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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2511.08846 | https://paperswithcode.co/api/v1/papers/arxiv/2511.08846?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.22411 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22411?include_resources=true | 200 | true | 85918 | Mitigating Overthinking in Large Reasoning Models via Manifold Steering | https://arxiv.org/abs/2505.22411 | [
{
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"owner": "aries-iai",
"name": "manifold_steering",
"stars": 15,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2506.07458 | https://paperswithcode.co/api/v1/papers/arxiv/2506.07458?include_resources=true | 200 | true | 72145 | KScope: A Framework for Characterizing the Knowledge Status of Language
Models | https://arxiv.org/abs/2506.07458 | [] | [] | [] | [] | [] |
2510.08010 | https://paperswithcode.co/api/v1/papers/arxiv/2510.08010?include_resources=true | 200 | true | 86780 | Accelerated Evolving Set Processes for Local PageRank Computation | https://arxiv.org/abs/2510.08010 | [] | [] | [] | [] | [] |
2506.00993 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00993?include_resources=true | 200 | true | 50352 | FlexSelect: Flexible Token Selection for Efficient Long Video Understanding | https://arxiv.org/abs/2506.00993 | [
{
"url": "https://github.com/yunzhuzhang0918/flexselect",
"owner": "yunzhuzhang0918",
"name": "flexselect",
"stars": 23,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://yunzhuzhang0918.github.io/flex_select/",
"is_official": true
}
] | [] | [] | [] |
2505.23883 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23883?include_resources=true | 200 | true | 50178 | BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning | https://arxiv.org/abs/2505.23883 | [
{
"url": "https://github.com/imageomics/treeoflife-toolbox",
"owner": "imageomics",
"name": "treeoflife-toolbox",
"stars": 2,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://imageomics.github.io/bioclip-2/",
"is_official": true
}
] | [] | [] | [] |
2505.21097 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21097?include_resources=true | 200 | true | 49922 | Thinker: Learning to Think Fast and Slow | https://arxiv.org/abs/2505.21097 | [] | [] | [] | [] | [] |
2503.06677 | https://paperswithcode.co/api/v1/papers/arxiv/2503.06677?include_resources=true | 200 | true | 74205 | REArtGS: Reconstructing and Generating Articulated Objects via 3D
Gaussian Splatting with Geometric and Motion Constraints | https://arxiv.org/abs/2503.06677 | [
{
"url": "https://github.com/wd-ustc-cs/REArtGS",
"owner": "wd-ustc-cs",
"name": "REArtGS",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://sites.google.com/view/reartgs/home",
"is_official": true
}
] | [] | [] | [] |
2506.03237 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03237?include_resources=true | 200 | true | 72316 | UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection | https://arxiv.org/abs/2506.03237 | [
{
"url": "https://github.com/quanlin-wu/unisite",
"owner": "quanlin-wu",
"name": "unisite",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2410.02890 | https://paperswithcode.co/api/v1/papers/arxiv/2410.02890?include_resources=true | 200 | true | 86315 | Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach | https://arxiv.org/abs/2410.02890 | [] | [] | [] | [] | [] |
2505.19386 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19386?include_resources=true | 200 | true | 49727 | Force Prompting: Video Generation Models Can Learn and Generalize Physics-based Control Signals | https://arxiv.org/abs/2505.19386 | [
{
"url": "https://github.com/brown-palm/force-prompting",
"owner": "brown-palm",
"name": "force-prompting",
"stars": 138,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://force-prompting.github.io/",
"is_official": true
}
] | [] | [] | [] |
2506.03642 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03642?include_resources=true | 200 | true | 86370 | Spatial Understanding from Videos: Structured Prompts Meet Simulation Data | https://arxiv.org/abs/2506.03642 | [] | [] | [] | [] | [] |
2509.01426 | https://paperswithcode.co/api/v1/papers/arxiv/2509.01426?include_resources=true | 200 | true | 87345 | DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases | https://arxiv.org/abs/2509.01426 | [
{
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"owner": "ncclab-sustech",
"name": "dca",
"stars": 14,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2506.14852 | https://paperswithcode.co/api/v1/papers/arxiv/2506.14852?include_resources=true | 200 | true | 51245 | Cost-Efficient Serving of LLM Agents via Test-Time Plan Caching | https://arxiv.org/abs/2506.14852 | [] | [] | [] | [] | [] |
