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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2511.06138 | https://paperswithcode.co/api/v1/papers/arxiv/2511.06138?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.12494 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12494?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.04838 | https://paperswithcode.co/api/v1/papers/arxiv/2510.04838?include_resources=true | 200 | true | 87477 | Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation | https://arxiv.org/abs/2510.04838 | [] | [] | [] | [] | [] |
2512.03000 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03000?include_resources=true | 200 | true | 54570 | DynamicVerse: A Physically-Aware Multimodal Framework for 4D World Modeling | https://arxiv.org/abs/2512.03000 | [
{
"url": "https://github.com/Dynamics-X/DynamicVerse",
"owner": "Dynamics-X",
"name": "DynamicVerse",
"stars": 100,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://dynamic-verse.github.io/",
"is_official": true
}
] | [] | [] | [] |
2510.13418 | https://paperswithcode.co/api/v1/papers/arxiv/2510.13418?include_resources=true | 200 | true | 86283 | Reinforcement Learning Meets Masked Generative Models: Mask-GRPO for Text-to-Image Generation | https://arxiv.org/abs/2510.13418 | [
{
"url": "https://github.com/xingzhejun/mask-grpo",
"owner": "xingzhejun",
"name": "mask-grpo",
"stars": 12,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2507.02937 | https://paperswithcode.co/api/v1/papers/arxiv/2507.02937?include_resources=true | 200 | true | 86166 | FoGE: Fock Space inspired encoding for graph prompting | https://arxiv.org/abs/2507.02937 | [] | [] | [] | [] | [] |
2602.02213 | https://paperswithcode.co/api/v1/papers/arxiv/2602.02213?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.09378 | https://paperswithcode.co/api/v1/papers/arxiv/2507.09378?include_resources=true | 200 | true | 86871 | Context-Aware Regularization with Markovian Integration for Attention-Based Nucleotide Analysis | https://arxiv.org/abs/2507.09378 | [] | [] | [] | [] | [] |
2506.15673 | https://paperswithcode.co/api/v1/papers/arxiv/2506.15673?include_resources=true | 200 | true | 51266 | UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting | https://arxiv.org/abs/2506.15673 | [] | [] | [] | [] | [] |
2410.06324 | https://paperswithcode.co/api/v1/papers/arxiv/2410.06324?include_resources=true | 200 | true | 87133 | Differentiation Through Black-Box Quadratic Programming Solvers | https://arxiv.org/abs/2410.06324 | [] | [] | [] | [] | [] |
2506.10982 | https://paperswithcode.co/api/v1/papers/arxiv/2506.10982?include_resources=true | 200 | true | 86961 | Rethinking Losses for Diffusion Bridge Samplers | https://arxiv.org/abs/2506.10982 | [] | [] | [] | [] | [] |
2505.20460 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20460?include_resources=true | 200 | true | 72692 | DIPO: Dual-State Images Controlled Articulated Object Generation Powered
by Diverse Data | https://arxiv.org/abs/2505.20460 | [] | [] | [] | [] | [] |
2510.03578 | https://paperswithcode.co/api/v1/papers/arxiv/2510.03578?include_resources=true | 200 | true | 86068 | Latent Mixture of Symmetries for Sample-Efficient Dynamic Learning | https://arxiv.org/abs/2510.03578 | [] | [] | [] | [] | [] |
2505.10610 | https://paperswithcode.co/api/v1/papers/arxiv/2505.10610?include_resources=true | 200 | true | 48793 | MMLongBench: Benchmarking Long-Context Vision-Language Models Effectively and Thoroughly | https://arxiv.org/abs/2505.10610 | [
{
"url": "https://github.com/edinburghnlp/mmlongbench",
"owner": "EdinburghNLP",
"name": "MMLongBench",
"stars": 170,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://zhaowei-wang-nlp.github.io/MMLongBench-page/",
"is_official": true
}
] | [] | [] | [] |
2508.13113 | https://paperswithcode.co/api/v1/papers/arxiv/2508.13113?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.18090 | https://paperswithcode.co/api/v1/papers/arxiv/2509.18090?include_resources=true | 200 | true | 52946 | GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface
Reconstruction | https://arxiv.org/abs/2509.18090 | [
{
"url": "https://github.com/fictionarry/geosvr",
"owner": "Fictionarry",
"name": "GeoSVR",
"stars": 151,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://fictionarry.github.io/GeoSVR-project/",
"is_official": true
}
] | [] | [] | [] |
2506.05530 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05530?include_resources=true | 200 | true | 86393 | Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum | https://arxiv.org/abs/2506.05530 | [] | [] | [] | [] | [] |
2602.08377 | https://paperswithcode.co/api/v1/papers/arxiv/2602.08377?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.17423 | https://paperswithcode.co/api/v1/papers/arxiv/2505.17423?include_resources=true | 200 | true | 49519 | VIBE: Video-to-Text Information Bottleneck Evaluation for TL;DR | https://arxiv.org/abs/2505.17423 | [
