{"url":"/ran/3","feed":"ran","feed_label":"Code that ran","page":3,"n_pages":10,"per_stream_per_page":15,"claim":"Per-sample execution status on synthesized fixtures; 'ran' is not a correctness claim about the paper.","sample_gap":{"source":"syntology-graph","read_at":"2026-09-24T18:15:14+00:00","samples":294260,"samples_ran":127244,"samples_unverified":167016,"papers_harvested":51887,"papers_ran":38943,"papers_harvested_nothing_ran":12944,"sample":"one function or class; identical code under several papers counted once"},"streams":{"post_freeze":{"source":"syntology-graph","read_at":"2026-09-24T18:15:14+00:00","order":"arXiv id descending","dates":"arXiv's metadata (CC0) where held; otherwise month_from_arxiv_id","n_with_arxiv_metadata":5105,"first":31,"last":45,"total":5105,"n_in_feed":150,"excluded":{"no_yymm_arxiv_id":0},"cards":[{"kind":"post","source":"syntology-graph","title":"Different Changes Require Different Reasoning: Change-Type-Specialized Experts for Robust Change Captioning","url":"/paper/arxiv-2609-01136","arxiv_id":"2609.01136","date":"2026-09-01","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/VisualAIKHU/MEDIC","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":8,"n_ran":1,"n_unverified":7,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":8}},{"kind":"post","source":"syntology-graph","title":"Modelpedia: A Catalog of Model Findings for the Meta-Science of AI","url":"/paper/arxiv-2609-01090","arxiv_id":"2609.01090","date":"2026-09-01","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/tatsu-lab/stanford_alpaca","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":4,"n_ran":4,"n_unverified":0,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"post","source":"syntology-graph","title":"StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?","url":"/paper/arxiv-2609-00787","arxiv_id":"2609.00787","date":"2026-09-01","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/thunlp/StudyBench","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":26,"n_ran":1,"n_unverified":25,"n_ran_honours":0,"n_ran_violates":1,"n_pointer_only_for_licence":26}},{"kind":"post","source":"syntology-graph","title":"MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks","url":"/paper/arxiv-2609-00696","arxiv_id":"2609.00696","date":"2026-09-01","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/ZiyanLiu16/MUGEN","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":6,"n_ran":1,"n_unverified":5,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":6}},{"kind":"post","source":"syntology-graph","title":"Beyond Language Priors: Diagnosing and Fixing Visual-Origin Hallucinations in Multimodal LLM","url":"/paper/arxiv-2609-00231","arxiv_id":"2609.00231","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/zxp555/ACFT_MM26","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":8,"n_ran":8,"n_unverified":0,"n_ran_honours":1,"n_ran_violates":1,"n_pointer_only_for_licence":8}},{"kind":"post","source":"syntology-graph","title":"Faster Than Flash: Exploiting Attention Sparsity for Efficient Long-Context Decoding","url":"/paper/arxiv-2609-00097","arxiv_id":"2609.00097","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/qluoluo/faster-flash-decoding","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":8,"n_ran":2,"n_unverified":6,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"post","source":"syntology-graph","title":"Driving on Memory","url":"/paper/arxiv-2608-31029","arxiv_id":"2608.31029","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/boschresearch/MemoryDrivoR","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":3,"n_ran":2,"n_unverified":1,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":3}},{"kind":"post","source":"syntology-graph","title":"UFPR-PEs: A Brazilian Face Recognition Benchmark with Self-Declared Race/Color Labels","url":"/paper/arxiv-2608-30688","arxiv_id":"2608.30688","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/UFPR-IPASP-PR/UFPR-PEs","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":15,"n_ran":2,"n_unverified":13,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":15}},{"kind":"post","source":"syntology-graph","title":"Learning Materials Properties from Scarce Labels and Unlabeled Crystals","url":"/paper/arxiv-2608-30682","arxiv_id":"2608.30682","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/littlepeachs/SemiMat","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":9,"n_ran":1,"n_unverified":8,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"post","source":"syntology-graph","title":"Cost-efficient Active Learning for Referring Image Segmentation and Grounding","url":"/paper/arxiv-2608-30621","arxiv_id":"2608.30621","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/junbum766/ALRIS","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":21,"n_ran":2,"n_unverified":19,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":21}},{"kind":"post","source":"syntology-graph","title":"CapFrame: Text-Instructed Viewpoint Grounding in 3D Gaussian Scenes via Geometric Pseudo Labels","url":"/paper/arxiv-2608-30342","arxiv_id":"2608.30342","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/jirongli/CapFrame","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":9,"n_ran":3,"n_unverified":6,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":9}},{"kind":"post","source":"syntology-graph","title":"SPARK: Skeleton-Guided Reasoning Synthesis from Large-Scale Scientific Literature","url":"/paper/arxiv-2608-30214","arxiv_id":"2608.30214","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/vertaix/Vendi-Score","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":8,"n_ran":4,"n_unverified":4,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"post","source":"syntology-graph","title":"ATGS: Anchored Temporal