2505.20347 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20347?include_resources=true | 200 | true | 49873 | SeRL: Self-Play Reinforcement Learning for Large Language Models with Limited Data | https://arxiv.org/abs/2505.20347 | [
{
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"owner": "wantbook-book",
"name": "SeRL",
"stars": 17,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2511.00977 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00977?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.11458 | https://paperswithcode.co/api/v1/papers/arxiv/2512.11458?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2411.08706 | https://paperswithcode.co/api/v1/papers/arxiv/2411.08706?include_resources=true | 200 | true | 39966 | Searching Latent Program Spaces | https://arxiv.org/abs/2411.08706 | [
{
"url": "https://github.com/clement-bonnet/lpn",
"owner": "clement-bonnet",
"name": "lpn",
"stars": 106,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2504.06792 | https://paperswithcode.co/api/v1/papers/arxiv/2504.06792?include_resources=true | 200 | true | 73609 | Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations | https://arxiv.org/abs/2504.06792 | [
{
"url": "https://github.com/RUCAIBox/EASYEP",
"owner": "RUCAIBox",
"name": "EASYEP",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2511.00124 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00124?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2504.00711 | https://paperswithcode.co/api/v1/papers/arxiv/2504.00711?include_resources=true | 200 | true | 47113 | GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments | https://arxiv.org/abs/2504.00711v2 | [] | [] | [] | [] | [] |
2505.13732 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13732?include_resources=true | 200 | true | 86521 | Backward Conformal Prediction | https://arxiv.org/abs/2505.13732 | [] | [] | [] | [] | [] |
2505.14489 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14489?include_resources=true | 200 | true | 49185 | Reasoning Models Better Express Their Confidence | https://arxiv.org/abs/2505.14489 | [
{
"url": "https://github.com/mattyoon/reasoning-models-confidence",
"owner": "MattYoon",
"name": "reasoning-models-confidence",
"stars": 21,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2512.09513 | https://paperswithcode.co/api/v1/papers/arxiv/2512.09513?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.00371 | https://paperswithcode.co/api/v1/papers/arxiv/2512.00371?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.19732 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19732?include_resources=true | 200 | true | 66026 | Memo: Training Memory-Efficient Embodied Agents with Reinforcement Learning | https://arxiv.org/abs/2510.19732 | [
{
"url": "https://github.com/gunshi/memo",
"owner": "gunshi",
"name": "memo",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2506.02336 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02336?include_resources=true | 200 | true | 86905 | Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression | https://arxiv.org/abs/2506.02336 | [] | [] | [] | [] | [] |
2506.00781 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00781?include_resources=true | 200 | true | 72461 | CoP: Agentic Red-teaming for Large Language Models using Composition of
Principles | https://arxiv.org/abs/2506.00781 | [] | [] | [] | [] | [] |
2507.10348 | https://paperswithcode.co/api/v1/papers/arxiv/2507.10348?include_resources=true | 200 | true | 86848 | Feature Distillation is the Better Choice for Model-Heterogeneous Federated Learning | https://arxiv.org/abs/2507.10348 | [] | [] | [] | [] | [] |
2506.16962 | https://paperswithcode.co/api/v1/papers/arxiv/2506.16962?include_resources=true | 200 | true | 51310 | Enhancing Step-by-Step and Verifiable Medical Reasoning in MLLMs | https://arxiv.org/abs/2506.16962 | [
{
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"owner": "manglu097",
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"stars": 71,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2511.05510 | https://paperswithcode.co/api/v1/papers/arxiv/2511.05510?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.04245 | https://paperswithcode.co/api/v1/papers/arxiv/2506.04245?include_resources=true | 200 | true | 50575 | Contextual Integrity in LLMs via Reasoning and Reinforcement Learning | https://arxiv.org/abs/2506.04245 | [
{
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"owner": "EricGLan",
"name": "CI-RL",
