | true | 86149 | Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs | https://arxiv.org/abs/2506.10967 | [
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2505.15544 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15544?include_resources=true | 200 | true | 86130 | A Temporal Difference Method for Stochastic Continuous Dynamics | https://arxiv.org/abs/2505.15544 | [] | [] | [] | [] | [] |
2507.12201 | https://paperswithcode.co/api/v1/papers/arxiv/2507.12201?include_resources=true | 200 | true | 87111 | RODS: Robust Optimization Inspired Diffusion Sampling for Detecting and Reducing Hallucination in Generative Models | https://arxiv.org/abs/2507.12201 | [] | [] | [] | [] | [] |
2502.04242 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04242?include_resources=true | 200 | true | 86439 | A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning | https://arxiv.org/abs/2502.04242 | [] | [] | [] | [] | [] |
2505.11774 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11774?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.16345 | https://paperswithcode.co/api/v1/papers/arxiv/2507.16345?include_resources=true | 200 | true | 87417 | The Cost of Compression: Tight Quadratic Black-Box Attacks on Sketches for $\ell_2$ Norm Estimation | https://arxiv.org/abs/2507.16345 | [] | [] | [] | [] | [] |
2510.12422 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12422?include_resources=true | 200 | true | 66438 | VideoLucy: Deep Memory Backtracking for Long Video Understanding | https://arxiv.org/abs/2510.12422 | [] | [
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2504.13161 | https://paperswithcode.co/api/v1/papers/arxiv/2504.13161?include_resources=true | 200 | true | 47869 | CLIMB: CLustering-based Iterative Data Mixture Bootstrapping for Language Model Pre-training | https://arxiv.org/abs/2504.13161 | [] | [
{
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