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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2510.20602 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20602?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.13904 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13904?include_resources=true | 200 | true | 85767 | Learning to Insert for Constructive Neural Vehicle Routing Solver | https://arxiv.org/abs/2505.13904 | [] | [] | [] | [] | [] |
2412.03568 | https://paperswithcode.co/api/v1/papers/arxiv/2412.03568?include_resources=true | 200 | true | 40996 | The Matrix: Infinite-Horizon World Generation with Real-Time Moving Control | https://arxiv.org/abs/2412.03568 | [] | [
{
"url": "https://thematrix1999.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.24243 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24243?include_resources=true | 200 | true | 87333 | Model Informed Flows for Bayesian Inference of Probabilistic Programs | https://arxiv.org/abs/2505.24243 | [] | [] | [] | [] | [] |
2506.02946 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02946?include_resources=true | 200 | true | 86505 | Abstract Counterfactuals for Language Model Agents | https://arxiv.org/abs/2506.02946 | [] | [] | [] | [] | [] |
2506.05188 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05188?include_resources=true | 200 | true | 86782 | Counterfactual reasoning: an analysis of in-context emergence | https://arxiv.org/abs/2506.05188 | [
{
"url": "https://github.com/mrtzmllr/counterfactual-reasoning",
"owner": "mrtzmllr",
"name": "counterfactual-reasoning",
"stars": 2,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2506.06542 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06542?include_resources=true | 200 | true | 86215 | Direct Fisher Score Estimation for Likelihood Maximization | https://arxiv.org/abs/2506.06542 | [] | [] | [] | [] | [] |
2511.02652 | https://paperswithcode.co/api/v1/papers/arxiv/2511.02652?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.15701 | https://paperswithcode.co/api/v1/papers/arxiv/2506.15701?include_resources=true | 200 | true | 86089 | Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning | https://arxiv.org/abs/2506.15701 | [
{
"url": "https://github.com/mind4compiler/compiler-r1",
"owner": "mind4compiler",
"name": "compiler-r1",
"stars": 32,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2412.00580 | https://paperswithcode.co/api/v1/papers/arxiv/2412.00580?include_resources=true | 200 | true | 86349 | Continuous Concepts Removal in Text-to-image Diffusion Models | https://arxiv.org/abs/2412.00580 | [] | [] | [] | [] | [] |
2511.04494 | https://paperswithcode.co/api/v1/papers/arxiv/2511.04494?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.18773 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18773?include_resources=true | 200 | true | 49650 | Strong Membership Inference Attacks on Massive Datasets and (Moderately) Large Language Models | https://arxiv.org/abs/2505.18773 | [] | [] | [] | [] | [] |
2502.00879 | https://paperswithcode.co/api/v1/papers/arxiv/2502.00879?include_resources=true | 200 | true | 86735 | Generating Computational Cognitive models using Large Language Models | https://arxiv.org/abs/2502.00879 | [] | [] | [] | [] | [] |
2506.22666 | https://paperswithcode.co/api/v1/papers/arxiv/2506.22666?include_resources=true | 200 | true | 86171 | VERA: Variational Inference Framework for Jailbreaking Large Language Models | https://arxiv.org/abs/2506.22666 | [] | [] | [] | [] | [] |
2506.02921 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02921?include_resources=true | 200 | true | 50478 | A Controllable Examination for Long-Context Language Models | https://arxiv.org/abs/2506.02921 | [
{
"url": "https://github.com/thomasyyj/longbio-benchmark",
"owner": "Thomasyyj",
"name": "LongBio-Benchmark",
"stars": 24,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2506.11898 | https://paperswithcode.co/api/v1/papers/arxiv/2506.11898?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.17864 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17864?include_resources=true | 200 | true | 87300 | ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos | https://arxiv.org/abs/2509.17864 | [] | [] | [] | [] | [] |
2510.19953 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19953?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.19640 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19640?include_resources=true | 200 | true | 66030 | Latent Space Factorization in LoRA | https://arxiv.org/abs/2510.19640 | [] | [] | [] | [] | [] |
2510.16670 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16670?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.14460 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14460?include_resources=true | 200 | true | 49179 | VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to Rank | https://arxiv.org/abs/2505.14460 | [