{
"url": "https://github.com/utaustin-swarmlab/task-aware-tldr-public",
"owner": "utaustin-swarmlab",
"name": "task-aware-tldr-public",
"stars": 2,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2502.07503 | https://paperswithcode.co/api/v1/papers/arxiv/2502.07503?include_resources=true | 200 | true | 87392 | Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems | https://arxiv.org/abs/2502.07503 | [] | [] | [] | [] | [] |
2506.00880 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00880?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.20875 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20875?include_resources=true | 200 | true | 72666 | Trans-EnV: A Framework for Evaluating the Linguistic Robustness of LLMs
Against English Varieties | https://arxiv.org/abs/2505.20875 | [
{
"url": "https://github.com/jiyounglee-0523/TransEnV",
"owner": "jiyounglee-0523",
"name": "TransEnV",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://huggingface.co/collections/jiyounglee0523/transenv-681eadb3c0c8cf363b363fb1",
"is_official": true
}
] | [] | [] | [] |
2510.18360 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18360?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.23946 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23946?include_resources=true | 200 | true | 86939 | Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve | https://arxiv.org/abs/2505.23946 | [] | [] | [] | [] | [] |
2502.04380 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04380?include_resources=true | 200 | true | 43779 | Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data | https://arxiv.org/abs/2502.04380 | [
{
"url": "https://github.com/modelscope/data-juicer",
"owner": "modelscope",
"name": "data-juicer",
"stars": 5640,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.22601 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22601?include_resources=true | 200 | true | 86397 | Machine Unlearning under Overparameterization | https://arxiv.org/abs/2505.22601 | [] | [] | [] | [] | [] |
2506.09278 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09278?include_resources=true | 200 | true | 50916 | UFM: A Simple Path towards Unified Dense Correspondence with Flow | https://arxiv.org/abs/2506.09278 | [
{
"url": "https://github.com/uniflowmatch/ufm",
"owner": "UniFlowMatch",
"name": "UFM",
"stars": 278,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://uniflowmatch.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.12049 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12049?include_resources=true | 200 | true | 86992 | Beyond Scalar Rewards: An Axiomatic Framework for Lexicographic MDPs | https://arxiv.org/abs/2505.12049 | [] | [] | [] | [] | [] |
2505.06371 | https://paperswithcode.co/api/v1/papers/arxiv/2505.06371?include_resources=true | 200 | true | 48586 | The ML.ENERGY Benchmark: Toward Automated Inference Energy Measurement and Optimization | https://arxiv.org/abs/2505.06371 | [
{
"url": "https://github.com/ml-energy/leaderboard",
"owner": "ml-energy",
"name": "leaderboard",
"stars": 3,
"is_official": true,
"source": "links_json"
},
{
"url": "https://github.com/ml-energy/zeus",
"owner": "ml-energy",
"name": "zeus",
"stars": 325,
"is_official"... | [
{
"url": "https://ml.energy/leaderboard",
"is_official": true
}
] | [] | [] | [] |
2510.18680 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18680?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.12430 | https://paperswithcode.co/api/v1/papers/arxiv/2502.12430?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.07501 | https://paperswithcode.co/api/v1/papers/arxiv/2510.07501?include_resources=true | 200 | true | 86419 | Evaluating and Learning Optimal Dynamic Treatment Regimes under Truncation by Death | https://arxiv.org/abs/2510.07501 | [] | [] | [] | [] | [] |
2411.12155 | https://paperswithcode.co/api/v1/papers/arxiv/2411.12155?include_resources=true | 200 | true | 40151 | Coarse-to-fine Q-Network with Action Sequence for Data-Efficient Robot Learning | https://arxiv.org/abs/2411.12155v4 | [] | [
{
"url": "https://younggyo.me/cqn-as/",
"is_official": true
}
] | [] | [] | [] |
2410.02615 | https://paperswithcode.co/api/v1/papers/arxiv/2410.02615?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.07447 | https://paperswithcode.co/api/v1/papers/arxiv/2509.07447?include_resources=true | 200 | true | 68590 | In the Eye of MLLM: Benchmarking Egocentric Video Intent Understanding
with Gaze-Guided Prompting | https://arxiv.org/abs/2509.07447 | [
{
"url": "https://github.com/taiyi98/EgoGazeVQA",
"owner": "taiyi98",
"name": "EgoGazeVQA",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2511.11750 | https://paperswithcode.co/api/v1/papers/arxiv/2511.11750?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.22853 | https://paperswithcode.co/api/v1/papers/arxiv/2511.22853?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.00539 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00539?include_resources=true | 200 | true | 50322 | ARIA: Training Language Agents with Intention-Driven Reward Aggregation | https://arxiv.org/abs/2506.00539v2 | [