"stars": 0,
"is_official": true,
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}
] | [] | [] | [] | [] |
2506.13558 | https://paperswithcode.co/api/v1/papers/arxiv/2506.13558?include_resources=true | 200 | true | 71948 | X-Scene: Large-Scale Driving Scene Generation with High Fidelity and
Flexible Controllability | https://arxiv.org/abs/2506.13558 | [] | [] | [] | [] | [] |
2510.04910 | https://paperswithcode.co/api/v1/papers/arxiv/2510.04910?include_resources=true | 200 | true | 53355 | Glocal Information Bottleneck for Time Series Imputation | https://arxiv.org/abs/2510.04910 | [
{
"url": "https://github.com/muyiiiii/neurips-25-glocal-ib",
"owner": "Muyiiiii",
"name": "NeurIPS-25-Glocal-IB",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2506.20879 | https://paperswithcode.co/api/v1/papers/arxiv/2506.20879?include_resources=true | 200 | true | 71720 | MultiHuman-Testbench: Benchmarking Image Generation for Multiple Humans | https://arxiv.org/abs/2506.20879 | [
{
"url": "https://github.com/Qualcomm-AI-research/MultiHuman-Testbench",
"owner": "Qualcomm-AI-research",
"name": "MultiHuman-Testbench",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2510.17348 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17348?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.15059 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15059?include_resources=true | 200 | true | 87211 | Restricted Spectral Gap Decomposition for Simulated Tempering Targeting Mixture Distributions | https://arxiv.org/abs/2505.15059 | [] | [] | [] | [] | [] |
2509.08104 | https://paperswithcode.co/api/v1/papers/arxiv/2509.08104?include_resources=true | 200 | true | 85866 | APML: Adaptive Probabilistic Matching Loss for Robust 3D Point Cloud Reconstruction | https://arxiv.org/abs/2509.08104 | [
{
"url": "https://github.com/apm-loss/apml",
"owner": "apm-loss",
"name": "apml",
"stars": 9,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2605.14137 | https://paperswithcode.co/api/v1/papers/arxiv/2605.14137?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.05495 | https://paperswithcode.co/api/v1/papers/arxiv/2505.05495?include_resources=true | 200 | true | 86621 | Learning 3D Persistent Embodied World Models | https://arxiv.org/abs/2505.05495 | [] | [] | [] | [] | [] |
2506.11928 | https://paperswithcode.co/api/v1/papers/arxiv/2506.11928?include_resources=true | 200 | true | 51086 | LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming? | https://arxiv.org/abs/2506.11928 | [
{
"url": "https://github.com/GavinZhengOI/LiveCodeBench-Pro",
"owner": "GavinZhengOI",
"name": "LiveCodeBench-Pro",
"stars": 159,
"is_official": true,
"source": "ai_extraction"
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] | [
{
"url": "https://livecodebenchpro.com/",
"is_official": true
}
] | [] | [] | [] |
2505.13858 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13858?include_resources=true | 200 | true | 86304 | Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules | https://arxiv.org/abs/2505.13858 | [] | [] | [] | [] | [] |
2510.19487 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19487?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.11274 | https://paperswithcode.co/api/v1/papers/arxiv/2507.11274?include_resources=true | 200 | true | 86737 | Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime | https://arxiv.org/abs/2507.11274 | [] | [] | [] | [] | [] |
2506.01582 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01582?include_resources=true | 200 | true | 86069 | Bayes optimal learning of attention-indexed models | https://arxiv.org/abs/2506.01582 | [] | [] | [] | [] | [] |
2506.05579 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05579?include_resources=true | 200 | true | 50675 | When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration | https://arxiv.org/abs/2506.05579v2 | [] | [
{
"url": "https://kite-live.vercel.app",
"is_official": true
}
] | [] | [] | [] |
2511.22121 | https://paperswithcode.co/api/v1/papers/arxiv/2511.22121?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.19678 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19678?include_resources=true | 200 | true | 87263 | Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs | https://arxiv.org/abs/2505.19678 | [] | [] | [] | [] | [] |
2502.06309 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06309?include_resources=true | 200 | true | 86743 | Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions | https://arxiv.org/abs/2502.06309 | [] | [] | [] | [] | [] |