{
"url": "https://github.com/tianhewu/visualquality-r1",
"owner": "TianheWu",
"name": "VisualQuality-R1",
"stars": 138,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.10726 | https://paperswithcode.co/api/v1/papers/arxiv/2505.10726?include_resources=true | 200 | true | 86255 | Learning Repetition-Invariant Representations for Polymer Informatics | https://arxiv.org/abs/2505.10726 | [] | [] | [] | [] | [] |
2507.01131 | https://paperswithcode.co/api/v1/papers/arxiv/2507.01131?include_resources=true | 200 | true | 71544 | Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations | https://arxiv.org/abs/2507.01131 | [] | [] | [] | [] | [] |
2506.07899 | https://paperswithcode.co/api/v1/papers/arxiv/2506.07899?include_resources=true | 200 | true | 87214 | MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs | https://arxiv.org/abs/2506.07899 | [] | [] | [] | [] | [] |
2506.06003 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06003?include_resources=true | 200 | true | 86994 | What Really is a Member? Discrediting Membership Inference via Poisoning | https://arxiv.org/abs/2506.06003 | [] | [] | [] | [] | [] |
2410.01778 | https://paperswithcode.co/api/v1/papers/arxiv/2410.01778?include_resources=true | 200 | true | 86334 | TopER: Topological Embeddings in Graph Representation Learning | https://arxiv.org/abs/2410.01778 | [] | [] | [] | [] | [] |
2506.06278 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06278?include_resources=true | 200 | true | 85849 | Distillation Robustifies Unlearning | https://arxiv.org/abs/2506.06278 | [] | [] | [] | [] | [] |
2505.11730 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11730?include_resources=true | 200 | true | 48888 | Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling | https://arxiv.org/abs/2505.11730 | [] | [] | [] | [] | [] |
2506.07388 | https://paperswithcode.co/api/v1/papers/arxiv/2506.07388?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.02138 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02138?include_resources=true | 200 | true | 50432 | Revisiting LRP: Positional Attribution as the Missing Ingredient for Transformer Explainability | https://arxiv.org/abs/2506.02138 | [
{
"url": "https://github.com/yardenbakish/pe-aware-lrp",
"owner": "YardenBakish",
"name": "PE-AWARE-LRP",
"stars": 12,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2510.19779 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19779?include_resources=true | 200 | true | 53782 | AdaSPEC: Selective Knowledge Distillation for Efficient Speculative
Decoders | https://arxiv.org/abs/2510.19779 | [
{
"url": "https://github.com/yuezhouhu/adaspec",
"owner": "yuezhouhu",
"name": "adaspec",
"stars": 31,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://github.com/yuezhouhu/adaspec",
"is_official": true
}
] | [] | [] | [] |
2505.13031 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13031?include_resources=true | 200 | true | 49020 | MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO | https://arxiv.org/abs/2505.13031 | [
{
"url": "https://github.com/tencentarc/mindomni",
"owner": "TencentARC",
"name": "MindOmni",
"stars": 140,
"is_official": true,
"source": "ai_extraction"
},
{
"url": "https://github.com/easonxiao-888/mindomni",
"owner": "easonxiao-888",
"name": "mindomni",
"stars": 3,
... | [
{
"url": "https://mindomni.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.20148 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20148?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2504.16795 | https://paperswithcode.co/api/v1/papers/arxiv/2504.16795?include_resources=true | 200 | true | 73370 | Random Long-Context Access for Mamba via Hardware-aligned Hierarchical
Sparse Attention | https://arxiv.org/abs/2504.16795 | [] | [] | [] | [] | [] |
2412.06708 | https://paperswithcode.co/api/v1/papers/arxiv/2412.06708?include_resources=true | 200 | true | 41246 | FlexEvent: Towards Flexible Event-Frame Object Detection at Varying Operational Frequencies | https://arxiv.org/abs/2412.06708v2 | [] | [
{
"url": "https://flexevent.github.io/",
"is_official": true
}
] | [] | [] | [] |
2510.01268 | https://paperswithcode.co/api/v1/papers/arxiv/2510.01268?include_resources=true | 200 | true | 67466 | AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical
Guarantees | https://arxiv.org/abs/2510.01268 | [
{
"url": "https://github.com/mamba413/adadetectgpt",
"owner": "Mamba413",
"name": "AdaDetectGPT",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://github.com/Mamba413/AdaDetectGPT",
"is_official": true
}
] | [] | [] | [] |
