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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2511.06305 | https://paperswithcode.co/api/v1/papers/arxiv/2511.06305?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.01705 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01705?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.03429 | https://paperswithcode.co/api/v1/papers/arxiv/2502.03429?include_resources=true | 200 | true | 86627 | On Fairness of Unified Multimodal Large Language Model for Image Generation | https://arxiv.org/abs/2502.03429 | [] | [] | [] | [] | [] |
2506.11153 | https://paperswithcode.co/api/v1/papers/arxiv/2506.11153?include_resources=true | 200 | true | 51063 | Mutual-Supervised Learning for Sequential-to-Parallel Code Translation | https://arxiv.org/abs/2506.11153 | [
{
"url": "https://github.com/kcxain/musl",
"owner": "kcxain",
"name": "musl",
"stars": 10,
"is_official": true,
"source": "links_json"
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{
"url": "https://github.com/kcxain/mupa",
"owner": "kcxain",
"name": "mupa",
"stars": 0,
"is_official": true,
"source": "hf_a... | [] | [] | [] | [] |
2506.03136 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03136?include_resources=true | 200 | true | 50495 | Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning | https://arxiv.org/abs/2506.03136 | [
{
"url": "https://github.com/gen-verse/cure",
"owner": "Gen-Verse",
"name": "CURE",
"stars": 144,
"is_official": true,
"source": "links_json"
},
{
"url": "https://github.com/gen-verse/reasonflux",
"owner": "Gen-Verse",
"name": "ReasonFlux",
"stars": 510,
"is_official"... | [
{
"url": "https://huggingface.co/collections/Gen-Verse/reasonflux-coder-6833109ed9300c62deb32c6b",
"is_official": true
}
] | [] | [] | [] |
2505.23399 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23399?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.20990 | https://paperswithcode.co/api/v1/papers/arxiv/2506.20990?include_resources=true | 200 | true | 85937 | SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes | https://arxiv.org/abs/2506.20990 | [] | [] | [] | [] | [] |
2505.12528 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12528?include_resources=true | 200 | true | 86127 | Nonlinear Laplacians: Tunable principal component analysis under directional prior information | https://arxiv.org/abs/2505.12528 | [] | [] | [] | [] | [] |
2506.03931 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03931?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.11883 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11883?include_resources=true | 200 | true | 85773 | MINGLE: Mixtures of Null-Space Gated Low-Rank Experts for Test-Time Continual Model Merging | https://arxiv.org/abs/2505.11883 | [
{
"url": "https://github.com/zihuanqiu/mingle",
"owner": "zihuanqiu",
"name": "mingle",
"stars": 15,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2502.07191 | https://paperswithcode.co/api/v1/papers/arxiv/2502.07191?include_resources=true | 200 | true | 44002 | Bag of Tricks for Inference-time Computation of LLM Reasoning | https://arxiv.org/abs/2502.07191 | [
{
"url": "https://github.com/usail-hkust/benchmark_inference_time_computation_LLM",
"owner": "usail-hkust",
"name": "benchmark_inference_time_computation_LLM",
"stars": 16,
"is_official": true,
"source": "links_json"
},
{
"url": "https://github.com/usail-hkust/benchmark_inference_tim... | [] | [] | [] | [] |
2511.00859 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00859?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2410.01508 | https://paperswithcode.co/api/v1/papers/arxiv/2410.01508?include_resources=true | 200 | true | 86909 | Disentangling Latent Shifts of In-Context Learning with Weak Supervision | https://arxiv.org/abs/2410.01508 | [] | [] | [] | [] | [] |
2505.19415 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19415?include_resources=true | 200 | true | 49729 | MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models | https://arxiv.org/abs/2505.19415 | [
{
"url": "https://github.com/hanghuacs/MMIG-Bench",
"owner": "hanghuacs",
"name": "MMIG-Bench",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://hanghuacs.github.io/MMIG-Bench/",
"is_official": true
}
] | [] | [] | [] |
2511.04063 | https://paperswithcode.co/api/v1/papers/arxiv/2511.04063?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.07055 | https://paperswithcode.co/api/v1/papers/arxiv/2509.07055?include_resources=true | 200 | true | 86373 | Sequentially Auditing Differential Privacy | https://arxiv.org/abs/2509.07055 | [] | [] | [] | [] | [] |