{
"url": "https://github.com/rhyang2021/aria",
"owner": "rhyang2021",
"name": "ARIA",
"stars": 25,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://aria-agent.github.io/",
"is_official": true
},
{
"url": "https://aria-agent.github.io",
"is_official": true
}
] | [] | [] | [] |
2507.12508 | https://paperswithcode.co/api/v1/papers/arxiv/2507.12508?include_resources=true | 200 | true | 51933 | MindJourney: Test-Time Scaling with World Models for Spatial Reasoning | https://arxiv.org/abs/2507.12508 | [
{
"url": "https://github.com/umass-embodied-agi/mindjourney",
"owner": "UMass-Embodied-AGI",
"name": "MindJourney",
"stars": 118,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://umass-embodied-agi.github.io/MindJourney/",
"is_official": true
}
] | [] | [] | [] |
2506.08708 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08708?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.23725 | https://paperswithcode.co/api/v1/papers/arxiv/2506.23725?include_resources=true | 200 | true | 71613 | PAC Bench: Do Foundation Models Understand Prerequisites for Executing
Manipulation Policies? | https://arxiv.org/abs/2506.23725 | [] | [
{
"url": "https://pacbench.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.12672 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12672?include_resources=true | 200 | true | 86581 | TransferTraj: A Vehicle Trajectory Learning Model for Region and Task Transferability | https://arxiv.org/abs/2505.12672 | [] | [] | [] | [] | [] |
2510.04770 | https://paperswithcode.co/api/v1/papers/arxiv/2510.04770?include_resources=true | 200 | true | 86502 | Beyond the Seen: Bounded Distribution Estimation for Open-Vocabulary Learning | https://arxiv.org/abs/2510.04770 | [] | [] | [] | [] | [] |
2511.12764 | https://paperswithcode.co/api/v1/papers/arxiv/2511.12764?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.06870 | https://paperswithcode.co/api/v1/papers/arxiv/2512.06870?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.20348 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20348?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.20762 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20762?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.19646 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19646?include_resources=true | 200 | true | 87053 | Energy-based generator matching: A neural sampler for general state space | https://arxiv.org/abs/2505.19646 | [] | [] | [] | [] | [] |
2506.14763 | https://paperswithcode.co/api/v1/papers/arxiv/2506.14763?include_resources=true | 200 | true | 86634 | RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skills | https://arxiv.org/abs/2506.14763 | [] | [] | [] | [] | [] |
2505.16400 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16400?include_resources=true | 200 | true | 49402 | AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning | https://arxiv.org/abs/2505.16400 | [] | [
{
"url": "https://huggingface.co/nvidia/AceReason-Nemotron-14B",
"is_official": true
}
] | [] | [] | [] |
2510.18467 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18467?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.27338 | https://paperswithcode.co/api/v1/papers/arxiv/2510.27338?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.09714 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09714?include_resources=true | 200 | true | 86380 | Auto-Compressing Networks | https://arxiv.org/abs/2506.09714 | [] | [] | [] | [] | [] |
2506.06259 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06259?include_resources=true | 200 | true | 87403 | An Optimized Franz-Parisi Criterion and its Equivalence with SQ Lower Bounds | https://arxiv.org/abs/2506.06259 | [] | [] | [] | [] | [] |
2506.09612 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09612?include_resources=true | 200 | true | 72073 | Consistent Story Generation: Unlocking the Potential of Zigzag Sampling | https://arxiv.org/abs/2506.09612 | [
{
"url": "https://github.com/Mingxiao-Li/Asymmetry-Zigzag-StoryDiffusion",
"owner": "Mingxiao-Li",
"name": "Asymmetry-Zigzag-StoryDiffusion",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2510.20800 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20800?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.05782 | https://paperswithcode.co/api/v1/papers/arxiv/2510.05782?include_resources=true | 200 | true | 86379 | Mysteries of the Deep: Role of Intermediate Representations in Out of Distribution Detection | https://arxiv.org/abs/2510.05782 | [] | [] | [] | [] | [] |
2506.08249 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08249?include_resources=true | 200 | true | 50837 | RADAR: Benchmarking Language Models on Imperfect Tabular Data | https://arxiv.org/abs/2506.08249 | [