2506.01853 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01853?include_resources=true | 200 | true | 50408 | ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding | https://arxiv.org/abs/2506.01853 | [
{
"url": "https://github.com/jamesyjl/shapellm-omni",
"owner": "JAMESYJL",
"name": "ShapeLLM-Omni",
"stars": 520,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://jamesyjl.github.io/ShapeLLM/",
"is_official": true
}
] | [] | [] | [] |
2505.21024 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21024?include_resources=true | 200 | true | 86382 | Pause Tokens Strictly Increase the Expressivity of Constant-Depth Transformers | https://arxiv.org/abs/2505.21024 | [] | [] | [] | [] | [] |
2502.11559 | https://paperswithcode.co/api/v1/papers/arxiv/2502.11559?include_resources=true | 200 | true | 85921 | Auto-Search and Refinement: An Automated Framework for Gender Bias Mitigation in Large Language Models | https://arxiv.org/abs/2502.11559 | [] | [] | [] | [] | [] |
2503.07029 | https://paperswithcode.co/api/v1/papers/arxiv/2503.07029?include_resources=true | 200 | true | 74194 | Availability-aware Sensor Fusion via Unified Canonical Space | https://arxiv.org/abs/2503.07029 | [] | [] | [] | [] | [] |
2509.18552 | https://paperswithcode.co/api/v1/papers/arxiv/2509.18552?include_resources=true | 200 | true | 87094 | Global Minimizers of Sigmoid Contrastive Loss | https://arxiv.org/abs/2509.18552 | [] | [] | [] | [] | [] |
2511.02194 | https://paperswithcode.co/api/v1/papers/arxiv/2511.02194?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2412.06966 | https://paperswithcode.co/api/v1/papers/arxiv/2412.06966?include_resources=true | 200 | true | 75541 | Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research | https://arxiv.org/abs/2412.06966 | [] | [] | [] | [] | [] |
2506.06271 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06271?include_resources=true | 200 | true | 87297 | BecomingLit: Relightable Gaussian Avatars with Hybrid Neural Shading | https://arxiv.org/abs/2506.06271 | [] | [] | [] | [] | [] |
2511.02225 | https://paperswithcode.co/api/v1/papers/arxiv/2511.02225?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.22664 | https://paperswithcode.co/api/v1/papers/arxiv/2511.22664?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.08428 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08428?include_resources=true | 200 | true | 87099 | Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings | https://arxiv.org/abs/2506.08428 | [] | [] | [] | [] | [] |
2505.18456 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18456?include_resources=true | 200 | true | 49612 | Anchored Diffusion Language Model | https://arxiv.org/abs/2505.18456 | [] | [] | [] | [] | [] |
2505.24518 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24518?include_resources=true | 200 | true | 85998 | ARECHO: Autoregressive Evaluation via Chain-Based Hypothesis Optimization for Speech Multi-Metric Estimation | https://arxiv.org/abs/2505.24518 | [] | [] | [] | [] | [] |
2505.12541 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12541?include_resources=true | 200 | true | 86545 | Private Statistical Estimation via Truncation | https://arxiv.org/abs/2505.12541 | [] | [] | [] | [] | [] |
2512.01405 | https://paperswithcode.co/api/v1/papers/arxiv/2512.01405?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2412.10321 | https://paperswithcode.co/api/v1/papers/arxiv/2412.10321?include_resources=true | 200 | true | 85933 | AdvPrefix: An Objective for Nuanced LLM Jailbreaks | https://arxiv.org/abs/2412.10321 | [] | [] | [] | [] | [] |
2505.20161 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20161?include_resources=true | 200 | true | 49823 | Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning | https://arxiv.org/abs/2505.20161 | [] | [] | [] | [] | [] |
2510.19421 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19421?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2409.20163 | https://paperswithcode.co/api/v1/papers/arxiv/2409.20163?include_resources=true | 200 | true | 86837 | MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants | https://arxiv.org/abs/2409.20163 | [
{
"url": "https://github.com/nuster1128/memsim",
"owner": "nuster1128",
"name": "memsim",
"stars": 16,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2602.01095 | https://paperswithcode.co/api/v1/papers/arxiv/2602.01095?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.15276 | https://paperswithcode.co/api/v1/papers/arxiv/2511.15276?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.08797 | https://paperswithcode.co/api/v1/papers/arxiv/2510.08797?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.05285 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05285?include_resources=true | 200 | true | 50640 | RaySt3R: Predicting Novel Depth Maps for Zero-Shot Object Completion | https://arxiv.org/abs/2506.05285 | [] | [
