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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2504.06560 | https://paperswithcode.co/api/v1/papers/arxiv/2504.06560?include_resources=true | 200 | true | 86245 | NeedleInATable: Exploring Long-Context Capability of Large Language Models towards Long-Structured Tables | https://arxiv.org/abs/2504.06560 | [] | [] | [] | [] | [] |
2506.17220 | https://paperswithcode.co/api/v1/papers/arxiv/2506.17220?include_resources=true | 200 | true | 86044 | Emergent Temporal Correspondences from Video Diffusion Transformers | https://arxiv.org/abs/2506.17220 | [] | [] | [] | [] | [] |
2506.00359 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00359?include_resources=true | 200 | true | 87251 | Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy | https://arxiv.org/abs/2506.00359 | [] | [] | [] | [] | [] |
2501.18792 | https://paperswithcode.co/api/v1/papers/arxiv/2501.18792?include_resources=true | 200 | true | 86467 | Bayesian Optimization with Preference Exploration using a Monotonic Neural Network Ensemble | https://arxiv.org/abs/2501.18792 | [] | [] | [] | [] | [] |
2503.17352 | https://paperswithcode.co/api/v1/papers/arxiv/2503.17352?include_resources=true | 200 | true | 46551 | OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement | https://arxiv.org/abs/2503.17352 | [
{
"url": "https://github.com/yihedeng9/openvlthinker",
"owner": "yihedeng9",
"name": "OpenVLThinker",
"stars": 123,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://yihe-deng.notion.site/openvlthinker",
"is_official": true
}
] | [] | [] | [] |
2505.15210 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15210?include_resources=true | 200 | true | 49271 | Deliberation on Priors: Trustworthy Reasoning of Large Language Models on Knowledge Graphs | https://arxiv.org/abs/2505.15210 | [
{
"url": "https://github.com/reml-group/deliberation-on-priors",
"owner": "reml-group",
"name": "Deliberation-on-Priors",
"stars": 31,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2602.07674 | https://paperswithcode.co/api/v1/papers/arxiv/2602.07674?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.16368 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16368?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.12448 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12448?include_resources=true | 200 | true | 48960 | SSR: Enhancing Depth Perception in Vision-Language Models via Rationale-Guided Spatial Reasoning | https://arxiv.org/abs/2505.12448v2 | [
{
"url": "https://github.com/yliu-cs/ssr",
"owner": "yliu-cs",
"name": "SSR",
"stars": 34,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://yliu-cs.github.io/SSR/",
"is_official": true
}
] | [] | [] | [] |
2502.17533 | https://paperswithcode.co/api/v1/papers/arxiv/2502.17533?include_resources=true | 200 | true | 85951 | From Euler to AI: Unifying Formulas for Mathematical Constants | https://arxiv.org/abs/2502.17533 | [] | [] | [] | [] | [] |
2510.18053 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18053?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.21600 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21600?include_resources=true | 200 | true | 49967 | R2R: Efficiently Navigating Divergent Reasoning Paths with Small-Large Model Token Routing | https://arxiv.org/abs/2505.21600 | [
{
"url": "https://github.com/thu-nics/r2r",
"owner": "thu-nics",
"name": "R2R",
"stars": 69,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://fuvty.github.io/R2R_Project_Page/",
"is_official": true
}
] | [] | [] | [] |
2509.15817 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15817?include_resources=true | 200 | true | 86052 | Escaping saddle points without Lipschitz smoothness: the power of nonlinear preconditioning | https://arxiv.org/abs/2509.15817 | [] | [] | [] | [] | [] |
2411.16315 | https://paperswithcode.co/api/v1/papers/arxiv/2411.16315?include_resources=true | 200 | true | 85784 | Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables | https://arxiv.org/abs/2411.16315 | [] | [] | [] | [] | [] |
2506.02177 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02177?include_resources=true | 200 | true | 72361 | Act Only When It Pays: Efficient Reinforcement Learning for LLM
Reasoning via Selective Rollouts | https://arxiv.org/abs/2506.02177 | [] | [] | [] | [] | [] |