Gaussian Splatting for Long Volumetric Video Representation","url":"/paper/arxiv-2608-30184","arxiv_id":"2608.30184","date":"2026-08-31","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/WuJH2001/ATGS","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":11,"n_ran":2,"n_unverified":9,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":11}},{"kind":"post","source":"syntology-graph","title":"LoopArena: Benchmarking Models as Runtime Controllers for Loop Engineering","url":"/paper/arxiv-2608-28281","arxiv_id":"2608.28281","date":"2026-08-28","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/AMAP-ML/LoopArena","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":12,"n_ran":8,"n_unverified":4,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"post","source":"syntology-graph","title":"RealSWE: A Compositional Evaluation of Coding Agents under Realistic User Requests","url":"/paper/arxiv-2608-27831","arxiv_id":"2608.27831","date":"2026-08-28","month_from_arxiv_id":null,"title_date_abstract_source":"arXiv metadata, CC0 1.0","repo_url":"https://github.com/sirosen/repro","n_repos":1,"official":false,"framework":null,"tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":3,"n_ran":3,"n_unverified":0,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":3}}]},"archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","filter":"repository link and at least one Syntology-ran sample","order":"archive date descending; an undated row is placed by its arXiv-id month after that month's dated rows","first":31,"last":45,"total":31700,"n_in_feed":150,"n_placed_by_arxiv_id_month":819,"n_dated_after_snapshot":0,"max_archive_date":"2025-07-17","excluded":{"no_date_no_arxiv_id":1,"code_link_without_paper_row":1},"cards":[{"kind":"archive","source":"pwc-archive","title":"Flow-Anchored Consistency Models","url":"/paper/flow-anchored-consistency-models","arxiv_id":"2507.03738","date":"2025-07-04","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/ali-vilab/FACM","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"image-generation","name":"Image Generation","url":"/task/image-generation"}],"n_task_tags_without_task_page":0,"ranked_on":[{"leaderboard":"/sota/image-generation-on-imagenet-256x256","task":"Image Generation","dataset":"ImageNet 256x256"}],"n_ranked_on":1,"venue":null,"syntology":{"n_samples":14,"n_ran":8,"n_unverified":6,"n_ran_honours":1,"n_ran_violates":1,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents","url":"/paper/rlver-reinforcement-learning-with-verifiable","arxiv_id":"2507.03112","date":"2025-07-03","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/tencent/digitalhuman","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"emotional-intelligence","name":"Emotional Intelligence","url":"/task/emotional-intelligence"},{"slug":"reinforcement-learning","name":"Reinforcement Learning","url":"/task/reinforcement-learning"},{"slug":"reinforcement-learning-2","name":"reinforcement-learning","url":"/task/reinforcement-learning-2"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":3,"n_ran":3,"n_unverified":0,"n_ran_honours":2,"n_ran_violates":0,"n_pointer_only_for_licence":3}},{"kind":"archive","source":"pwc-archive","title":"Cautious Next Token Prediction","url":"/paper/cautious-next-token-prediction","arxiv_id":"2507.03038","date":"2025-07-03","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/wyzjack/CNTP","n_repos":1,"official":true,"framework":"jax","tasks":[{"slug":"prediction","name":"Prediction","url":"/task/prediction"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":14,"n_ran":7,"n_unverified":7,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks","url":"/paper/meta-secalign-a-secure-foundation-llm-against","arxiv_id":"2507.02735","date":"2025-07-03","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/facebookresearch/meta_secalign","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"instruction-following","name":"Instruction Following","url":"/task/instruction-following"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":3,"n_ran":3,"n_unverified":0,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":3}},{"kind":"archive","source":"pwc-archive","title":"SIU3R: Simultaneous Scene Understanding and 3D Reconstruction Beyond Feature Alignment","url":"/paper/siu3r-simultaneous-scene-understanding-and-3d","arxiv_id":"2507.02705","date":"2025-07-03","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/WU-CVGL/SIU3R","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"3d-reconstruction","name":"3D Reconstruction","url":"/task/3d-reconstruction"},{"slug":"scene-understanding","name":"Scene Understanding","url":"/task/scene-understanding"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":1,"n_ran":1,"n_unverified":0,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":1}},{"kind":"archive","source":"pwc-archive","title":"Energy-Based Transformers are Scalable Learners and Thinkers","url":"/paper/energy-based-transformers-are-scalable","arxiv_id":"2507.02092","date":"2025-07-02","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/alexiglad/EBT","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"denoising","name":"Denoising","url":"/task/denoising"},{"slug":"image-denoising","name":"Image Denoising","url":"/task/image-denoising"},{"slug":"math","name":"Math","url":"/task/math"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":5,"n_ran":2,"n_unverified":3,"n_ran_honours":0,"n_ran_violates":1,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"Kwai Keye-VL Technical Report","url":"/paper/kwai-keye-vl-technical-report","arxiv_id":"2507.01949","date":"2025-07-02","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/kwai-keye/keye","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"instruction-following","name":"Instruction