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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2411.13730 | https://paperswithcode.co/api/v1/papers/arxiv/2411.13730?include_resources=true | 200 | true | 85870 | Replicable Online Learning | https://arxiv.org/abs/2411.13730 | [] | [] | [] | [] | [] |
2505.12585 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12585?include_resources=true | 200 | true | 86674 | Learning Robust Spectral Dynamics for Temporal Domain Generalization | https://arxiv.org/abs/2505.12585 | [] | [] | [] | [] | [] |
2509.17313 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17313?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.10422 | https://paperswithcode.co/api/v1/papers/arxiv/2512.10422?include_resources=true | 200 | true | 63847 | Cooperative Retrieval-Augmented Generation for Question Answering: Mutual Information Exchange and Ranking by Contrasting Layers | https://arxiv.org/abs/2512.10422 | [
{
"url": "https://github.com/meaningful96/CoopRAG",
"owner": "meaningful96",
"name": "CoopRAG",
"stars": 11,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2505.19087 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19087?include_resources=true | 200 | true | 87318 | Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes | https://arxiv.org/abs/2505.19087 | [] | [] | [] | [] | [] |
2505.15781 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15781?include_resources=true | 200 | true | 49326 | dKV-Cache: The Cache for Diffusion Language Models | https://arxiv.org/abs/2505.15781 | [
{
"url": "https://github.com/horseee/dkv-cache",
"owner": "horseee",
"name": "dkv-cache",
"stars": 125,
"is_official": true,
"source": "links_json"
},
{
"url": "https://github.com/alibaba/graph-gpt",
"owner": "alibaba",
"name": "graph-gpt",
"stars": 96,
"is_official":... | [] | [] | [] | [] |
2505.20292 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20292?include_resources=true | 200 | true | 49861 | OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation | https://arxiv.org/abs/2505.20292 | [
{
"url": "https://github.com/pku-yuangroup/consisid",
"owner": "PKU-YuanGroup",
"name": "ConsisID",
"stars": 792,
"is_official": true,
"source": "ai_extraction"
},
{
"url": "https://github.com/pku-yuangroup/opens2v-nexus",
"owner": "PKU-YuanGroup",
"name": "OpenS2V-Nexus",
... | [
{
"url": "https://pku-yuangroup.github.io/OpenS2V-Nexus",
"is_official": true
}
] | [] | [] | [] |
2502.02870 | https://paperswithcode.co/api/v1/papers/arxiv/2502.02870?include_resources=true | 200 | true | 86391 | Uncertainty Quantification with the Empirical Neural Tangent Kernel | https://arxiv.org/abs/2502.02870 | [] | [] | [] | [] | [] |
2503.04363 | https://paperswithcode.co/api/v1/papers/arxiv/2503.04363?include_resources=true | 200 | true | 86242 | Causally Reliable Concept Bottleneck Models | https://arxiv.org/abs/2503.04363 | [] | [] | [] | [] | [] |
2412.06474 | https://paperswithcode.co/api/v1/papers/arxiv/2412.06474?include_resources=true | 200 | true | 41232 | From Uncertainty to Trust: Enhancing Reliability in Vision-Language Models with Uncertainty-Guided Dropout Decoding | https://arxiv.org/abs/2412.06474 | [
{
"url": "https://github.com/kigb/dropoutdecoding",
"owner": "kigb",
"name": "dropoutdecoding",
"stars": 22,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2503.09657 | https://paperswithcode.co/api/v1/papers/arxiv/2503.09657?include_resources=true | 200 | true | 74130 | Týr-the-Pruner: Structural Pruning LLMs via Global Sparsity
Distribution Optimization | https://arxiv.org/abs/2503.09657 | [
{
"url": "https://github.com/AMD-AGI/Tyr-the-Pruner",
"owner": "AMD-AGI",
"name": "Tyr-the-Pruner",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2509.16411 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16411?include_resources=true | 200 | true | 86666 | Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe | https://arxiv.org/abs/2509.16411 | [] | [] | [] | [] | [] |
2509.24748 | https://paperswithcode.co/api/v1/papers/arxiv/2509.24748?include_resources=true | 200 | true | 85763 | Robust Policy Expansion for Offline-to-Online RL under Diverse Data Corruption | https://arxiv.org/abs/2509.24748 | [
{
"url": "https://github.com/felix-thu/rpex",
"owner": "felix-thu",
"name": "rpex",