2506.23589 | https://paperswithcode.co/api/v1/papers/arxiv/2506.23589?include_resources=true | 200 | true | 71623 | Transition Matching: Scalable and Flexible Generative Modeling | https://arxiv.org/abs/2506.23589 | [] | [] | [] | [] | [] |
2601.10901 | https://paperswithcode.co/api/v1/papers/arxiv/2601.10901?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.01430 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01430?include_resources=true | 200 | true | 72426 | DNAEdit: Direct Noise Alignment for Text-Guided Rectified Flow Editing | https://arxiv.org/abs/2506.01430 | [] | [] | [] | [] | [] |
2502.04780 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04780?include_resources=true | 200 | true | 43823 | SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning | https://arxiv.org/abs/2502.04780 | [
{
"url": "https://github.com/zou-group/sirius",
"owner": "zou-group",
"name": "sirius",
"stars": 86,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2510.13445 | https://paperswithcode.co/api/v1/papers/arxiv/2510.13445?include_resources=true | 200 | true | 85871 | Robust Minimax Boosting with Performance Guarantees | https://arxiv.org/abs/2510.13445 | [] | [] | [] | [] | [] |
2506.05341 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05341?include_resources=true | 200 | true | 50658 | Direct Numerical Layout Generation for 3D Indoor Scene Synthesis via Spatial Reasoning | https://arxiv.org/abs/2506.05341 | [] | [
{
"url": "https://directlayout.github.io/",
"is_official": true
}
] | [] | [] | [] |
2509.01720 | https://paperswithcode.co/api/v1/papers/arxiv/2509.01720?include_resources=true | 200 | true | 87445 | Succeed or Learn Slowly: Sample Efficient Off-Policy Reinforcement Learning for Mobile App Control | https://arxiv.org/abs/2509.01720 | [] | [] | [] | [] | [] |
2405.12895 | https://paperswithcode.co/api/v1/papers/arxiv/2405.12895?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.02473 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02473?include_resources=true | 200 | true | 87146 | Generative Perception of Shape and Material from Differential Motion | https://arxiv.org/abs/2506.02473 | [] | [] | [] | [] | [] |
2511.00637 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00637?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.21512 | https://paperswithcode.co/api/v1/papers/arxiv/2510.21512?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.24000 | https://paperswithcode.co/api/v1/papers/arxiv/2506.24000?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.16814 | https://paperswithcode.co/api/v1/papers/arxiv/2507.16814?include_resources=true | 200 | true | 52039 | Semi-off-Policy Reinforcement Learning for Vision-Language Slow-thinking Reasoning | https://arxiv.org/abs/2507.16814 | [] | [] | [] | [] | [] |
2502.07760 | https://paperswithcode.co/api/v1/papers/arxiv/2502.07760?include_resources=true | 200 | true | 44051 | Scalable Fingerprinting of Large Language Models | https://arxiv.org/abs/2502.07760 | [
{
"url": "https://github.com/sewoonglab/scalable-fingerprinting-of-llms",
"owner": "SewoongLab",
"name": "scalable-fingerprinting-of-llms",
"stars": 2,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2503.12880 | https://paperswithcode.co/api/v1/papers/arxiv/2503.12880?include_resources=true | 200 | true | 46229 | nvBench 2.0: A Benchmark for Natural Language to Visualization under Ambiguity | https://arxiv.org/abs/2503.12880 | [] | [
{
"url": "https://nvbench2.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.09664 | https://paperswithcode.co/api/v1/papers/arxiv/2505.09664?include_resources=true | 200 | true | 86635 | KINDLE: Knowledge-Guided Distillation for Prior-Free Gene Regulatory Network Inference | https://arxiv.org/abs/2505.09664 | [] | [] | [] | [] | [] |
2505.18600 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18600?include_resources=true | 200 | true | 49629 | Chain-of-Zoom: Extreme Super-Resolution via Scale Autoregression and Preference Alignment | https://arxiv.org/abs/2505.18600v2 | [
{
"url": "https://github.com/bryanswkim/chain-of-zoom",
"owner": "bryanswkim",
"name": "Chain-of-Zoom",
"stars": 744,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://bryanswkim.github.io/chain-of-zoom/",
"is_official": true
}
] | [] | [] | [] |
