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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2510.05520 | https://paperswithcode.co/api/v1/papers/arxiv/2510.05520?include_resources=true | 200 | true | 86832 | CAM: A Constructivist View of Agentic Memory for LLM-Based Reading Comprehension | https://arxiv.org/abs/2510.05520 | [] | [] | [] | [] | [] |
2505.23734 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23734?include_resources=true | 200 | true | 50145 | ZPressor: Bottleneck-Aware Compression for Scalable Feed-Forward 3DGS | https://arxiv.org/abs/2505.23734 | [
{
"url": "https://github.com/ziplab/zpressor",
"owner": "ziplab",
"name": "ZPressor",
"stars": 152,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://lhmd.top/zpressor/",
"is_official": true
},
{
"url": "https://lhmd.top/zpressor",
"is_official": true
}
] | [] | [] | [] |
2502.08006 | https://paperswithcode.co/api/v1/papers/arxiv/2502.08006?include_resources=true | 200 | true | 44074 | Greed is Good: A Unifying Perspective on Guided Generation | https://arxiv.org/abs/2502.08006v2 | [] | [] | [] | [] | [] |
2501.00663 | https://paperswithcode.co/api/v1/papers/arxiv/2501.00663?include_resources=true | 200 | true | 42371 | Titans: Learning to Memorize at Test Time | https://arxiv.org/abs/2501.00663 | [
{
"url": "https://github.com/rahulpatnaik/titan-architechture",
"owner": "RahulPatnaik",
"name": "Titan-architechture",
"stars": 5,
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"source": "links_json"
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] | [] | [] | [] | [] |
2506.14051 | https://paperswithcode.co/api/v1/papers/arxiv/2506.14051?include_resources=true | 200 | true | 87265 | Estimation of Treatment Effects in Extreme and Unobserved Data | https://arxiv.org/abs/2506.14051 | [] | [] | [] | [] | [] |
2411.10962 | https://paperswithcode.co/api/v1/papers/arxiv/2411.10962?include_resources=true | 200 | true | 40084 | V2X-Radar: A Multi-modal Dataset with 4D Radar for Cooperative Perception | https://arxiv.org/abs/2411.10962 | [
{
"url": "https://github.com/yanglei18/v2x-radar",
"owner": "yanglei18",
"name": "V2X-Radar",
"stars": 58,
"is_official": true,
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] | [
{
"url": "http://openmpd.com/column/V2X-Radar",
"is_official": true
}
] | [] | [] | [] |
2408.13036 | https://paperswithcode.co/api/v1/papers/arxiv/2408.13036?include_resources=true | 200 | true | 76534 | H3D-DGS: Exploring Heterogeneous 3D Motion Representation for Deformable 3D Gaussian Splatting | https://arxiv.org/abs/2408.13036 | [] | [] | [] | [] | [] |
2504.06263 | https://paperswithcode.co/api/v1/papers/arxiv/2504.06263?include_resources=true | 200 | true | 47433 | OmniSVG: A Unified Scalable Vector Graphics Generation Model | https://arxiv.org/abs/2504.06263 | [
{
"url": "https://github.com/omnisvg/omnisvg",
"owner": "OmniSVG",
"name": "OmniSVG",
"stars": 2279,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://omnisvg.github.io/",
"is_official": true
}
] | [] | [] | [] |
2509.25033 | https://paperswithcode.co/api/v1/papers/arxiv/2509.25033?include_resources=true | 200 | true | 66004 | VT-FSL: Bridging Vision and Text with LLMs for Few-Shot Learning | https://arxiv.org/abs/2509.25033 | [] | [] | [] | [] | [] |
2502.17721 | https://paperswithcode.co/api/v1/papers/arxiv/2502.17721?include_resources=true | 200 | true | 85961 | Aligning Compound AI Systems via System-level DPO | https://arxiv.org/abs/2502.17721 | [] | [] | [] | [] | [] |
2506.05701 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05701?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.06164 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06164?include_resources=true | 200 | true | 86714 | Functional Complexity-adaptive Temporal Tensor Decomposition | https://arxiv.org/abs/2502.06164 | [] | [] | [] | [] | [] |
2407.00611 | https://paperswithcode.co/api/v1/papers/arxiv/2407.00611?include_resources=true | 200 | true | 86835 | StarTrail: Concentric Ring Parallelism for Efficient Near-Infinite-Context Transformer Model Training | https://arxiv.org/abs/2407.00611 | [] | [] | [] | [] | [] |
2506.01317 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01317?include_resources=true | 200 | true | 72417 | T-SHIRT: Token-Selective Hierarchical Data Selection for Instruction Tuning | https://arxiv.org/abs/2506.01317 | [
{
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"owner": "Dynamite321",