{
"url": "https://github.com/kenqgu/radar",
"owner": "kenqgu",
"name": "radar",
"stars": 9,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.15818 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15818?include_resources=true | 200 | true | 86261 | InstructSAM: A Training-free Framework for Instruction-Oriented Remote Sensing Object Recognition | https://arxiv.org/abs/2505.15818 | [] | [] | [] | [] | [] |
2505.23579 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23579?include_resources=true | 200 | true | 50119 | BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model | https://arxiv.org/abs/2505.23579 | [
{
"url": "https://github.com/bowang-lab/bioreason",
"owner": "bowang-lab",
"name": "BioReason",
"stars": 341,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.09922 | https://paperswithcode.co/api/v1/papers/arxiv/2505.09922?include_resources=true | 200 | true | 86926 | Improving the Euclidean Diffusion Generation of Manifold Data by Mitigating Score Function Singularity | https://arxiv.org/abs/2505.09922 | [] | [] | [] | [] | [] |
2505.23949 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23949?include_resources=true | 200 | true | 86531 | TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks | https://arxiv.org/abs/2505.23949 | [] | [] | [] | [] | [] |
2512.03014 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03014?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.23173 | https://paperswithcode.co/api/v1/papers/arxiv/2509.23173?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.06254 | https://paperswithcode.co/api/v1/papers/arxiv/2510.06254?include_resources=true | 200 | true | 86314 | Enhanced Self-Distillation Framework for Efficient Spiking Neural Network Training | https://arxiv.org/abs/2510.06254 | [
{
"url": "https://github.com/intelli-chip-lab/enhanced-self-distillation-framework-for-snn",
"owner": "intelli-chip-lab",
"name": "enhanced-self-distillation-framework-for-snn",
"stars": 7,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2509.25989 | https://paperswithcode.co/api/v1/papers/arxiv/2509.25989?include_resources=true | 200 | true | 86220 | Towards Reliable and Holistic Visual In-Context Learning Prompt Selection | https://arxiv.org/abs/2509.25989 | [] | [] | [] | [] | [] |
2506.03179 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03179?include_resources=true | 200 | true | 72546 | Vid-SME: Membership Inference Attacks against Large Video Understanding Models | https://arxiv.org/abs/2506.03179 | [] | [] | [] | [] | [] |
2509.15188 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15188?include_resources=true | 200 | true | 65934 | Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning | https://arxiv.org/abs/2509.15188 | [] | [] | [] | [] | [] |
2510.07924 | https://paperswithcode.co/api/v1/papers/arxiv/2510.07924?include_resources=true | 200 | true | 87437 | Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers | https://arxiv.org/abs/2510.07924 | [] | [] | [] | [] | [] |
2510.20615 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20615?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.20745 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20745?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.23868 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23868?include_resources=true | 200 | true | 86773 | Noise-Robustness Through Noise: Asymmetric LoRA Adaption with Poisoning Expert | https://arxiv.org/abs/2505.23868 | [] | [] | [] | [] | [] |
2510.19270 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19270?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.00573 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00573?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.03075 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03075?include_resources=true | 200 | true | 86969 | Agnostic Learning under Targeted Poisoning: Optimal Rates and the Role of Randomness | https://arxiv.org/abs/2506.03075 | [] | [] | [] | [] | [] |
2502.06536 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06536?include_resources=true | 200 | true | 86191 | Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions | https://arxiv.org/abs/2502.06536 | [] | [] | [] | [] | [] |
2509.24734 | https://paperswithcode.co/api/v1/papers/arxiv/2509.24734?include_resources=true | 200 | true | 85942 | A TRIANGLE Enables Multimodal Alignment Beyond Cosine Similarity | https://arxiv.org/abs/2509.24734 | [] | [] | [] | [] | [] |
2502.16292 | https://paperswithcode.co/api/v1/papers/arxiv/2502.16292?include_resources=true | 200 | true | 86474 | Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms | https://arxiv.org/abs/2502.16292 | [] | [] | [] | [] | [] |