2505.19645 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19645?include_resources=true | 200 | true | 86540 | MoESD: Unveil Speculative Decoding's Potential for Accelerating Sparse MoE | https://arxiv.org/abs/2505.19645 | [] | [] | [] | [] | [] |
2505.13934 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13934?include_resources=true | 200 | true | 49109 | RLVR-World: Training World Models with Reinforcement Learning | https://arxiv.org/abs/2505.13934 | [
{
"url": "https://github.com/thuml/rlvr-world",
"owner": "thuml",
"name": "RLVR-World",
"stars": 169,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://thuml.github.io/RLVR-World",
"is_official": true
}
] | [] | [] | [] |
2506.04283 | https://paperswithcode.co/api/v1/papers/arxiv/2506.04283?include_resources=true | 200 | true | 86248 | SSIMBaD: Sigma Scaling with SSIM-Guided Balanced Diffusion for AnimeFace Colorization | https://arxiv.org/abs/2506.04283 | [] | [] | [] | [] | [] |
2407.21243 | https://paperswithcode.co/api/v1/papers/arxiv/2407.21243?include_resources=true | 200 | true | 86369 | Informed Correctors for Discrete Diffusion Models | https://arxiv.org/abs/2407.21243 | [
{
"url": "https://github.com/lindermanlab/informed-correctors",
"owner": "lindermanlab",
"name": "informed-correctors",
"stars": 2,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2506.09518 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09518?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.17847 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17847?include_resources=true | 200 | true | 86163 | Semantic and Visual Crop-Guided Diffusion Models for Heterogeneous Tissue Synthesis in Histopathology | https://arxiv.org/abs/2509.17847 | [] | [] | [] | [] | [] |
2406.09264 | https://paperswithcode.co/api/v1/papers/arxiv/2406.09264?include_resources=true | 200 | true | 32872 | Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions | https://arxiv.org/abs/2406.09264v3 | [
{
"url": "https://github.com/huashen218/bidirectional-human-ai-alignment",
"owner": "huashen218",
"name": "bidirectional-human-ai-alignment",
"stars": 47,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2508.21468 | https://paperswithcode.co/api/v1/papers/arxiv/2508.21468?include_resources=true | 200 | true | 85758 | Controllable 3D Molecular Generation for Structure-Based Drug Design Through Bayesian Flow Networks and Gradient Integration | https://arxiv.org/abs/2508.21468 | [] | [] | [] | [] | [] |
2502.11018 | https://paperswithcode.co/api/v1/papers/arxiv/2502.11018?include_resources=true | 200 | true | 44268 | GRIFFIN: Effective Token Alignment for Faster Speculative Decoding | https://arxiv.org/abs/2502.11018 | [
{
"url": "https://github.com/hsj576/griffin",
"owner": "hsj576",
"name": "GRIFFIN",
"stars": 18,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2505.14214 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14214?include_resources=true | 200 | true | 87236 | Regularized least squares learning with heavy-tailed noise is minimax optimal | https://arxiv.org/abs/2505.14214 | [] | [] | [] | [] | [] |
2505.23811 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23811?include_resources=true | 200 | true | 86274 | LayerIF: Estimating Layer Quality for Large Language Models using Influence Functions | https://arxiv.org/abs/2505.23811 | [] | [] | [] | [] | [] |
2505.21724 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21724?include_resources=true | 200 | true | 49973 | OmniResponse: Online Multimodal Conversational Response Generation in Dyadic Interactions | https://arxiv.org/abs/2505.21724 | [
{
"url": "https://github.com/awakening-ai/OmniResponse",
"owner": "awakening-ai",
"name": "OmniResponse",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://omniresponse.github.io/",
"is_official": true
}
] | [] | [] | [] |
2506.02672 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02672?include_resources=true | 200 | true | 72340 | EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving | https://arxiv.org/abs/2506.02672 | [] | [] | [] | [] | [] |
2506.16054 | https://paperswithcode.co/api/v1/papers/arxiv/2506.16054?include_resources=true | 200 | true | 51284 | PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models | https://arxiv.org/abs/2506.16054 | [] | [
{