"name": "T-SHIRT",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2506.01716 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01716?include_resources=true | 200 | true | 50401 | Self-Challenging Language Model Agents | https://arxiv.org/abs/2506.01716 | [] | [] | [] | [] | [] |
2511.03725 | https://paperswithcode.co/api/v1/papers/arxiv/2511.03725?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.12171 | https://paperswithcode.co/api/v1/papers/arxiv/2502.12171?include_resources=true | 200 | true | 44432 | GoRA: Gradient-driven Adaptive Low Rank Adaptation | https://arxiv.org/abs/2502.12171v2 | [
{
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"owner": "hhnqqq",
"name": "MyTransformers",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2507.18624 | https://paperswithcode.co/api/v1/papers/arxiv/2507.18624?include_resources=true | 200 | true | 70754 | Checklists Are Better Than Reward Models For Aligning Language Models | https://arxiv.org/abs/2507.18624 | [] | [] | [] | [] | [] |
2509.10687 | https://paperswithcode.co/api/v1/papers/arxiv/2509.10687?include_resources=true | 200 | true | 52827 | Stable Part Diffusion 4D: Multi-View RGB and Kinematic Parts Video
Generation | https://arxiv.org/abs/2509.10687 | [] | [
{
"url": "https://stablepartdiffusion4d.github.io/",
"is_official": true
}
] | [] | [] | [] |
2502.13095 | https://paperswithcode.co/api/v1/papers/arxiv/2502.13095?include_resources=true | 200 | true | 86160 | Understanding and Rectifying Safety Perception Distortion in VLMs | https://arxiv.org/abs/2502.13095 | [] | [] | [] | [] | [] |
2411.15046 | https://paperswithcode.co/api/v1/papers/arxiv/2411.15046?include_resources=true | 200 | true | 86814 | On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning | https://arxiv.org/abs/2411.15046 | [] | [] | [] | [] | [] |
2411.17265 | https://paperswithcode.co/api/v1/papers/arxiv/2411.17265?include_resources=true | 200 | true | 40503 | A Topic-level Self-Correctional Approach to Mitigate Hallucinations in MLLMs | https://arxiv.org/abs/2411.17265v2 | [
{
"url": "https://github.com/tpr-dpo/tpr-dpo",
"owner": "tpr-dpo",
"name": "tpr-dpo",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://tpr-dpo.github.io",
"is_official": true
},
{
"url": "https://topic-overwrite.github.io",
"is_official": true
}
] | [] | [] | [] |
2502.04510 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04510?include_resources=true | 200 | true | 87151 | Heterogeneous Swarms: Jointly Optimizing Model Roles and Weights for Multi-LLM Systems | https://arxiv.org/abs/2502.04510 | [] | [] | [] | [] | [] |
2412.04233 | https://paperswithcode.co/api/v1/papers/arxiv/2412.04233?include_resources=true | 200 | true | 86356 | HyperMARL: Adaptive Hypernetworks for Multi-Agent RL | https://arxiv.org/abs/2412.04233 | [
{
"url": "https://github.com/kaleabtessera/hypermarl",
"owner": "kaleabtessera",
"name": "hypermarl",
"stars": 21,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2505.23564 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23564?include_resources=true | 200 | true | 50117 | Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models | https://arxiv.org/abs/2505.23564 | [
{
"url": "https://github.com/aiframeresearch/spo",
"owner": "AIFrameResearch",
"name": "SPO",
"stars": 43,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.18584 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18584?include_resources=true | 200 | true | 87109 | Unleashing Diffusion Transformers for Visual Correspondence by Modulating Massive Activations | https://arxiv.org/abs/2505.18584 | [] | [] | [] | [] | [] |
2510.12007 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12007?include_resources=true | 200 | true | 87248 | Semi-infinite Nonconvex Constrained Min-Max Optimization | https://arxiv.org/abs/2510.12007 | [] | [] | [] | [] | [] |
2511.01795 | https://paperswithcode.co/api/v1/papers/arxiv/2511.01795?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.04580 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04580?include_resources=true | 200 | true | 87385 | Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context | https://arxiv.org/abs/2502.04580 | [] | [] | [] | [] | [] |
2409.18893 | https://paperswithcode.co/api/v1/papers/arxiv/2409.18893?include_resources=true | 200 | true | 87247 | HM3: Hierarchical Multi-Objective Model Merging for Pretrained Models | https://arxiv.org/abs/2409.18893 | [] | [] | [] | [] | [] |