2502.17821 | https://paperswithcode.co/api/v1/papers/arxiv/2502.17821?include_resources=true | 200 | true | 85734 | CAML: Collaborative Auxiliary Modality Learning for Multi-Agent Systems | https://arxiv.org/abs/2502.17821 | [] | [] | [] | [] | [] |
2510.17364 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17364?include_resources=true | 200 | true | 66168 | Recurrent Attention-based Token Selection for Efficient Streaming Video-LLMs | https://arxiv.org/abs/2510.17364 | [] | [] | [] | [] | [] |
2509.23492 | https://paperswithcode.co/api/v1/papers/arxiv/2509.23492?include_resources=true | 200 | true | 87130 | Orientation-anchored Hyper-Gaussian for 4D Reconstruction from Casual Videos | https://arxiv.org/abs/2509.23492 | [] | [] | [] | [] | [] |
2511.20315 | https://paperswithcode.co/api/v1/papers/arxiv/2511.20315?include_resources=true | 200 | true | 64538 | Geometry of Decision Making in Language Models | https://arxiv.org/abs/2511.20315 | [] | [] | [] | [] | [] |
2506.00771 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00771?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.21071 | https://paperswithcode.co/api/v1/papers/arxiv/2503.21071?include_resources=true | 200 | true | 86395 | Purifying Approximate Differential Privacy with Randomized Post-processing | https://arxiv.org/abs/2503.21071 | [] | [] | [] | [] | [] |
2504.06232 | https://paperswithcode.co/api/v1/papers/arxiv/2504.06232?include_resources=true | 200 | true | 47429 | HiFlow: Training-free High-Resolution Image Generation with Flow-Aligned Guidance | https://arxiv.org/abs/2504.06232v2 | [
{
"url": "https://github.com/bujiazi/hiflow",
"owner": "Bujiazi",
"name": "HiFlow",
"stars": 84,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://bujiazi.github.io/hiflow.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.13631 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13631?include_resources=true | 200 | true | 86287 | Learning (Approximately) Equivariant Networks via Constrained Optimization | https://arxiv.org/abs/2505.13631 | [] | [] | [] | [] | [] |
2510.12114 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12114?include_resources=true | 200 | true | 86995 | Self-Supervised Selective-Guided Diffusion Model for Old-Photo Face Restoration | https://arxiv.org/abs/2510.12114 | [
{
"url": "https://github.com/pris-cv/ssdiff",
"owner": "pris-cv",
"name": "ssdiff",
"stars": 15,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2505.21364 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21364?include_resources=true | 200 | true | 86518 | Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders | https://arxiv.org/abs/2505.21364 | [
{
"url": "https://github.com/james-oldfield/mxd",
"owner": "james-oldfield",
"name": "mxd",
"stars": 16,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2509.15857 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15857?include_resources=true | 200 | true | 86820 | EvoBrain: Dynamic Multi-channel EEG Graph Modeling for Time-evolving Brain Network | https://arxiv.org/abs/2509.15857 | [] | [] | [] | [] | [] |
2502.18475 | https://paperswithcode.co/api/v1/papers/arxiv/2502.18475?include_resources=true | 200 | true | 87005 | Least squares variational inference | https://arxiv.org/abs/2502.18475 | [] | [] | [] | [] | [] |
2510.19530 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19530?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2603.07529 | https://paperswithcode.co/api/v1/papers/arxiv/2603.07529?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2508.06041 | https://paperswithcode.co/api/v1/papers/arxiv/2508.06041?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2603.15336 | https://paperswithcode.co/api/v1/papers/arxiv/2603.15336?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2508.08421 | https://paperswithcode.co/api/v1/papers/arxiv/2508.08421?include_resources=true | 200 | true | 87104 | Neural Tangent Knowledge Distillation for Optical Convolutional Networks | https://arxiv.org/abs/2508.08421 | [] | [] | [] | [] | [] |
2506.13613 | https://paperswithcode.co/api/v1/papers/arxiv/2506.13613?include_resources=true | 200 | true | 86977 | Variational Inference with Mixtures of Isotropic Gaussians | https://arxiv.org/abs/2506.13613 | [] | [] | [] | [] | [] |