"url": "https://a-suozhang.xyz/paroattn.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.16716 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16716?include_resources=true | 200 | true | 49437 | The Computational Complexity of Counting Linear Regions in ReLU Neural Networks | https://arxiv.org/abs/2505.16716 | [] | [] | [] | [] | [] |
2511.03263 | https://paperswithcode.co/api/v1/papers/arxiv/2511.03263?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.18531 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18531?include_resources=true | 200 | true | 85731 | Learning Principles from Multi-modal Human Preference | https://arxiv.org/abs/2505.18531 | [] | [
{
"url": "https://generative-rlhf-v.github.io/",
"is_official": true
}
] | [] | [] | [] |
2509.18208 | https://paperswithcode.co/api/v1/papers/arxiv/2509.18208?include_resources=true | 200 | true | 86036 | Variational Task Vector Composition | https://arxiv.org/abs/2509.18208 | [] | [] | [] | [] | [] |
2509.18094 | https://paperswithcode.co/api/v1/papers/arxiv/2509.18094?include_resources=true | 200 | true | 52912 | UniPixel: Unified Object Referring and Segmentation for Pixel-Level
Visual Reasoning | https://arxiv.org/abs/2509.18094 | [
{
"url": "https://github.com/polyu-chenlab/unipixel",
"owner": "PolyU-ChenLab",
"name": "UniPixel",
"stars": 214,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://polyu-chenlab.github.io/unipixel",
"is_official": true
}
] | [] | [] | [] |
2503.23793 | https://paperswithcode.co/api/v1/papers/arxiv/2503.23793?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.10425 | https://paperswithcode.co/api/v1/papers/arxiv/2505.10425?include_resources=true | 200 | true | 86282 | Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs | https://arxiv.org/abs/2505.10425 | [] | [] | [] | [] | [] |
2507.07400 | https://paperswithcode.co/api/v1/papers/arxiv/2507.07400?include_resources=true | 200 | true | 86806 | KVFlow: Efficient Prefix Caching for Accelerating LLM-based Multi-Agent Workflows | https://arxiv.org/abs/2507.07400 | [] | [] | [] | [] | [] |
2508.12787 | https://paperswithcode.co/api/v1/papers/arxiv/2508.12787?include_resources=true | 200 | true | 86933 | Wavy Transformer | https://arxiv.org/abs/2508.12787 | [] | [] | [] | [] | [] |
2411.04975 | https://paperswithcode.co/api/v1/papers/arxiv/2411.04975?include_resources=true | 200 | true | 75842 | SuffixDecoding: Extreme Speculative Decoding for Emerging AI Applications | https://arxiv.org/abs/2411.04975 | [
{
"url": "https://github.com/snowflakedb/arcticinference",
"owner": "snowflakedb",
"name": "arcticinference",
"stars": 270,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://suffix-decoding.github.io",
"is_official": true
}
] | [] | [] | [] |
2506.03278 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03278?include_resources=true | 200 | true | 50507 | FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes | https://arxiv.org/abs/2506.03278 | [
{
"url": "https://github.com/ibm/failuresensoriq",
"owner": "IBM",
"name": "FailureSensorIQ",
"stars": 30,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.01917 | https://paperswithcode.co/api/v1/papers/arxiv/2505.01917?include_resources=true | 200 | true | 86159 | Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling | https://arxiv.org/abs/2505.01917 | [] | [] | [] | [] | [] |
2505.13197 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13197?include_resources=true | 200 | true | 86007 | Inferring stochastic dynamics with growth from cross-sectional data | https://arxiv.org/abs/2505.13197 | [] | [] | [] | [] | [] |
2506.01347 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01347?include_resources=true | 200 | true | 50379 | The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning | https://arxiv.org/abs/2506.01347 | [
{
"url": "https://github.com/tianhongzxy/rlvr-decomposed",
"owner": "TianHongZXY",
"name": "RLVR-Decomposed",
"stars": 142,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2411.13112 | https://paperswithcode.co/api/v1/papers/arxiv/2411.13112?include_resources=true | 200 | true | 75752 | SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models | https://arxiv.org/abs/2411.13112 | [] | [] | [] | [] | [] |
2505.19406 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19406?include_resources=true | 200 | true | 86263 | Unveiling the Compositional Ability Gap in Vision-Language Reasoning Model | https://arxiv.org/abs/2505.19406 | [] | [] | [] | [] | [] |