2509.19003 | https://paperswithcode.co/api/v1/papers/arxiv/2509.19003?include_resources=true | 200 | true | 67947 | Unveiling Chain of Step Reasoning for Vision-Language Models with
Fine-grained Rewards | https://arxiv.org/abs/2509.19003 | [
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"owner": "baaivision",
"name": "CoS",
"stars": 0,
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"source": "hf_api"
}
] | [] | [] | [] | [] |
2507.09990 | https://paperswithcode.co/api/v1/papers/arxiv/2507.09990?include_resources=true | 200 | true | 87065 | Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix | https://arxiv.org/abs/2507.09990 | [] | [] | [] | [] | [] |
2509.13341 | https://paperswithcode.co/api/v1/papers/arxiv/2509.13341?include_resources=true | 200 | true | 86643 | Imagined Autocurricula | https://arxiv.org/abs/2509.13341 | [] | [] | [] | [] | [] |
2409.09778 | https://paperswithcode.co/api/v1/papers/arxiv/2409.09778?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2406.17345 | https://paperswithcode.co/api/v1/papers/arxiv/2406.17345?include_resources=true | 200 | true | 33645 | NerfBaselines: Consistent and Reproducible Evaluation of Novel View Synthesis Methods | https://arxiv.org/abs/2406.17345 | [] | [] | [] | [] | [] |
2511.22944 | https://paperswithcode.co/api/v1/papers/arxiv/2511.22944?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.01939 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01939?include_resources=true | 200 | true | 50417 | Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning | https://arxiv.org/abs/2506.01939 | [] | [
{
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},
{
"url": "https://shenzhi-wang.github.io/high-entropy-minority-tokens-rlvr",
"is_official": true
}
] | [] | [] | [] |
2509.16691 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16691?include_resources=true | 200 | true | 68078 | InstanceAssemble: Layout-Aware Image Generation via Instance Assembling
Attention | https://arxiv.org/abs/2509.16691 | [
{
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"owner": "FireRedTeam",
"name": "InstanceAssemble",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2505.15877 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15877?include_resources=true | 200 | true | 86887 | Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval | https://arxiv.org/abs/2505.15877 | [] | [] | [] | [] | [] |
2410.19964 | https://paperswithcode.co/api/v1/papers/arxiv/2410.19964?include_resources=true | 200 | true | 87037 | Understanding Adam Requires Better Rotation Dependent Assumptions | https://arxiv.org/abs/2410.19964 | [] | [] | [] | [] | [] |
2507.07781 | https://paperswithcode.co/api/v1/papers/arxiv/2507.07781?include_resources=true | 200 | true | 71271 | SURPRISE3D: A Dataset for Spatial Understanding and Reasoning in Complex
3D Scenes | https://arxiv.org/abs/2507.07781 | [
{
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"owner": "liziwennba",
"name": "SUPRISE",
"stars": 0,
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}
] | [] | [] | [] | [] |
2502.03198 | https://paperswithcode.co/api/v1/papers/arxiv/2502.03198?include_resources=true | 200 | true | 86768 | SimSort: A Data-Driven Framework for Spike Sorting by Large-Scale Electrophysiology Simulation | https://arxiv.org/abs/2502.03198 | [] | [] | [] | [] | [] |
2505.17017 | https://paperswithcode.co/api/v1/papers/arxiv/2505.17017?include_resources=true | 200 | true | 72844 | Delving into RL for Image Generation with CoT: A Study on DPO vs. GRPO | https://arxiv.org/abs/2505.17017 | [
{
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"owner": "ZiyuGuo99",
"name": "Image-Generation-CoT",
"stars": 844,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2506.23361 | https://paperswithcode.co/api/v1/papers/arxiv/2506.23361?include_resources=true | 200 | true | 71635 | OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions | https://arxiv.org/abs/2506.23361 | [
{
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"owner": "caiyuanhao1998",
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"stars": 0,
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] | [
{
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"is_official": true
}
] | [] | [] | [] |
2509.15235 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15235?include_resources=true | 200 | true | 68268 | ViSpec: Accelerating Vision-Language Models with Vision-Aware
Speculative Decoding | https://arxiv.org/abs/2509.15235 | [
{