2511.03187 | https://paperswithcode.co/api/v1/papers/arxiv/2511.03187?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.03335 | https://paperswithcode.co/api/v1/papers/arxiv/2505.03335?include_resources=true | 200 | true | 48442 | Absolute Zero: Reinforced Self-play Reasoning with Zero Data | https://arxiv.org/abs/2505.03335v2 | [
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{
"url": "https://github.com/leaplabthu/absolute-zero-reasoner",
"owner": "LeapLabTHU",
"name": "Absolute-Zero-Reasoner",
"... | [
{
"url": "https://andrewzh112.github.io/absolute-zero-reasoner/",
"is_official": true
}
] | [] | [] | [] |
2509.17276 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17276?include_resources=true | 200 | true | 86214 | Probabilistic Token Alignment for Large Language Model Fusion | https://arxiv.org/abs/2509.17276 | [] | [
{
"url": "https://runjia.tech/neurips_pta-llm/",
"is_official": true
}
] | [] | [] | [] |
2502.00466 | https://paperswithcode.co/api/v1/papers/arxiv/2502.00466?include_resources=true | 200 | true | 75001 | EDELINE: Enhancing Memory in Diffusion-based World Models via
Linear-Time Sequence Modeling | https://arxiv.org/abs/2502.00466 | [] | [] | [] | [] | [] |
2510.13307 | https://paperswithcode.co/api/v1/papers/arxiv/2510.13307?include_resources=true | 200 | true | 86696 | Novel Class Discovery for Point Cloud Segmentation via Joint Learning of Causal Representation and Reasoning | https://arxiv.org/abs/2510.13307 | [] | [] | [] | [] | [] |
2510.01532 | https://paperswithcode.co/api/v1/papers/arxiv/2510.01532?include_resources=true | 200 | true | 86834 | MATCH: Multi-faceted Adaptive Topo-Consistency for Semi-Supervised Histopathology Segmentation | https://arxiv.org/abs/2510.01532 | [
{
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"owner": "melon-xu",
"name": "match",
"stars": 4,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2512.03210 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03210?include_resources=true | 200 | true | 64190 | Flux4D: Flow-based Unsupervised 4D Reconstruction | https://arxiv.org/abs/2512.03210 | [] | [
{
"url": "https://waabi.ai/flux4d",
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}
] | [] | [] | [] |
2507.01001 | https://paperswithcode.co/api/v1/papers/arxiv/2507.01001?include_resources=true | 200 | true | 51615 | SciArena: An Open Evaluation Platform for Foundation Models in Scientific Literature Tasks | https://arxiv.org/abs/2507.01001 | [
{
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"owner": "yale-nlp",
"name": "SciArena",
"stars": 55,
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"url": "https://sciarena.allen.ai/",
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2512.03571 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03571?include_resources=true | 200 | true | 64173 | EnCompass: Enhancing Agent Programming with Search Over Program Execution Paths | https://arxiv.org/abs/2512.03571 | [] | [] | [] | [] | [] |
2411.10707 | https://paperswithcode.co/api/v1/papers/arxiv/2411.10707?include_resources=true | 200 | true | 86340 | Differentiable extensions with rounding guarantees for combinatorial optimization over permutations | https://arxiv.org/abs/2411.10707 | [] | [] | [] | [] | [] |
2505.11081 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11081?include_resources=true | 200 | true | 48831 | ShiQ: Bringing back Bellman to LLMs | https://arxiv.org/abs/2505.11081 | [] | [] | [] | [] | [] |
2505.20268 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20268?include_resources=true | 200 | true | 86901 | Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits | https://arxiv.org/abs/2505.20268 | [] | [] | [] | [] | [] |
2510.13660 | https://paperswithcode.co/api/v1/papers/arxiv/2510.13660?include_resources=true | 200 | true | 87110 | OmniGaze: Reward-inspired Generalizable Gaze Estimation In The Wild | https://arxiv.org/abs/2510.13660 | [] | [] | [] | [] | [] |
2505.11792 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11792?include_resources=true | 200 | true | 48896 | Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling | https://arxiv.org/abs/2505.11792 | [
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2506.09990 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09990?include_resources=true | 200 | true | 50969 | Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation | https://arxiv.org/abs/2506.09990 | [] | [
{
"url": "https://chain-of-action.github.io",
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2509.22010 | https://paperswithcode.co/api/v1/papers/arxiv/2509.22010?include_resources=true | 200 | true | 86050 | CoFFT: Chain of Foresight-Focus Thought for Visual Language Models | https://arxiv.org/abs/2509.22010 | [] | [] | [] | [] | [] |