{
"url": "https://rayst3r.github.io/",
"is_official": true
},
{
"url": "https://rayst3r.github.io",
"is_official": true
}
] | [] | [] | [] |
2507.03279 | https://paperswithcode.co/api/v1/papers/arxiv/2507.03279?include_resources=true | 200 | true | 71453 | Conformal Information Pursuit for Interactively Guiding Large Language
Models | https://arxiv.org/abs/2507.03279 | [] | [] | [] | [] | [] |
2506.13690 | https://paperswithcode.co/api/v1/papers/arxiv/2506.13690?include_resources=true | 200 | true | 87317 | Meta-learning how to Share Credit among Macro-Actions | https://arxiv.org/abs/2506.13690 | [] | [] | [] | [] | [] |
2501.08263 | https://paperswithcode.co/api/v1/papers/arxiv/2501.08263?include_resources=true | 200 | true | 86833 | Multiplayer Federated Learning: Reaching Equilibrium with Less Communication | https://arxiv.org/abs/2501.08263 | [] | [] | [] | [] | [] |
2508.18076 | https://paperswithcode.co/api/v1/papers/arxiv/2508.18076?include_resources=true | 200 | true | 52509 | Neither Valid nor Reliable? Investigating the Use of LLMs as Judges | https://arxiv.org/abs/2508.18076v2 | [] | [] | [] | [] | [] |
2506.08415 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08415?include_resources=true | 200 | true | 87374 | Improved Scaling Laws in Linear Regression via Data Reuse | https://arxiv.org/abs/2506.08415 | [] | [] | [] | [] | [] |
2601.08731 | https://paperswithcode.co/api/v1/papers/arxiv/2601.08731?include_resources=true | 200 | true | 62577 | Learning from Demonstrations via Capability-Aware Goal Sampling | https://arxiv.org/abs/2601.08731 | [] | [] | [] | [] | [] |
2504.09702 | https://paperswithcode.co/api/v1/papers/arxiv/2504.09702?include_resources=true | 200 | true | 47625 | MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges? | https://arxiv.org/abs/2504.09702v2 | [
{
"url": "https://github.com/yunx-z/mlrc-bench",
"owner": "yunx-z",
"name": "MLRC-Bench",
"stars": 8,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://huggingface.co/spaces/launch/MLRC_Bench",
"is_official": true
}
] | [] | [] | [] |
2507.01737 | https://paperswithcode.co/api/v1/papers/arxiv/2507.01737?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.06072 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06072?include_resources=true | 200 | true | 86915 | Projection-based Lyapunov method for fully heterogeneous weakly-coupled MDPs | https://arxiv.org/abs/2502.06072 | [] | [] | [] | [] | [] |
2509.18648 | https://paperswithcode.co/api/v1/papers/arxiv/2509.18648?include_resources=true | 200 | true | 86168 | SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer | https://arxiv.org/abs/2509.18648 | [] | [] | [] | [] | [] |
2506.03340 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03340?include_resources=true | 200 | true | 86193 | Seeing the Arrow of Time in Large Multimodal Models | https://arxiv.org/abs/2506.03340 | [] | [] | [] | [] | [] |
2506.18165 | https://paperswithcode.co/api/v1/papers/arxiv/2506.18165?include_resources=true | 200 | true | 86946 | Non-equilibrium Annealed Adjoint Sampler | https://arxiv.org/abs/2506.18165 | [] | [] | [] | [] | [] |
2510.07823 | https://paperswithcode.co/api/v1/papers/arxiv/2510.07823?include_resources=true | 200 | true | 86096 | Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation | https://arxiv.org/abs/2510.07823 | [] | [] | [] | [] | [] |
2408.11029 | https://paperswithcode.co/api/v1/papers/arxiv/2408.11029?include_resources=true | 200 | true | 36037 | Scaling Law with Learning Rate Annealing | https://arxiv.org/abs/2408.11029v2 | [] | [] | [] | [] | [] |
2502.07064 | https://paperswithcode.co/api/v1/papers/arxiv/2502.07064?include_resources=true | 200 | true | 86529 | Contextual Thompson Sampling via Generation of Missing Data | https://arxiv.org/abs/2502.07064 | [] | [] | [] | [] | [] |
2501.14155 | https://paperswithcode.co/api/v1/papers/arxiv/2501.14155?include_resources=true | 200 | true | 87405 | Learning to price with resource constraints: from full information to machine-learned prices | https://arxiv.org/abs/2501.14155 | [] | [] | [] | [] | [] |
2511.19431 | https://paperswithcode.co/api/v1/papers/arxiv/2511.19431?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.02631 | https://paperswithcode.co/api/v1/papers/arxiv/2502.02631?include_resources=true | 200 | true | 43673 | ParetoQ: Scaling Laws in Extremely Low-bit LLM Quantization | https://arxiv.org/abs/2502.02631 | [
{
"url": "https://github.com/facebookresearch/LLM-QAT",
"owner": "facebookresearch",
"name": "LLM-QAT",
"stars": 322,
"is_official": false,
"source": "links_json"
}
] | [] | [] | [] | [] |
2508.00643 | https://paperswithcode.co/api/v1/papers/arxiv/2508.00643?include_resources=true | 200 | true | 87224 | Light-Weight Diffusion Multiplier and Uncertainty Quantification for Fourier Neural Operators | https://arxiv.org/abs/2508.00643 | [] | [] | [] | [] | [] |