2509.05117 | https://paperswithcode.co/api/v1/papers/arxiv/2509.05117?include_resources=true | 200 | true | 68695 | HyPINO: Multi-Physics Neural Operators via HyperPINNs and the Method of
Manufactured Solutions | https://arxiv.org/abs/2509.05117 | [
{
"url": "https://github.com/rbischof/hypino",
"owner": "rbischof",
"name": "hypino",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2511.01315 | https://paperswithcode.co/api/v1/papers/arxiv/2511.01315?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.17174 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17174?include_resources=true | 200 | true | 85899 | Self-Supervised Discovery of Neural Circuits in Spatially Patterned Neural Responses with Graph Neural Networks | https://arxiv.org/abs/2509.17174 | [] | [] | [] | [] | [] |
2502.01159 | https://paperswithcode.co/api/v1/papers/arxiv/2502.01159?include_resources=true | 200 | true | 74959 | AtmosSci-Bench: Evaluating the Recent Advance of Large Language Model for Atmospheric Science | https://arxiv.org/abs/2502.01159 | [
{
"url": "https://github.com/Relaxed-System-Lab/AtmosSci-Bench",
"owner": "Relaxed-System-Lab",
"name": "AtmosSci-Bench",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2505.12371 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12371?include_resources=true | 200 | true | 72993 | MedAgentBoard: Benchmarking Multi-Agent Collaboration with Conventional Methods for Diverse Medical Tasks | https://arxiv.org/abs/2505.12371 | [] | [] | [] | [] | [] |
2510.20273 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20273?include_resources=true | 200 | true | 65989 | SynTSBench: Rethinking Temporal Pattern Learning in Deep Learning Models
for Time Series | https://arxiv.org/abs/2510.20273 | [
{
"url": "https://github.com/TanQitai/SynTSBench",
"owner": "TanQitai",
"name": "SynTSBench",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2505.22332 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22332?include_resources=true | 200 | true | 87170 | Credal Prediction based on Relative Likelihood | https://arxiv.org/abs/2505.22332 | [] | [] | [] | [] | [] |
2506.09995 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09995?include_resources=true | 200 | true | 50974 | PlayerOne: Egocentric World Simulator | https://arxiv.org/abs/2506.09995 | [
{
"url": "https://github.com/yuanpengtu/PlayerOne",
"owner": "yuanpengtu",
"name": "PlayerOne",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://playerone-hku.github.io/",
"is_official": true
}
] | [] | [] | [] |
2405.05905 | https://paperswithcode.co/api/v1/papers/arxiv/2405.05905?include_resources=true | 200 | true | 87352 | Truthful Aggregation of LLMs with an Application to Online Advertising | https://arxiv.org/abs/2405.05905 | [] | [] | [] | [] | [] |
2507.07712 | https://paperswithcode.co/api/v1/papers/arxiv/2507.07712?include_resources=true | 200 | true | 87312 | Class-wise Balancing Data Replay for Federated Class-Incremental Learning | https://arxiv.org/abs/2507.07712 | [] | [] | [] | [] | [] |
2511.20928 | https://paperswithcode.co/api/v1/papers/arxiv/2511.20928?include_resources=true | 200 | true | 64504 | Smooth regularization for efficient video recognition | https://arxiv.org/abs/2511.20928 | [
{
"url": "https://github.com/gilgoldm/grw-smoothing",
"owner": "gilgoldm",
"name": "grw-smoothing",
"stars": 2,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2502.01341 | https://paperswithcode.co/api/v1/papers/arxiv/2502.01341?include_resources=true | 200 | true | 43561 | AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding | https://arxiv.org/abs/2502.01341 | [
{
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"owner": "mvish7",
"name": "AlignVLM",
"stars": 13,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2505.15093 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15093?include_resources=true | 200 | true | 49259 | Steering Generative Models with Experimental Data for Protein Fitness Optimization | https://arxiv.org/abs/2505.15093 | [
{
"url": "https://github.com/jsunn-y/sgpo",
"owner": "jsunn-y",
"name": "SGPO",
"stars": 25,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2507.11344 | https://paperswithcode.co/api/v1/papers/arxiv/2507.11344?include_resources=true | 200 | true | 87026 | Guiding Fair LLM Decision-Making with Reward Models | https://arxiv.org/abs/2507.11344 | [] | [] | [] | [] | [] |