2511.00328 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00328?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2504.10637 | https://paperswithcode.co/api/v1/papers/arxiv/2504.10637?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.06521 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06521?include_resources=true | 200 | true | 86613 | Sharp Gap-Dependent Variance-Aware Regret Bounds for Tabular MDPs | https://arxiv.org/abs/2506.06521 | [] | [] | [] | [] | [] |
2506.15933 | https://paperswithcode.co/api/v1/papers/arxiv/2506.15933?include_resources=true | 200 | true | 87031 | CORAL: Disentangling Latent Representations in Long-Tailed Diffusion | https://arxiv.org/abs/2506.15933 | [] | [] | [] | [] | [] |
2510.03548 | https://paperswithcode.co/api/v1/papers/arxiv/2510.03548?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.02829 | https://paperswithcode.co/api/v1/papers/arxiv/2505.02829?include_resources=true | 200 | true | 48416 | LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery | https://arxiv.org/abs/2505.02829 | [
{
"url": "https://github.com/lisat-bair/LISAt_code",
"owner": "lisat-bair",
"name": "LISAt_code",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://lisat-bair.github.io/LISAt/",
"is_official": true
}
] | [] | [] | [] |
2505.18948 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18948?include_resources=true | 200 | true | 87044 | Exact Expressive Power of Transformers with Padding | https://arxiv.org/abs/2505.18948 | [] | [] | [] | [] | [] |
2511.05095 | https://paperswithcode.co/api/v1/papers/arxiv/2511.05095?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.02882 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02882?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.15155 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15155?include_resources=true | 200 | true | 87468 | Self-Improving Embodied Foundation Models | https://arxiv.org/abs/2509.15155 | [] | [
{
"url": "https://self-improving-efms.github.io/",
"is_official": true
}
] | [] | [] | [] |
2506.20601 | https://paperswithcode.co/api/v1/papers/arxiv/2506.20601?include_resources=true | 200 | true | 51468 | Video Perception Models for 3D Scene Synthesis | https://arxiv.org/abs/2506.20601 | [] | [
{
"url": "https://vipscene.github.io",
"is_official": true
}
] | [] | [] | [] |
2510.13665 | https://paperswithcode.co/api/v1/papers/arxiv/2510.13665?include_resources=true | 200 | true | 87393 | Axial Neural Networks for Dimension-Free Foundation Models | https://arxiv.org/abs/2510.13665 | [] | [] | [] | [] | [] |
2508.00887 | https://paperswithcode.co/api/v1/papers/arxiv/2508.00887?include_resources=true | 200 | true | 87471 | FRAM: Frobenius-Regularized Assignment Matching with Mixed-Precision Computing | https://arxiv.org/abs/2508.00887 | [] | [] | [] | [] | [] |
2502.14739 | https://paperswithcode.co/api/v1/papers/arxiv/2502.14739?include_resources=true | 200 | true | 44677 | SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines | https://arxiv.org/abs/2502.14739v4 | [] | [
{
"url": "https://supergpqa.github.io/",
"is_official": true
}
] | [] | [] | [] |
2502.11583 | https://paperswithcode.co/api/v1/papers/arxiv/2502.11583?include_resources=true | 200 | true | 74654 | Distributional Autoencoders Know the Score | https://arxiv.org/abs/2502.11583 | [
{
"url": "https://github.com/andleb/DistributionalAutoencodersScore",
"owner": "andleb",
"name": "DistributionalAutoencodersScore",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://neurips.cc/virtual/2025/poster/119870",
"is_official": true
}
] | [] | [] | [] |
2506.01599 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01599?include_resources=true | 200 | true | 87447 | Connecting Neural Models Latent Geometries with Relative Geodesic Representations | https://arxiv.org/abs/2506.01599 | [] | [] | [] | [] | [] |
2505.20993 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20993?include_resources=true | 200 | true | 72661 | Who Reasons in the Large Language Models? | https://arxiv.org/abs/2505.20993 | [] | [] | [] | [] | [] |
2407.11550 | https://paperswithcode.co/api/v1/papers/arxiv/2407.11550?include_resources=true | 200 | true | 66345 | Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference | https://arxiv.org/abs/2407.11550 | [] | [] | [] | [] | [] |
2503.20815 | https://paperswithcode.co/api/v1/papers/arxiv/2503.20815?include_resources=true | 200 | true | 86208 | D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction | https://arxiv.org/abs/2503.20815 | [] | [] | [] | [] | [] |
2506.06522 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06522?include_resources=true | 200 | true | 72187 | Fixing It in Post: A Comparative Study of LLM Post-Training Data Quality
and Model Performance | https://arxiv.org/abs/2506.06522 | [] | [] | [] | [] | [] |
2511.02419 | https://paperswithcode.co/api/v1/papers/arxiv/2511.02419?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2603.07006 | https://paperswithcode.co/api/v1/papers/arxiv/2603.07006?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.