"stars": 1,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2502.05454 | https://paperswithcode.co/api/v1/papers/arxiv/2502.05454?include_resources=true | 200 | true | 85802 | Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following | https://arxiv.org/abs/2502.05454 | [] | [] | [] | [] | [] |
2506.03133 | https://paperswithcode.co/api/v1/papers/arxiv/2506.03133?include_resources=true | 200 | true | 72314 | PoLAR: Polar-Decomposed Low-Rank Adapter Representation | https://arxiv.org/abs/2506.03133 | [] | [] | [] | [] | [] |
2505.21671 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21671?include_resources=true | 200 | true | 86489 | Adaptive Frontier Exploration on Graphs with Applications to Network-Based Disease Testing | https://arxiv.org/abs/2505.21671 | [] | [] | [] | [] | [] |
2502.13251 | https://paperswithcode.co/api/v1/papers/arxiv/2502.13251?include_resources=true | 200 | true | 44538 | Neural Attention Search | https://arxiv.org/abs/2502.13251 | [] | [] | [] | [] | [] |
2502.00757 | https://paperswithcode.co/api/v1/papers/arxiv/2502.00757?include_resources=true | 200 | true | 43518 | AgentBreeder: Mitigating the AI Safety Impact of Multi-Agent Scaffolds via Self-Improvement | https://arxiv.org/abs/2502.00757v3 | [
{
"url": "https://github.com/j-rosser-uk/agentbreeder",
"owner": "J-Rosser-UK",
"name": "AgentBreeder",
"stars": 9,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2507.07995 | https://paperswithcode.co/api/v1/papers/arxiv/2507.07995?include_resources=true | 200 | true | 71255 | Single-pass Adaptive Image Tokenization for Minimum Program Search | https://arxiv.org/abs/2507.07995 | [] | [] | [] | [] | [] |
2505.21251 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21251?include_resources=true | 200 | true | 87143 | Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework | https://arxiv.org/abs/2505.21251 | [] | [] | [] | [] | [] |
2403.00397 | https://paperswithcode.co/api/v1/papers/arxiv/2403.00397?include_resources=true | 200 | true | 86857 | The Price of Opportunity Fairness in Matroid Allocation Problems | https://arxiv.org/abs/2403.00397 | [] | [] | [] | [] | [] |
2501.19205 | https://paperswithcode.co/api/v1/papers/arxiv/2501.19205?include_resources=true | 200 | true | 75023 | RIGNO: A Graph-based framework for robust and accurate operator learning
for PDEs on arbitrary domains | https://arxiv.org/abs/2501.19205 | [
{
"url": "https://github.com/camlab-ethz/rigno",
"owner": "camlab-ethz",
"name": "rigno",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2509.16588 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16588?include_resources=true | 200 | true | 86258 | SQS: Enhancing Sparse Perception Models via Query-based Splatting in Autonomous Driving | https://arxiv.org/abs/2509.16588 | [] | [] | [] | [] | [] |
2510.15965 | https://paperswithcode.co/api/v1/papers/arxiv/2510.15965?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.16872 | https://paperswithcode.co/api/v1/papers/arxiv/2503.16872?include_resources=true | 200 | true | 87081 | Lie Detector: Unified Backdoor Detection via Cross-Examination Framework | https://arxiv.org/abs/2503.16872 | [] | [] | [] | [] | [] |
2511.00988 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00988?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.13733 | https://paperswithcode.co/api/v1/papers/arxiv/2511.13733?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.24296 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24296?include_resources=true | 200 | true | 87460 | Data Fusion for Partial Identification of Causal Effects | https://arxiv.org/abs/2505.24296 | [] | [] | [] | [] | [] |
2505.21496 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21496?include_resources=true | 200 | true | 49953 | UI-Genie: A Self-Improving Approach for Iteratively Boosting MLLM-based Mobile GUI Agents | https://arxiv.org/abs/2505.21496 | [
{
"url": "https://github.com/euphoria16/ui-genie",
"owner": "Euphoria16",
"name": "UI-Genie",
"stars": 48,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.14125 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14125?include_resources=true | 200 | true | 87274 | Contrastive Consolidation of Top-Down Modulations Achieves Sparsely Supervised Continual Learning | https://arxiv.org/abs/2505.14125 | [] | [] | [] | [] | [] |
2505.21074 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21074?include_resources=true | 200 | true | 85953 | Red-Teaming Text-to-Image Systems by Rule-based Preference Modeling | https://arxiv.org/abs/2505.21074 | [] | [] | [] | [] | [] |