2510.07964 | https://paperswithcode.co/api/v1/papers/arxiv/2510.07964?include_resources=true | 200 | true | 86938 | PRESCRIBE: Predicting Single-Cell Responses with Bayesian Estimation | https://arxiv.org/abs/2510.07964 | [] | [] | [] | [] | [] |
2502.16706 | https://paperswithcode.co/api/v1/papers/arxiv/2502.16706?include_resources=true | 200 | true | 85954 | DISC: Dynamic Decomposition Improves LLM Inference Scaling | https://arxiv.org/abs/2502.16706 | [] | [] | [] | [] | [] |
2505.18473 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18473?include_resources=true | 200 | true | 87160 | PDPO: Parametric Density Path Optimization | https://arxiv.org/abs/2505.18473 | [] | [] | [] | [] | [] |
2510.12565 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12565?include_resources=true | 200 | true | 66432 | MMOT: The First Challenging Benchmark for Drone-based Multispectral
Multi-Object Tracking | https://arxiv.org/abs/2510.12565 | [
{
"url": "https://github.com/Annzstbl/MMOT",
"owner": "Annzstbl",
"name": "MMOT",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2507.01372 | https://paperswithcode.co/api/v1/papers/arxiv/2507.01372?include_resources=true | 200 | true | 87049 | Active Measurement: Efficient Estimation at Scale | https://arxiv.org/abs/2507.01372 | [] | [] | [] | [] | [] |
2504.10143 | https://paperswithcode.co/api/v1/papers/arxiv/2504.10143?include_resources=true | 200 | true | 87195 | On the Value of Cross-Modal Misalignment in Multimodal Representation Learning | https://arxiv.org/abs/2504.10143 | [] | [] | [] | [] | [] |
2510.10396 | https://paperswithcode.co/api/v1/papers/arxiv/2510.10396?include_resources=true | 200 | true | 66573 | MRSAudio: A Large-Scale Multimodal Recorded Spatial Audio Dataset with
Refined Annotations | https://arxiv.org/abs/2510.10396 | [
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"url": "https://github.com/MRSAudio/MRSAudio_Main",
"owner": "MRSAudio",
"name": "MRSAudio_Main",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://mrsaudio.github.io",
"is_official": true
}
] | [] | [] | [] |
2405.13954 | https://paperswithcode.co/api/v1/papers/arxiv/2405.13954?include_resources=true | 200 | true | 86686 | What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions | https://arxiv.org/abs/2405.13954 | [] | [] | [] | [] | [] |
2510.15729 | https://paperswithcode.co/api/v1/papers/arxiv/2510.15729?include_resources=true | 200 | true | 85904 | FACE: A general Framework for Mapping Collaborative Filtering Embeddings into LLM Tokens | https://arxiv.org/abs/2510.15729 | [
{
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"owner": "yixinroll",
"name": "face",
"stars": 8,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2510.17489 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17489?include_resources=true | 200 | true | 66161 | DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured
Hierarchical Representation Learning | https://arxiv.org/abs/2510.17489 | [
{
"url": "https://github.com/heyongxin233/DETree",
"owner": "heyongxin233",
"name": "DETree",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2411.14133 | https://paperswithcode.co/api/v1/papers/arxiv/2411.14133?include_resources=true | 200 | true | 40245 | GASP: Efficient Black-Box Generation of Adversarial Suffixes for Jailbreaking LLMs | https://arxiv.org/abs/2411.14133v2 | [
{
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"owner": "TrustMLRG",
"name": "GASP",
"stars": 10,
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] | [] | [] | [] | [] |
2506.21374 | https://paperswithcode.co/api/v1/papers/arxiv/2506.21374?include_resources=true | 200 | true | 86736 | Pay Attention to Small Weights | https://arxiv.org/abs/2506.21374 | [] | [] | [] | [] | [] |
2510.04908 | https://paperswithcode.co/api/v1/papers/arxiv/2510.04908?include_resources=true | 200 | true | 66933 | How Different from the Past? Spatio-Temporal Time Series Forecasting
with Self-Supervised Deviation Learning | https://arxiv.org/abs/2510.04908 | [
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"owner": "Jimmy-7664",
"name": "ST-SSDL",
"stars": 0,
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] | [] | [] | [] | [] |
2503.10633 | https://paperswithcode.co/api/v1/papers/arxiv/2503.10633?include_resources=true | 200 | true | 46079 | Charting and Navigating Hugging Face's Model Atlas | https://arxiv.org/abs/2503.10633 | [
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"owner": "eliahuhorwitz",
"name": "Model-Atlas",
"stars": 33,
"is_official": true,