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"owner": "KangJialiang",
"name": "ViSpec",
"stars": 0,
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] | [] | [] | [] | [] |
2505.13737 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13737?include_resources=true | 200 | true | 72951 | Causal Head Gating: A Framework for Interpreting Roles of Attention Heads in Transformers | https://arxiv.org/abs/2505.13737 | [] | [] | [] | [] | [] |
2505.13938 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13938?include_resources=true | 200 | true | 49110 | CLEVER: A Curated Benchmark for Formally Verified Code Generation | https://arxiv.org/abs/2505.13938v3 | [
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"name": "clever-prover",
"stars": 2,
"i... | [] | [] | [] | [] |
2511.13911 | https://paperswithcode.co/api/v1/papers/arxiv/2511.13911?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.16888 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16888?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.02731 | https://paperswithcode.co/api/v1/papers/arxiv/2510.02731?include_resources=true | 200 | true | 87066 | Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering | https://arxiv.org/abs/2510.02731 | [] | [] | [] | [] | [] |
2505.14177 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14177?include_resources=true | 200 | true | 86717 | From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling | https://arxiv.org/abs/2505.14177 | [] | [] | [] | [] | [] |
2504.03188 | https://paperswithcode.co/api/v1/papers/arxiv/2504.03188?include_resources=true | 200 | true | 86563 | Pairwise Optimal Transports for Training All-to-All Flow-Based Condition Transfer Model | https://arxiv.org/abs/2504.03188 | [] | [] | [] | [] | [] |
2501.13734 | https://paperswithcode.co/api/v1/papers/arxiv/2501.13734?include_resources=true | 200 | true | 43157 | Sample complexity of data-driven tuning of model hyperparameters in neural networks with structured parameter-dependent dual function | https://arxiv.org/abs/2501.13734 | [] | [] | [] | [] | [] |
2511.02773 | https://paperswithcode.co/api/v1/papers/arxiv/2511.02773?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2508.12720 | https://paperswithcode.co/api/v1/papers/arxiv/2508.12720?include_resources=true | 200 | true | 87064 | Quantifying and Alleviating Co-Adaptation in Sparse-View 3D Gaussian Splatting | https://arxiv.org/abs/2508.12720 | [] | [] | [] | [] | [] |
2512.03127 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03127?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.03601 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03601?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.20648 | https://paperswithcode.co/api/v1/papers/arxiv/2509.20648?include_resources=true | 200 | true | 87453 | Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration | https://arxiv.org/abs/2509.20648 | [] | [] | [] | [] | [] |
2508.08222 | https://paperswithcode.co/api/v1/papers/arxiv/2508.08222?include_resources=true | 200 | true | 86396 | Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent | https://arxiv.org/abs/2508.08222 | [] | [] | [] | [] | [] |
2511.01510 | https://paperswithcode.co/api/v1/papers/arxiv/2511.01510?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2508.02085 | https://paperswithcode.co/api/v1/papers/arxiv/2508.02085?include_resources=true | 200 | true | 70300 | SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning
with LLM-Based Agents | https://arxiv.org/abs/2508.02085 | [
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] | [
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}
] | [] | [] | [] |
2506.11791 | https://paperswithcode.co/api/v1/papers/arxiv/2506.11791?include_resources=true | 200 | true | 51080 | SEC-bench: Automated Benchmarking of LLM Agents on Real-World Software Security Tasks | https://arxiv.org/abs/2506.11791 | [
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] | [
{
"url": "https://sec-bench.github.io",
"is_official": true
}
] | [] | [] | [] |
2506.13771 | https://paperswithcode.co/api/v1/papers/arxiv/2506.13771?include_resources=true | 200 | true | 51174 | LittleBit: Ultra Low-Bit Quantization via Latent Factorization | https://arxiv.org/abs/2506.13771 | [
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"owner": "SamsungLabs",
"name": "LittleBit",
"stars": 0,
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] | [] | [] | [] | [] |