2512.00940 | https://paperswithcode.co/api/v1/papers/arxiv/2512.00940?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.09881 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09881?include_resources=true | 200 | true | 86302 | Leveraging Depth and Language for Open-Vocabulary Domain-Generalized Semantic Segmentation | https://arxiv.org/abs/2506.09881 | [
{
"url": "https://github.com/sy-ch/vireo",
"owner": "sy-ch",
"name": "vireo",
"stars": 28,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2506.23225 | https://paperswithcode.co/api/v1/papers/arxiv/2506.23225?include_resources=true | 200 | true | 71645 | Masked Gated Linear Unit | https://arxiv.org/abs/2506.23225 | [] | [] | [] | [] | [] |
2512.14677 | https://paperswithcode.co/api/v1/papers/arxiv/2512.14677?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.16548 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16548?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.19481 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19481?include_resources=true | 200 | true | 85889 | Win Fast or Lose Slow: Balancing Speed and Accuracy in Latency-Sensitive Decisions of LLMs | https://arxiv.org/abs/2505.19481 | [] | [] | [] | [] | [] |
2412.11060 | https://paperswithcode.co/api/v1/papers/arxiv/2412.11060?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.07978 | https://paperswithcode.co/api/v1/papers/arxiv/2507.07978?include_resources=true | 200 | true | 51823 | Martian World Models: Controllable Video Synthesis with Physically Accurate 3D Reconstructions | https://arxiv.org/abs/2507.07978 | [] | [
{
"url": "https://marsgenai.github.io",
"is_official": true
}
] | [] | [] | [] |
2506.06656 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06656?include_resources=true | 200 | true | 86496 | Rescaled Influence Functions: Accurate Data Attribution in High Dimension | https://arxiv.org/abs/2506.06656 | [] | [] | [] | [] | [] |
2505.18342 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18342?include_resources=true | 200 | true | 85931 | Pose Splatter: A 3D Gaussian Splatting Model for Quantifying Animal Pose and Appearance | https://arxiv.org/abs/2505.18342 | [] | [] | [] | [] | [] |
2505.24630 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24630?include_resources=true | 200 | true | 50248 | The Hallucination Dilemma: Factuality-Aware Reinforcement Learning for Large Reasoning Models | https://arxiv.org/abs/2505.24630 | [
{
"url": "https://github.com/nusnlp/fspo",
"owner": "nusnlp",
"name": "fspo",
"stars": 20,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2512.03678 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03678?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.20604 | https://paperswithcode.co/api/v1/papers/arxiv/2511.20604?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.01863 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01863?include_resources=true | 200 | true | 50409 | Unified Scaling Laws for Compressed Representations | https://arxiv.org/abs/2506.01863 | [] | [] | [] | [] | [] |
2510.18713 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18713?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.09809 | https://paperswithcode.co/api/v1/papers/arxiv/2511.09809?include_resources=true | 200 | true | 54229 | Test-Time Spectrum-Aware Latent Steering for Zero-Shot Generalization in Vision-Language Models | https://arxiv.org/abs/2511.09809 | [
{
"url": "https://github.com/kdafnis/STS",
"owner": "kdafnis",
"name": "STS",
"stars": 4,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2505.21962 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21962?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2410.12609 | https://paperswithcode.co/api/v1/papers/arxiv/2410.12609?include_resources=true | 200 | true | 86972 | Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs | https://arxiv.org/abs/2410.12609 | [] | [] | [] | [] | [] |
2505.20172 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20172?include_resources=true | 200 | true | 85806 | A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation | https://arxiv.org/abs/2505.20172 | [] | [] | [] | [] | [] |
2505.13379 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13379?include_resources=true | 200 | true | 49054 | Thinkless: LLM Learns When to Think | https://arxiv.org/abs/2505.13379 | [
{
"url": "https://github.com/vainf/thinkless",
"owner": "VainF",
"name": "Thinkless",