2502.01051 | https://paperswithcode.co/api/v1/papers/arxiv/2502.01051?include_resources=true | 200 | true | 43540 | Diffusion Model as a Noise-Aware Latent Reward Model for Step-Level Preference Optimization | https://arxiv.org/abs/2502.01051v3 | [
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"url": "https://github.com/kwai-kolors/lpo",
"owner": "Kwai-Kolors",
"name": "LPO",
"stars": 57,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.22094 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22094?include_resources=true | 200 | true | 49995 | ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning | https://arxiv.org/abs/2505.22094v5 | [
{
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"owner": "ReinFlow",
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"stars": 207,
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] | [
{
"url": "https://reinflow.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.21577 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21577?include_resources=true | 200 | true | 49964 | RepoMaster: Autonomous Exploration and Understanding of GitHub Repositories for Complex Task Solving | https://arxiv.org/abs/2505.21577v2 | [
{
"url": "https://github.com/quantaalpha/repomaster",
"owner": "QuantaAlpha",
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{
"url": "https://github.com/wanghuacan/repomaster",
"owner": "wanghuacan",
"name": "repomaster",
"stars": 0... | [
{
"url": "https://quantaalpha.github.io",
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2509.16965 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16965?include_resources=true | 200 | true | 85956 | Preference Distillation via Value based Reinforcement Learning | https://arxiv.org/abs/2509.16965 | [] | [] | [] | [] | [] |
2506.11151 | https://paperswithcode.co/api/v1/papers/arxiv/2506.11151?include_resources=true | 200 | true | 86213 | Self-Calibrating BCIs: Ranking and Recovery of Mental Targets Without Labels | https://arxiv.org/abs/2506.11151 | [] | [] | [] | [] | [] |
2505.14359 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14359?include_resources=true | 200 | true | 72932 | Dual Data Alignment Makes AI-Generated Image Detector Easier
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2505.18427 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18427?include_resources=true | 200 | true | 85923 | Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm | https://arxiv.org/abs/2505.18427 | [] | [] | [] | [] | [] |
2502.11806 | https://paperswithcode.co/api/v1/papers/arxiv/2502.11806?include_resources=true | 200 | true | 87450 | Exploring Translation Mechanism of Large Language Models | https://arxiv.org/abs/2502.11806 | [] | [] | [] | [] | [] |
2505.10272 | https://paperswithcode.co/api/v1/papers/arxiv/2505.10272?include_resources=true | 200 | true | 86139 | Spike-timing-dependent Hebbian learning as noisy gradient descent | https://arxiv.org/abs/2505.10272 | [] | [] | [] | [] | [] |
2506.01374 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01374?include_resources=true | 200 | true | 86433 | Compiler Optimization via LLM Reasoning for Efficient Model Serving | https://arxiv.org/abs/2506.01374 | [] | [] | [] | [] | [] |
2512.19649 | https://paperswithcode.co/api/v1/papers/arxiv/2512.19649?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2508.13070 | https://paperswithcode.co/api/v1/papers/arxiv/2508.13070?include_resources=true | 200 | true | 86070 | Reinforced Context Order Recovery for Adaptive Reasoning and Planning | https://arxiv.org/abs/2508.13070 | [] | [] | [] | [] | [] |
2503.09799 | https://paperswithcode.co/api/v1/papers/arxiv/2503.09799?include_resources=true | 200 | true | 46002 | Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo | https://arxiv.org/abs/2503.09799 | [
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2508.15051 | https://paperswithcode.co/api/v1/papers/arxiv/2508.15051?include_resources=true | 200 | true | 87020 | Robust Estimation Under Heterogeneous Corruption Rates | https://arxiv.org/abs/2508.15051 | [] | [] | [] | [] | [] |
2412.03906 | https://paperswithcode.co/api/v1/papers/arxiv/2412.03906?include_resources=true | 200 | true | 86377 | Final-Model-Only Data Attribution with a Unifying View of Gradient-Based Methods | https://arxiv.org/abs/2412.03906 | [] | [] | [] | [] | [] |
2506.04088 | https://paperswithcode.co/api/v1/papers/arxiv/2506.04088?include_resources=true | 200 | true | 50551 | Multimodal Tabular Reasoning with Privileged Structured Information | https://arxiv.org/abs/2506.04088 | [] | [] | [] | [] | [] |