2510.17313 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17313?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2410.07746 | https://paperswithcode.co/api/v1/papers/arxiv/2410.07746?include_resources=true | 200 | true | 86446 | Benign Overfitting in Single-Head Attention | https://arxiv.org/abs/2410.07746 | [] | [] | [] | [] | [] |
2503.09501 | https://paperswithcode.co/api/v1/papers/arxiv/2503.09501?include_resources=true | 200 | true | 45973 | ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning | https://arxiv.org/abs/2503.09501v3 | [
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"owner": "ziyuwan",
"name": "ReMA-public",
"stars": 61,
"is_official": true,
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}
] | [] | [] | [] | [] |
2305.08813 | https://paperswithcode.co/api/v1/papers/arxiv/2305.08813?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.15450 | https://paperswithcode.co/api/v1/papers/arxiv/2503.15450?include_resources=true | 200 | true | 46397 | SkyLadder: Better and Faster Pretraining via Context Window Scheduling | https://arxiv.org/abs/2503.15450 | [
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"owner": "sail-sg",
"name": "SkyLadder",
"stars": 41,
"is_official": true,
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] | [] | [] | [] | [] |
2509.19271 | https://paperswithcode.co/api/v1/papers/arxiv/2509.19271?include_resources=true | 200 | true | 67922 | WolBanking77: Wolof Banking Speech Intent Classification Dataset | https://arxiv.org/abs/2509.19271 | [
{
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"owner": "abdoukarim",
"name": "wolbanking77",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2511.07378 | https://paperswithcode.co/api/v1/papers/arxiv/2511.07378?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.17004 | https://paperswithcode.co/api/v1/papers/arxiv/2505.17004?include_resources=true | 200 | true | 49480 | Guided Diffusion Sampling on Function Spaces with Applications to PDEs | https://arxiv.org/abs/2505.17004 | [
{
"url": "https://github.com/neuraloperator/fundps",
"owner": "neuraloperator",
"name": "FunDPS",
"stars": 33,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2603.18157 | https://paperswithcode.co/api/v1/papers/arxiv/2603.18157?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.24627 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24627?include_resources=true | 200 | true | 87424 | Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees | https://arxiv.org/abs/2505.24627 | [] | [] | [] | [] | [] |
2505.01912 | https://paperswithcode.co/api/v1/papers/arxiv/2505.01912?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.16640 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16640?include_resources=true | 200 | true | 49427 | BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization | https://arxiv.org/abs/2505.16640 | [] | [
{
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{
"url": "https://badvla-project.github.io/.",
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2507.09846 | https://paperswithcode.co/api/v1/papers/arxiv/2507.09846?include_resources=true | 200 | true | 86235 | Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training | https://arxiv.org/abs/2507.09846 | [] | [] | [] | [] | [] |
2506.10805 | https://paperswithcode.co/api/v1/papers/arxiv/2506.10805?include_resources=true | 200 | true | 72036 | Detecting High-Stakes Interactions with Activation Probes | https://arxiv.org/abs/2506.10805 | [] | [] | [] | [] | [] |
2411.05348 | https://paperswithcode.co/api/v1/papers/arxiv/2411.05348?include_resources=true | 200 | true | 39788 | LLM-PySC2: Starcraft II learning environment for Large Language Models | https://arxiv.org/abs/2411.05348 | [
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2502.09324 | https://paperswithcode.co/api/v1/papers/arxiv/2502.09324?include_resources=true | 200 | true | 85977 | Depth-Bounds for Neural Networks via the Braid Arrangement | https://arxiv.org/abs/2502.09324 | [] | [] | [] | [] | [] |
2507.11688 | https://paperswithcode.co/api/v1/papers/arxiv/2507.11688?include_resources=true | 200 | true | 87325 | Composing Linear Layers from Irreducibles | https://arxiv.org/abs/2507.11688 | [] | [] | [] | [] | [] |