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{
"url": "https://horwitz.ai/model-atlas",
"is_official": true
}
] | [] | [] | [] |
2506.15691 | https://paperswithcode.co/api/v1/papers/arxiv/2506.15691?include_resources=true | 200 | true | 85993 | What Do Latent Action Models Actually Learn? | https://arxiv.org/abs/2506.15691 | [] | [] | [] | [] | [] |
2504.12739 | https://paperswithcode.co/api/v1/papers/arxiv/2504.12739?include_resources=true | 200 | true | 47836 | Mask Image Watermarking | https://arxiv.org/abs/2504.12739v2 | [
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"owner": "hurunyi",
"name": "MaskMark",
"stars": 41,
"is_official": true,
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}
] | [] | [] | [] | [] |
2508.14927 | https://paperswithcode.co/api/v1/papers/arxiv/2508.14927?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.06218 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06218?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.14603 | https://paperswithcode.co/api/v1/papers/arxiv/2506.14603?include_resources=true | 200 | true | 51224 | Align Your Flow: Scaling Continuous-Time Flow Map Distillation | https://arxiv.org/abs/2506.14603 | [] | [
{
"url": "https://research.nvidia.com/labs/toronto-ai/AlignYourFlow/",
"is_official": true
}
] | [] | [] | [] |
2502.06749 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06749?include_resources=true | 200 | true | 86399 | Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty | https://arxiv.org/abs/2502.06749 | [] | [] | [] | [] | [] |
2506.02689 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02689?include_resources=true | 200 | true | 85707 | MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching | https://arxiv.org/abs/2506.02689 | [] | [] | [] | [] | [] |
2506.20194 | https://paperswithcode.co/api/v1/papers/arxiv/2506.20194?include_resources=true | 200 | true | 86169 | DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs | https://arxiv.org/abs/2506.20194 | [] | [] | [] | [] | [] |
2510.27340 | https://paperswithcode.co/api/v1/papers/arxiv/2510.27340?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.10844 | https://paperswithcode.co/api/v1/papers/arxiv/2505.10844?include_resources=true | 200 | true | 48808 | Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models | https://arxiv.org/abs/2505.10844 | [
{
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"owner": "stephenxia1",
"name": "brainteasers",
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] | [] | [] | [] | [] |
2506.10707 | https://paperswithcode.co/api/v1/papers/arxiv/2506.10707?include_resources=true | 200 | true | 51022 | ConTextTab: A Semantics-Aware Tabular In-Context Learner | https://arxiv.org/abs/2506.10707 | [
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2511.00446 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00446?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.15940 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15940?include_resources=true | 200 | true | 86109 | Efficient Pre-Training of LLMs via Topology-Aware Communication Alignment on More Than 9600 GPUs | https://arxiv.org/abs/2509.15940 | [] | [] | [] | [] | [] |
2505.13644 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13644?include_resources=true | 200 | true | 86196 | Collapsing Taylor Mode Automatic Differentiation | https://arxiv.org/abs/2505.13644 | [] | [] | [] | [] | [] |
2505.23419 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23419?include_resources=true | 200 | true | 50106 | SWE-bench Goes Live! | https://arxiv.org/abs/2505.23419v2 | [
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2505.24749 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24749?include_resources=true | 200 | true | 85957 | SUMO: Subspace-Aware Moment-Orthogonalization for Accelerating Memory-Efficient LLM Training | https://arxiv.org/abs/2505.24749 | [] | [] | [] | [] | [] |
2503.00307 | https://paperswithcode.co/api/v1/papers/arxiv/2503.00307?include_resources=true | 200 | true | 45248 | Remasking Discrete Diffusion Models with Inference-Time Scaling | https://arxiv.org/abs/2503.00307 | [
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2504.01002 | https://paperswithcode.co/api/v1/papers/arxiv/2504.01002?include_resources=true | 200 | true | 73762 | Token embeddings violate the manifold hypothesis | https://arxiv.org/abs/2504.01002 | [] | [] | [] | [] | [] |