2510.06307 | https://paperswithcode.co/api/v1/papers/arxiv/2510.06307?include_resources=true | 200 | true | 86123 | Belief-Calibrated Multi-Agent Consensus Seeking for Complex NLP Tasks | https://arxiv.org/abs/2510.06307 | [
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"owner": "dengwentao99",
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"stars": 1,
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] | [] | [] | [] | [] |
2407.07221 | https://paperswithcode.co/api/v1/papers/arxiv/2407.07221?include_resources=true | 200 | true | 87456 | Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning | https://arxiv.org/abs/2407.07221 | [] | [] | [] | [] | [] |
2512.23853 | https://paperswithcode.co/api/v1/papers/arxiv/2512.23853?include_resources=true | 200 | true | 63205 | Flow Matching Neural Processes | https://arxiv.org/abs/2512.23853 | [
{
"url": "https://github.com/danrsm/flowNP",
"owner": "danrsm",
"name": "flowNP",
"stars": 5,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2505.15879 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15879?include_resources=true | 200 | true | 49342 | GRIT: Teaching MLLMs to Think with Images | https://arxiv.org/abs/2505.15879 | [
{
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"owner": "eric-ai-lab",
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"stars": 165,
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] | [
{
"url": "https://grounded-reasoning.github.io",
"is_official": true
}
] | [] | [] | [] |
2411.00066 | https://paperswithcode.co/api/v1/papers/arxiv/2411.00066?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.22760 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22760?include_resources=true | 200 | true | 85716 | Non-convex entropic mean-field optimization via Best Response flow | https://arxiv.org/abs/2505.22760 | [] | [] | [] | [] | [] |
2410.09038 | https://paperswithcode.co/api/v1/papers/arxiv/2410.09038?include_resources=true | 200 | true | 38332 | SimpleStrat: Diversifying Language Model Generation with Stratification | https://arxiv.org/abs/2410.09038v2 | [] | [] | [] | [] | [] |
2510.20871 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20871?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.15692 | https://paperswithcode.co/api/v1/papers/arxiv/2506.15692?include_resources=true | 200 | true | 72622 | MLE-STAR: Machine Learning Engineering Agent via Search and Targeted
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2505.19371 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19371?include_resources=true | 200 | true | 49724 | Foundations of Top-$k$ Decoding For Language Models | https://arxiv.org/abs/2505.19371 | [] | [] | [] | [] | [] |
2507.18342 | https://paperswithcode.co/api/v1/papers/arxiv/2507.18342?include_resources=true | 200 | true | 70776 | EgoExoBench: A Benchmark for First- and Third-person View Video
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2502.09564 | https://paperswithcode.co/api/v1/papers/arxiv/2502.09564?include_resources=true | 200 | true | 85859 | Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing | https://arxiv.org/abs/2502.09564 | [] | [] | [] | [] | [] |
2311.16515 | https://paperswithcode.co/api/v1/papers/arxiv/2311.16515?include_resources=true | 200 | true | 23866 | Automatic Synthetic Data and Fine-grained Adaptive Feature Alignment for Composed Person Retrieval | https://arxiv.org/abs/2311.16515v4 | [
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2505.15311 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15311?include_resources=true | 200 | true | 49283 | Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning | https://arxiv.org/abs/2505.15311 | [] | [] | [] | [] | [] |
2505.23971 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23971?include_resources=true | 200 | true | 86623 | Critical Batch Size Revisited: A Simple Empirical Approach to Large-Batch Language Model Training | https://arxiv.org/abs/2505.23971 | [] | [] | [] | [] | [] |
2510.19241 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19241?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.06907 | https://paperswithcode.co/api/v1/papers/arxiv/2510.06907?include_resources=true | 200 | true | 87254 | Angular Constraint Embedding via SpherePair Loss for Constrained Clustering | https://arxiv.org/abs/2510.06907 | [
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2504.14945 | https://paperswithcode.co/api/v1/papers/arxiv/2504.14945?include_resources=true | 200 | true | 47981 | Learning to Reason under Off-Policy Guidance | https://arxiv.org/abs/2504.14945v3 | [