2508.15593 | https://paperswithcode.co/api/v1/papers/arxiv/2508.15593?include_resources=true | 200 | true | 86989 | Inductive Domain Transfer In Misspecified Simulation-Based Inference | https://arxiv.org/abs/2508.15593 | [] | [] | [] | [] | [] |
2505.21791 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21791?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2412.06028 | https://paperswithcode.co/api/v1/papers/arxiv/2412.06028?include_resources=true | 200 | true | 41205 | FlexDiT: Dynamic Token Density Control for Diffusion Transformer | https://arxiv.org/abs/2412.06028 | [
{
"url": "https://github.com/changsn/flexdit",
"owner": "changsn",
"name": "FlexDiT",
"stars": 16,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2505.16322 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16322?include_resources=true | 200 | true | 72861 | AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners | https://arxiv.org/abs/2505.16322 | [] | [] | [] | [] | [] |
2511.13223 | https://paperswithcode.co/api/v1/papers/arxiv/2511.13223?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.17686 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17686?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2601.10058 | https://paperswithcode.co/api/v1/papers/arxiv/2601.10058?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2411.02184 | https://paperswithcode.co/api/v1/papers/arxiv/2411.02184?include_resources=true | 200 | true | 86082 | Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the Role of Model Complexity | https://arxiv.org/abs/2411.02184 | [] | [] | [] | [] | [] |
2510.17266 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17266?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2410.09836 | https://paperswithcode.co/api/v1/papers/arxiv/2410.09836?include_resources=true | 200 | true | 86699 | Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift | https://arxiv.org/abs/2410.09836 | [
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2507.09473 | https://paperswithcode.co/api/v1/papers/arxiv/2507.09473?include_resources=true | 200 | true | 85917 | Incentive-Aware Dynamic Resource Allocation under Long-Term Cost Constraints | https://arxiv.org/abs/2507.09473 | [] | [] | [] | [] | [] |
2505.18371 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18371?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.10567 | https://paperswithcode.co/api/v1/papers/arxiv/2507.10567?include_resources=true | 200 | true | 86987 | Protocols for Verifying Smooth Strategies in Bandits and Games | https://arxiv.org/abs/2507.10567 | [] | [] | [] | [] | [] |
2505.12891 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12891?include_resources=true | 200 | true | 49008 | TIME: A Multi-level Benchmark for Temporal Reasoning of LLMs in Real-World Scenarios | https://arxiv.org/abs/2505.12891 | [
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2511.17782 | https://paperswithcode.co/api/v1/papers/arxiv/2511.17782?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.23062 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23062?include_resources=true | 200 | true | 87441 | Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data | https://arxiv.org/abs/2505.23062 | [] | [] | [] | [] | [] |
2412.09059 | https://paperswithcode.co/api/v1/papers/arxiv/2412.09059?include_resources=true | 200 | true | 86543 | Go With the Flow: Fast Diffusion for Gaussian Mixture Models | https://arxiv.org/abs/2412.09059 | [
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2506.06589 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06589?include_resources=true | 200 | true | 87324 | Precise Information Control in Long-Form Text Generation | https://arxiv.org/abs/2506.06589 | [] | [] | [] | [] | [] |
2511.05664 | https://paperswithcode.co/api/v1/papers/arxiv/2511.05664?include_resources=true | 200 | true | 54144 | KLASS: KL-Guided Fast Inference in Masked Diffusion Models | https://arxiv.org/abs/2511.05664 | [
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2510.20244 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20244?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.08017 | https://paperswithcode.co/api/v1/papers/arxiv/2510.08017?include_resources=true | 200 | true | 86291 | RayFusion: Ray Fusion Enhanced Collaborative Visual Perception | https://arxiv.org/abs/2510.08017 | [
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2505.18700 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18700?include_resources=true | 200 | true | 49642 | GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains | https://arxiv.org/abs/2505.18700 | [
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