2506.05872 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05872?include_resources=true | 200 | true | 72212 | Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detection | https://arxiv.org/abs/2506.05872 | [] | [] | [] | [] | [] |
2511.01126 | https://paperswithcode.co/api/v1/papers/arxiv/2511.01126?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.02932 | https://paperswithcode.co/api/v1/papers/arxiv/2512.02932?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.10948 | https://paperswithcode.co/api/v1/papers/arxiv/2506.10948?include_resources=true | 200 | true | 66005 | Execution Guided Line-by-Line Code Generation | https://arxiv.org/abs/2506.10948 | [
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2510.12238 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12238?include_resources=true | 200 | true | 86970 | A Gradient Guided Diffusion Framework for Chance Constrained Programming | https://arxiv.org/abs/2510.12238 | [] | [] | [] | [] | [] |
2412.00744 | https://paperswithcode.co/api/v1/papers/arxiv/2412.00744?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.12779 | https://paperswithcode.co/api/v1/papers/arxiv/2506.12779?include_resources=true | 200 | true | 51121 | From Experts to a Generalist: Toward General Whole-Body Control for Humanoid Robots | https://arxiv.org/abs/2506.12779v2 | [
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2504.06704 | https://paperswithcode.co/api/v1/papers/arxiv/2504.06704?include_resources=true | 200 | true | 73612 | CAT: Circular-Convolutional Attention for Sub-Quadratic Transformers | https://arxiv.org/abs/2504.06704 | [] | [] | [] | [] | [] |
2411.00359 | https://paperswithcode.co/api/v1/papers/arxiv/2411.00359?include_resources=true | 200 | true | 39494 | Constrained Diffusion Implicit Models | https://arxiv.org/abs/2411.00359 | [] | [] | [] | [] | [] |
2502.06398 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06398?include_resources=true | 200 | true | 86596 | Learning Counterfactual Outcomes Under Rank Preservation | https://arxiv.org/abs/2502.06398 | [] | [] | [] | [] | [] |
2507.17030 | https://paperswithcode.co/api/v1/papers/arxiv/2507.17030?include_resources=true | 200 | true | 87262 | CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates | https://arxiv.org/abs/2507.17030 | [] | [] | [] | [] | [] |
2506.21724 | https://paperswithcode.co/api/v1/papers/arxiv/2506.21724?include_resources=true | 200 | true | 51539 | Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning | https://arxiv.org/abs/2506.21724 | [
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2506.08312 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08312?include_resources=true | 200 | true | 86371 | Private Evolution Converges | https://arxiv.org/abs/2506.08312 | [] | [] | [] | [] | [] |
2507.14697 | https://paperswithcode.co/api/v1/papers/arxiv/2507.14697?include_resources=true | 200 | true | 70979 | GTPBD: A Fine-Grained Global Terraced Parcel and Boundary Dataset | https://arxiv.org/abs/2507.14697 | [
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2505.12697 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12697?include_resources=true | 200 | true | 48987 | Towards A Generalist Code Embedding Model Based On Massive Data Synthesis | https://arxiv.org/abs/2505.12697 | [
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"name": "FlagEmbedding",
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2511.22154 | https://paperswithcode.co/api/v1/papers/arxiv/2511.22154?include_resources=true | 200 | true | 64439 | WearVQA: A Visual Question Answering Benchmark for Wearables in Egocentric Authentic Real-world scenarios | https://arxiv.org/abs/2511.22154 | [] | [] | [] | [] | [] |
2505.15952 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15952?include_resources=true | 200 | true | 49348 | VideoGameQA-Bench: Evaluating Vision-Language Models for Video Game Quality Assurance | https://arxiv.org/abs/2505.15952 | [] | [
{
"url": "https://asgaardlab.github.io/videogameqa-bench/",
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2510.16123 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16123?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.13383 | https://paperswithcode.co/api/v1/papers/arxiv/2507.13383?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.15978 | https://paperswithcode.co/api/v1/papers/arxiv/2510.15978?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
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