"stars": 246,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2512.22664 | https://paperswithcode.co/api/v1/papers/arxiv/2512.22664?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.20177 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20177?include_resources=true | 200 | true | 86597 | The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination | https://arxiv.org/abs/2505.20177 | [] | [] | [] | [] | [] |
2602.20296 | https://paperswithcode.co/api/v1/papers/arxiv/2602.20296?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.01300 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01300?include_resources=true | 200 | true | 50373 | ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding | https://arxiv.org/abs/2506.01300 | [] | [] | [] | [] | [] |
2505.20686 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20686?include_resources=true | 200 | true | 72681 | Accelerating RL for LLM Reasoning with Optimal Advantage Regression | https://arxiv.org/abs/2505.20686 | [
{
"url": "https://github.com/zhaolingao/a-po",
"owner": "zhaolingao",
"name": "a-po",
"stars": 41,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2512.03125 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03125?include_resources=true | 200 | true | 54595 | Mitigating Intra- and Inter-modal Forgetting in Continual Learning of Unified Multimodal Models | https://arxiv.org/abs/2512.03125 | [
{
"url": "https://github.com/Christina200/MoDE-official",
"owner": "Christina200",
"name": "MoDE-official",
"stars": 9,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2604.11223 | https://paperswithcode.co/api/v1/papers/arxiv/2604.11223?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.02259 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02259?include_resources=true | 200 | true | 87196 | Stochastically Dominant Peer Prediction | https://arxiv.org/abs/2506.02259 | [] | [] | [] | [] | [] |
2408.08395 | https://paperswithcode.co/api/v1/papers/arxiv/2408.08395?include_resources=true | 200 | true | 86879 | Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback | https://arxiv.org/abs/2408.08395 | [] | [] | [] | [] | [] |
2503.22194 | https://paperswithcode.co/api/v1/papers/arxiv/2503.22194?include_resources=true | 200 | true | 46915 | ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation | https://arxiv.org/abs/2503.22194 | [] | [
{
"url": "https://origen2025.github.io/",
"is_official": true
}
] | [] | [] | [] |
2412.03526 | https://paperswithcode.co/api/v1/papers/arxiv/2412.03526?include_resources=true | 200 | true | 40987 | Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos | https://arxiv.org/abs/2412.03526v2 | [] | [
{
"url": "https://research.nvidia.com/labs/toronto-ai/bullet-timer/",
"is_official": true
}
] | [] | [] | [] |
2506.01084 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01084?include_resources=true | 200 | true | 50361 | zip2zip: Inference-Time Adaptive Vocabularies for Language Models via Token Compression | https://arxiv.org/abs/2506.01084 | [
{
"url": "https://github.com/epfl-dlab/zip2zip",
"owner": "epfl-dlab",
"name": "zip2zip",
"stars": 10,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2502.16816 | https://paperswithcode.co/api/v1/papers/arxiv/2502.16816?include_resources=true | 200 | true | 86704 | Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learning | https://arxiv.org/abs/2502.16816 | [] | [] | [] | [] | [] |
2504.09629 | https://paperswithcode.co/api/v1/papers/arxiv/2504.09629?include_resources=true | 200 | true | 47616 | Quantization Error Propagation: Revisiting Layer-Wise Post-Training Quantization | https://arxiv.org/abs/2504.09629v2 | [] | [] | [] | [] | [] |
2506.12693 | https://paperswithcode.co/api/v1/papers/arxiv/2506.12693?include_resources=true | 200 | true | 87309 | Zero-shot Denoising via Neural Compression: Theoretical and algorithmic framework | https://arxiv.org/abs/2506.12693 | [] | [] | [] | [] | [] |
2511.12658 | https://paperswithcode.co/api/v1/papers/arxiv/2511.12658?include_resources=true | 200 | true | 64955 | Toward Real-world Text Image Forgery Localization: Structured and Interpretable Data Synthesis | https://arxiv.org/abs/2511.12658 | [
{
"url": "https://github.com/ZeqinYu/FSTS",
"owner": "ZeqinYu",
"name": "FSTS",