2510.19163 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19163?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2504.16427 | https://paperswithcode.co/api/v1/papers/arxiv/2504.16427?include_resources=true | 200 | true | 48075 | Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark | https://arxiv.org/abs/2504.16427v2 | [
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2501.17356 | https://paperswithcode.co/api/v1/papers/arxiv/2501.17356?include_resources=true | 200 | true | 87166 | On the Coexistence and Ensembling of Watermarks | https://arxiv.org/abs/2501.17356 | [] | [] | [] | [] | [] |
2505.15134 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15134?include_resources=true | 200 | true | 49262 | The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning | https://arxiv.org/abs/2505.15134 | [
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2505.18724 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18724?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.05743 | https://paperswithcode.co/api/v1/papers/arxiv/2502.05743?include_resources=true | 200 | true | 85882 | Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling | https://arxiv.org/abs/2502.05743 | [] | [] | [] | [] | [] |
2504.00587 | https://paperswithcode.co/api/v1/papers/arxiv/2504.00587?include_resources=true | 200 | true | 47105 | AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systems | https://arxiv.org/abs/2504.00587v2 | [] | [] | [] | [] | [] |
2507.06543 | https://paperswithcode.co/api/v1/papers/arxiv/2507.06543?include_resources=true | 200 | true | 51783 | Token Bottleneck: One Token to Remember Dynamics | https://arxiv.org/abs/2507.06543 | [
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2410.12652 | https://paperswithcode.co/api/v1/papers/arxiv/2410.12652?include_resources=true | 200 | true | 87034 | Constrained Posterior Sampling: Time Series Generation with Hard Constraints | https://arxiv.org/abs/2410.12652 | [] | [] | [] | [] | [] |
2507.15887 | https://paperswithcode.co/api/v1/papers/arxiv/2507.15887?include_resources=true | 200 | true | 70989 | AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs? | https://arxiv.org/abs/2507.15887 | [] | [] | [] | [] | [] |
2505.24550 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24550?include_resources=true | 200 | true | 72510 | A*-Thought: Efficient Reasoning via Bidirectional Compression for
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2509.17186 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17186?include_resources=true | 200 | true | 87083 | Dendritic Resonate-and-Fire Neuron for Effective and Efficient Long Sequence Modeling | https://arxiv.org/abs/2509.17186 | [] | [] | [] | [] | [] |
2412.12661 | https://paperswithcode.co/api/v1/papers/arxiv/2412.12661?include_resources=true | 200 | true | 41737 | MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants | https://arxiv.org/abs/2412.12661 | [
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2506.09684 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09684?include_resources=true | 200 | true | 50941 | Inv-Entropy: A Fully Probabilistic Framework for Uncertainty Quantification in Language Models | https://arxiv.org/abs/2506.09684 | [
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2507.06607 | https://paperswithcode.co/api/v1/papers/arxiv/2507.06607?include_resources=true | 200 | true | 51784 | Decoder-Hybrid-Decoder Architecture for Efficient Reasoning with Long Generation | https://arxiv.org/abs/2507.06607v2 | [
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2505.18276 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18276?include_resources=true | 200 | true | 86478 | Preconditioned Langevin Dynamics with Score-based Generative Models for Infinite-Dimensional Linear Bayesian Inverse Problems | https://arxiv.org/abs/2505.18276 | [] | [] | [] | [] | [] |
2505.19093 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19093?include_resources=true | 200 | true | 86094 | A Unified Framework for Variable Selection in Model-Based Clustering with Missing Not at Random | https://arxiv.org/abs/2505.19093 | [] | [] | [] | [] | [] |
2411.04625 | https://paperswithcode.co/api/v1/papers/arxiv/2411.04625?include_resources=true | 200 | true | 86831 | Sharp Analysis for KL-Regularized Contextual Bandits and RLHF | https://arxiv.org/abs/2411.04625 | [] | [] | [] | [] | [] |
2502.06545 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06545?include_resources=true | 200 | true | 43936 | Universal Sequence Preconditioning | https://arxiv.org/abs/2502.06545v2 | [] | [] | [] | [] | [] |
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