2503.03923 | https://paperswithcode.co/api/v1/papers/arxiv/2503.03923?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.09395 | https://paperswithcode.co/api/v1/papers/arxiv/2503.09395?include_resources=true | 200 | true | 87128 | Adjusted Count Quantification Learning on Graphs | https://arxiv.org/abs/2503.09395 | [] | [] | [] | [] | [] |
2505.22566 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22566?include_resources=true | 200 | true | 86131 | Universal Visuo-Tactile Video Understanding for Embodied Interaction | https://arxiv.org/abs/2505.22566 | [] | [] | [] | [] | [] |
2503.17538 | https://paperswithcode.co/api/v1/papers/arxiv/2503.17538?include_resources=true | 200 | true | 46566 | A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics | https://arxiv.org/abs/2503.17538 | [] | [] | [] | [] | [] |
2512.03247 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03247?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.19858 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19858?include_resources=true | 200 | true | 72709 | A Unified Solution to Video Fusion: From Multi-Frame Learning to
Benchmarking | https://arxiv.org/abs/2505.19858 | [
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2505.15811 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15811?include_resources=true | 200 | true | 85808 | On the creation of narrow AI: hierarchy and nonlocality of neural network skills | https://arxiv.org/abs/2505.15811 | [] | [] | [] | [] | [] |
2511.06310 | https://paperswithcode.co/api/v1/papers/arxiv/2511.06310?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.21817 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21817?include_resources=true | 200 | true | 86525 | ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation | https://arxiv.org/abs/2505.21817 | [] | [] | [] | [] | [] |
2506.02846 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02846?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.20612 | https://paperswithcode.co/api/v1/papers/arxiv/2509.20612?include_resources=true | 200 | true | 85787 | Policy Compatible Skill Incremental Learning via Lazy Learning Interface | https://arxiv.org/abs/2509.20612 | [] | [] | [] | [] | [] |
2506.04626 | https://paperswithcode.co/api/v1/papers/arxiv/2506.04626?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.18118 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18118?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.20446 | https://paperswithcode.co/api/v1/papers/arxiv/2511.20446?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.19911 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19911?include_resources=true | 200 | true | 87154 | Attention! You Vision Language Model Could Be Maliciously Manipulated | https://arxiv.org/abs/2505.19911 | [] | [] | [] | [] | [] |
2509.16500 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16500?include_resources=true | 200 | true | 68098 | RLGF: Reinforcement Learning with Geometric Feedback for Autonomous
Driving Video Generation | https://arxiv.org/abs/2509.16500 | [] | [] | [] | [] | [] |
2506.05198 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05198?include_resources=true | 200 | true | 86226 | Quantifying Cross-Modality Memorization in Vision-Language Models | https://arxiv.org/abs/2506.05198 | [] | [] | [] | [] | [] |
2506.02162 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02162?include_resources=true | 200 | true | 87419 | Asymptotically exact variational flows via involutive MCMC kernels | https://arxiv.org/abs/2506.02162 | [] | [] | [] | [] | [] |
2506.00885 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00885?include_resources=true | 200 | true | 50342 | CoVoMix2: Advancing Zero-Shot Dialogue Generation with Fully Non-Autoregressive Flow Matching | https://arxiv.org/abs/2506.00885 | [] | [] | [] | [] | [] |
2510.16675 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16675?include_resources=true | 200 | true | 66206 | Infinite Neural Operators: Gaussian processes on functions | https://arxiv.org/abs/2510.16675 | [] | [] | [] | [] | [] |
2505.23566 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23566?include_resources=true | 200 | true | 50118 | Uni-MuMER: Unified Multi-Task Fine-Tuning of Vision-Language Model for Handwritten Mathematical Expression Recognition | https://arxiv.org/abs/2505.23566 | [
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