"stars": 5,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2407.10000 | https://paperswithcode.co/api/v1/papers/arxiv/2407.10000?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.21322 | https://paperswithcode.co/api/v1/papers/arxiv/2503.21322?include_resources=true | 200 | true | 46844 | HyperGraphRAG: Retrieval-Augmented Generation with Hypergraph-Structured Knowledge Representation | https://arxiv.org/abs/2503.21322 | [
{
"url": "https://github.com/lhrlab/hypergraphrag",
"owner": "LHRLAB",
"name": "HyperGraphRAG",
"stars": 298,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2512.12567 | https://paperswithcode.co/api/v1/papers/arxiv/2512.12567?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.12220 | https://paperswithcode.co/api/v1/papers/arxiv/2506.12220?include_resources=true | 200 | true | 86577 | Two heads are better than one: simulating large transformers with small ones | https://arxiv.org/abs/2506.12220 | [] | [] | [] | [] | [] |
2510.01303 | https://paperswithcode.co/api/v1/papers/arxiv/2510.01303?include_resources=true | 200 | true | 87387 | Low Rank Gradients and Where to Find Them | https://arxiv.org/abs/2510.01303 | [] | [] | [] | [] | [] |
2406.18202 | https://paperswithcode.co/api/v1/papers/arxiv/2406.18202?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.15201 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15201?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.09257 | https://paperswithcode.co/api/v1/papers/arxiv/2502.09257?include_resources=true | 200 | true | 86811 | Bandit Multiclass List Classification | https://arxiv.org/abs/2502.09257 | [] | [] | [] | [] | [] |
2502.01384 | https://paperswithcode.co/api/v1/papers/arxiv/2502.01384?include_resources=true | 200 | true | 43564 | Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods | https://arxiv.org/abs/2502.01384v2 | [
{
"url": "https://github.com/ozekri/sepo",
"owner": "ozekri",
"name": "SEPO",
"stars": 31,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2511.22429 | https://paperswithcode.co/api/v1/papers/arxiv/2511.22429?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2509.17439 | https://paperswithcode.co/api/v1/papers/arxiv/2509.17439?include_resources=true | 200 | true | 86443 | SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding | https://arxiv.org/abs/2509.17439 | [] | [] | [] | [] | [] |
2601.09860 | https://paperswithcode.co/api/v1/papers/arxiv/2601.09860?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.21635 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21635?include_resources=true | 200 | true | 85765 | Object Concepts Emerge from Motion | https://arxiv.org/abs/2505.21635 | [] | [] | [] | [] | [] |
2502.19049 | https://paperswithcode.co/api/v1/papers/arxiv/2502.19049?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.10446 | https://paperswithcode.co/api/v1/papers/arxiv/2505.10446?include_resources=true | 200 | true | 48774 | Reinforcing the Diffusion Chain of Lateral Thought with Diffusion Language Models | https://arxiv.org/abs/2505.10446v2 | [] | [] | [] | [] | [] |
2505.18524 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18524?include_resources=true | 200 | true | 49623 | metaTextGrad: Automatically optimizing language model optimizers | https://arxiv.org/abs/2505.18524 | [
{
"url": "https://github.com/zou-group/metatextgrad",
"owner": "zou-group",
"name": "metatextgrad",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://github.com/zou-group/metatextgrad",
"is_official": true
}
] | [] | [] | [] |
2410.10101 | https://paperswithcode.co/api/v1/papers/arxiv/2410.10101?include_resources=true | 200 | true | 86000 | Learning Linear Attention in Polynomial Time | https://arxiv.org/abs/2410.10101 | [] | [] | [] | [] | [] |
2505.20081 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20081?include_resources=true | 200 | true | 49809 | Inference-time Alignment in Continuous Space | https://arxiv.org/abs/2505.20081 | [
{
"url": "https://github.com/yuanyige/sea",
"owner": "yuanyige",
"name": "SEA",
"stars": 1,
"is_official": true,
"source": "ai_extraction"
},
{
"url": "https://github.com/sea-neurips/code",
"owner": "sea-neurips",
"name": "code",
"stars": 0,
"is_official": true,
"... | [] | [] | [] | [] |
2510.09537 | https://paperswithcode.co/api/v1/papers/arxiv/2510.09537?include_resources=true | 200 | true | 86677 | FLOWING: Implicit Neural Flows for Structure-Preserving Morphing | https://arxiv.org/abs/2510.09537 | [] | [
{
"url": "https://schardong.github.io/flowing/",
"is_official": true
}
] | [] | [] | [] |