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2505.15647 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15647?include_resources=true | 200 | true | 86335 | Second-Order Convergence in Private Stochastic Non-Convex Optimization | https://arxiv.org/abs/2505.15647 | [] | [] | [] | [] | [] |
2507.06806 | https://paperswithcode.co/api/v1/papers/arxiv/2507.06806?include_resources=true | 200 | true | 71307 | GreenHyperSpectra: A multi-source hyperspectral dataset for global
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2512.01188 | https://paperswithcode.co/api/v1/papers/arxiv/2512.01188?include_resources=true | 200 | true | 64310 | Real-World Reinforcement Learning of Active Perception Behaviors | https://arxiv.org/abs/2512.01188 | [
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2504.13146 | https://paperswithcode.co/api/v1/papers/arxiv/2504.13146?include_resources=true | 200 | true | 47866 | Antidistillation Sampling | https://arxiv.org/abs/2504.13146 | [
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2405.12961 | https://paperswithcode.co/api/v1/papers/arxiv/2405.12961?include_resources=true | 200 | true | 87073 | Aligning Transformers with Continuous Feedback via Energy Rank Alignment | https://arxiv.org/abs/2405.12961 | [] | [] | [] | [] | [] |
2506.01935 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01935?include_resources=true | 200 | true | 72373 | Low-Rank Head Avatar Personalization with Registers | https://arxiv.org/abs/2506.01935 | [] | [] | [] | [] | [] |
2505.19547 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19547?include_resources=true | 200 | true | 85990 | STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution Generalization | https://arxiv.org/abs/2505.19547 | [] | [] | [] | [] | [] |
2412.01784 | https://paperswithcode.co/api/v1/papers/arxiv/2412.01784?include_resources=true | 200 | true | 86918 | Noise Injection Reveals Hidden Capabilities of Sandbagging Language Models | https://arxiv.org/abs/2412.01784 | [] | [] | [] | [] | [] |
2505.21721 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21721?include_resources=true | 200 | true | 86265 | Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference | https://arxiv.org/abs/2505.21721 | [] | [] | [] | [] | [] |
2505.13432 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13432?include_resources=true | 200 | true | 49065 | Synthetic-Powered Predictive Inference | https://arxiv.org/abs/2505.13432 | [
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2506.01748 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01748?include_resources=true | 200 | true | 86902 | Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning | https://arxiv.org/abs/2506.01748 | [] | [] | [] | [] | [] |
2512.14480 | https://paperswithcode.co/api/v1/papers/arxiv/2512.14480?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.19955 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19955?include_resources=true | 200 | true | 49792 | MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research | https://arxiv.org/abs/2505.19955 | [
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2506.02754 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02754?include_resources=true | 200 | true | 86976 | Safely Learning Controlled Stochastic Dynamics | https://arxiv.org/abs/2506.02754 | [] | [] | [] | [] | [] |
2601.03483 | https://paperswithcode.co/api/v1/papers/arxiv/2601.03483?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.15807 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15807?include_resources=true | 200 | true | 87119 | The Atlas of In-Context Learning: How Attention Heads Shape In-Context Retrieval Augmentation | https://arxiv.org/abs/2505.15807 | [] | [] | [] | [] | [] |
2510.18322 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18322?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.19877 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19877?include_resources=true | 200 | true | 72706 | Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought | https://arxiv.org/abs/2505.19877 | [] | [] | [] | [] | [] |
2410.14281 | https://paperswithcode.co/api/v1/papers/arxiv/2410.14281?include_resources=true | 200 | true | 86587 | PLMTrajRec: A Scalable and Generalizable Trajectory Recovery Method with Pre-trained Language Models | https://arxiv.org/abs/2410.14281 | [] | [] | [] | [] | [] |
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