Following","url":"/task/instruction-following"},{"slug":"reinforcement-learning-1","name":"Reinforcement Learning (RL)","url":"/task/reinforcement-learning-1"},{"slug":"video-understanding","name":"Video Understanding","url":"/task/video-understanding"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":13,"n_ran":4,"n_unverified":9,"n_ran_honours":3,"n_ran_violates":0,"n_pointer_only_for_licence":13}},{"kind":"archive","source":"pwc-archive","title":"LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior Sampling","url":"/paper/ld-rps-zero-shot-unified-image-restoration","arxiv_id":"2507.00790","date":"2025-07-01","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/amap-ml/ld-rps","n_repos":1,"official":true,"framework":"jax","tasks":[{"slug":"image-restoration","name":"Image Restoration","url":"/task/image-restoration"},{"slug":"unified-image-restoration","name":"Unified Image Restoration","url":"/task/unified-image-restoration"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":8,"n_ran":3,"n_unverified":5,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":8}},{"kind":"archive","source":"pwc-archive","title":"UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions","url":"/paper/umdatrack-unified-multi-domain-adaptive","arxiv_id":"2507.00648","date":"2025-07-01","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/z-z188/umdatrack","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"domain-adaptation","name":"Domain Adaptation","url":"/task/domain-adaptation"},{"slug":"object-tracking","name":"Object Tracking","url":"/task/object-tracking"},{"slug":"visual-object-tracking","name":"Visual Object Tracking","url":"/task/visual-object-tracking"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":2,"n_ran":2,"n_unverified":0,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":1}},{"kind":"archive","source":"pwc-archive","title":"LLaVA-SP: Enhancing Visual Representation with Visual Spatial Tokens for MLLMs","url":"/paper/llava-sp-enhancing-visual-representation-with","arxiv_id":"2507.00505","date":"2025-07-01","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/cnfaker/llava-sp","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"large-language-model","name":"Large Language Model","url":"/task/large-language-model"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":8,"n_ran":8,"n_unverified":0,"n_ran_honours":0,"n_ran_violates":1,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space","url":"/paper/se-3-equivariant-diffusion-policy-in-1","arxiv_id":"2507.01723","date":null,"month_from_arxiv_id":"2025-07","title_date_abstract_source":null,"repo_url":"https://github.com/amazon-science/Spherical_Diffusion_Policy","n_repos":1,"official":true,"framework":"pytorch","tasks":[],"n_task_tags_without_task_page":0,"ranked_on":[{"leaderboard":"/sota/robot-manipulation-on-mimicgen","task":"Robot Manipulation","dataset":"MimicGen"}],"n_ranked_on":1,"venue":null,"syntology":{"n_samples":14,"n_ran":7,"n_unverified":7,"n_ran_honours":1,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation","url":"/paper/fadrm-fast-and-accurate-data-residual","arxiv_id":"2506.24125","date":"2025-06-30","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/jiacheng8/fadrm","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"computational-efficiency","name":"Computational Efficiency","url":"/task/computational-efficiency"},{"slug":"dataset-distillation","name":"Dataset Distillation","url":"/task/dataset-distillation"}],"n_task_tags_without_task_page":1,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":18,"n_ran":17,"n_unverified":1,"n_ran_honours":0,"n_ran_violates":1,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning","url":"/paper/spiral-self-play-on-zero-sum-games","arxiv_id":"2506.24119","date":"2025-06-30","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/spiral-rl/spiral","n_repos":1,"official":true,"framework":null,"tasks":[{"slug":"math","name":"Math","url":"/task/math"},{"slug":"multi-agent-reinforcement-learning","name":"Multi-agent Reinforcement Learning","url":"/task/multi-agent-reinforcement-learning"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":9,"n_ran":2,"n_unverified":7,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"Flash-VStream: Efficient Real-Time Understanding for Long Video Streams","url":"/paper/flash-vstream-efficient-real-time","arxiv_id":"2506.23825","date":"2025-06-30","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/IVGSZ/Flash-VStream","n_repos":1,"official":true,"framework":"pytorch","tasks":[{"slug":"mme","name":"MME","url":"/task/mme"},{"slug":"video-understanding","name":"Video Understanding","url":"/task/video-understanding"},{"slug":"cross-modal-alignment","name":"cross-modal alignment","url":"/task/cross-modal-alignment"}],"n_task_tags_without_task_page":3,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":11,"n_ran":7,"n_unverified":4,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":0}},{"kind":"archive","source":"pwc-archive","title":"Dataset Distillation via Vision-Language Category Prototype","url":"/paper/dataset-distillation-via-vision-language","arxiv_id":"2506.23580","date":"2025-06-30","month_from_arxiv_id":null,"title_date_abstract_source":null,"repo_url":"https://github.com/Guang000/Awesome-Dataset-Distillation","n_repos":2,"official":true,"framework":null,"tasks":[{"slug":"dataset-distillation","name":"Dataset Distillation","url":"/task/dataset-distillation"},{"slug":"descriptive","name":"Descriptive","url":"/task/descriptive"},{"slug":"large-language-model","name":"Large Language Model","url":"/task/large-language-model"}],"n_task_tags_without_task_page":0,"ranked_on":[],"n_ranked_on":0,"venue":null,"syntology":{"n_samples":2,"n_ran":1,"n_unverified":1,"n_ran_honours":0,"n_ran_violates":0,"n_pointer_only_for_licence":2}}]}}}