2510.17858 | https://paperswithcode.co/api/v1/papers/arxiv/2510.17858?include_resources=true | 200 | true | 66384 | Shortcutting Pre-trained Flow Matching Diffusion Models is Almost Free
Lunch | https://arxiv.org/abs/2510.17858 | [] | [] | [] | [] | [] |
2509.15607 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15607?include_resources=true | 200 | true | 68161 | PRIMT: Preference-based Reinforcement Learning with Multimodal Feedback and Trajectory Synthesis from Foundation Models | https://arxiv.org/abs/2509.15607 | [] | [] | [] | [] | [] |
2411.19466 | https://paperswithcode.co/api/v1/papers/arxiv/2411.19466?include_resources=true | 200 | true | 40684 | ForgerySleuth: Empowering Multimodal Large Language Models for Image Manipulation Detection | https://arxiv.org/abs/2411.19466 | [
{
"url": "https://github.com/sunzhihao18/forgerysleuth",
"owner": "sunzhihao18",
"name": "ForgerySleuth",
"stars": 28,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2505.21318 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21318?include_resources=true | 200 | true | 49935 | Beyond Chemical QA: Evaluating LLM's Chemical Reasoning with Modular Chemical Operations | https://arxiv.org/abs/2505.21318 | [] | [] | [] | [] | [] |
2507.09424 | https://paperswithcode.co/api/v1/papers/arxiv/2507.09424?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.07364 | https://paperswithcode.co/api/v1/papers/arxiv/2502.07364?include_resources=true | 200 | true | 86477 | Effects of Dropout on Performance in Long-range Graph Learning Tasks | https://arxiv.org/abs/2502.07364 | [] | [] | [] | [] | [] |
2510.20877 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20877?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.16406 | https://paperswithcode.co/api/v1/papers/arxiv/2506.16406?include_resources=true | 200 | true | 51296 | Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights | https://arxiv.org/abs/2506.16406 | [
{
"url": "https://github.com/jerryliang24/drag-and-drop-llms",
"owner": "jerryliang24",
"name": "Drag-and-Drop-LLMs",
"stars": 139,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://jerryliang24.github.io/DnD/",
"is_official": true
},
{
"url": "https://jerryliang24.github.io/DnD",
"is_official": true
}
] | [] | [] | [] |
2509.16629 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16629?include_resources=true | 200 | true | 86026 | Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features | https://arxiv.org/abs/2509.16629 | [
{
"url": "https://github.com/catchxu/cape",
"owner": "catchxu",
"name": "cape",
"stars": 1,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2503.03480 | https://paperswithcode.co/api/v1/papers/arxiv/2503.03480?include_resources=true | 200 | true | 45485 | SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning | https://arxiv.org/abs/2503.03480v2 | [
{
"url": "https://github.com/PKU-Alignment/SafeVLA",
"owner": "PKU-Alignment",
"name": "SafeVLA",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://pku-safevla.github.io/",
"is_official": true
},
{
"url": "https://pku-safevla.github.io",
"is_official": true
}
] | [] | [] | [] |
2512.00862 | https://paperswithcode.co/api/v1/papers/arxiv/2512.00862?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2507.15062 | https://paperswithcode.co/api/v1/papers/arxiv/2507.15062?include_resources=true | 200 | true | 70955 | Touch in the Wild: Learning Fine-Grained Manipulation with a Portable
Visuo-Tactile Gripper | https://arxiv.org/abs/2507.15062 | [
{
"url": "https://github.com/YolandaXinyueZhu/touch_in_the_wild",
"owner": "YolandaXinyueZhu",
"name": "touch_in_the_wild",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://binghao-huang.github.io/touch_in_the_wild/",
"is_official": true
}
] | [] | [] | [] |
2505.11383 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11383?include_resources=true | 200 | true | 73029 | Dynam3D: Dynamic Layered 3D Tokens Empower VLM for Vision-and-Language
Navigation | https://arxiv.org/abs/2505.11383 | [
{
"url": "https://github.com/MrZihan/Dynam3D",
"owner": "MrZihan",
"name": "Dynam3D",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://neurips.cc/virtual/2025/loc/san-diego/oral/115716",
"is_official": true
}
] | [] | [] | [] |
2410.17770 | https://paperswithcode.co/api/v1/papers/arxiv/2410.17770?include_resources=true | 200 | true | 85732 | Small Singular Values Matter: A Random Matrix Analysis of Transformer Models | https://arxiv.org/abs/2410.17770 | [] | [] | [] | [] | [] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.