Make any data you want</p>\n","updatedAt":"2026-06-23T05:51:32.352Z","author":{"_id":"66d7e9519b7da501cd2ceeaa","avatarUrl":"/avatars/f23c207ef9264851a4cdefb000b22fc4.svg","fullname":"Cong","name":"Coneonewan","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":1,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.8247194290161133},"editors":["Coneonewan"],"editorAvatarUrls":["/avatars/f23c207ef9264851a4cdefb000b22fc4.svg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2606.21337","authors":[{"_id":"6a3a16b3fdcd3514343bb6a3","user":{"_id":"66d7e9519b7da501cd2ceeaa","avatarUrl":"/avatars/f23c207ef9264851a4cdefb000b22fc4.svg","isPro":false,"fullname":"Cong","user":"Coneonewan","type":"user","name":"Coneonewan"},"name":"Cong Wan","status":"claimed_verified","statusLastChangedAt":"2026-06-23T13:56:05.018Z","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6a4","name":"Zeyu Guo","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6a5","name":"Zijian Cai","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6a6","name":"Jiangyang Li","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6a7","name":"SongLin Dong","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6a8","name":"Lin Peng","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6a9","user":{"_id":"668df98de9e585e8718f767f","avatarUrl":"/avatars/2be52f4ae88a0991c8ae584f8e870734.svg","isPro":false,"fullname":"Xiangyang Luo","user":"XiangyangLuo02","type":"user","name":"XiangyangLuo02"},"name":"Xiangyang Luo","status":"claimed_verified","statusLastChangedAt":"2026-06-23T13:56:01.079Z","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6aa","name":"Zhiheng Ma","hidden":false},{"_id":"6a3a16b3fdcd3514343bb6ab","name":"Yihong Gong","hidden":false}],"publishedAt":"2026-06-19T00:00:00.000Z","submittedOnDailyAt":"2026-06-23T00:00:00.000Z","title":"DataClaw0: Agentic Tailoring Multimodal Data from Raw Streams","submittedOnDailyBy":{"_id":"66d7e9519b7da501cd2ceeaa","avatarUrl":"/avatars/f23c207ef9264851a4cdefb000b22fc4.svg","isPro":false,"fullname":"Cong","user":"Coneonewan","type":"user","name":"Coneonewan"},"summary":"Massive unstructured multimodal streams suffer from high \"data entropy,\" impeding both efficient human knowledge acquisition and high-quality AI post-training. Existing passive annotation paradigms, heavily reliant on heuristic rules or general VLMs, are costly, monotonous, and fail to unlock the deep procedural logic embedded in raw data. We elevate data processing to a learnable capability, proposing a paradigm shift towards Agentic Data Tailoring, which actively refining and structuring data to align with diverse user and downstream intents. To overcome the data scarcity bottleneck in training such high-order capabilities, we design a two-stage pipeline grounding generative semantic synthesis in deterministic Factual Anchors, yielding a large-scale dataset spanning five core physical and digital domains. Building upon this, DataClaw_0-9B model synergizes Supervised Fine-Tuning (SFT) with Group Relative Policy Optimization (GRPO), achieving robust alignment with complex refinement and tailoring intents. To systematically quantify this capability, we construct DataClaw_0-val, the first benchmark dedicated to data refinement. Crucially, we adopt downstream post-training as the ultimate validation touchstone. Evaluations on video generation, real-world VQA, and GUI navigation confirm that DataClaw_0 delivers high-information-density tailored data, facilitating efficient model adaptation to new tasks under limited training data regimes. Project page: https://czjdsg.github.io/MakeAnyData","upvotes":65,"discussionId":"6a3a16b3fdcd3514343bb6ac","projectPage":"https://czjdsg.github.io/MakeAnyData/#cases","githubRepo":"https://github.com/vancyland/DataClaw0","githubRepoAddedBy":"user","ai_summary":"Agentic Data Tailoring paradigm uses learnable data processing to structure high-entropy multimodal streams, with DataClaw_0-9B model achieving robust alignment through SFT and GRPO on a novel benchmark.","ai_keywords":["Agentic Data Tailoring","generative semantic synthesis","deterministic Factual Anchors","Supervised Fine-Tuning","Group Relative Policy Optimization","data refinement","multimodal streams","data entropy","downstream post-training"],"ai_summary_model":"Qwen/Qwen2.5-Coder-32B-Instruct","githubStars":24},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"6a146ff99c5e89e04b70e4b9","avatarUrl":"/avatars/3a434e78443a2005dd4c7101b8e159cd.svg","isPro":false,"fullname":"Zheng Yifan","user":"zhengyifan20","type":"user"},{"_id":"6442c7d97feb866811b2935c","avatarUrl":"/avatars/16c18db3b33785203c3023307fcc547e.svg","isPro":false,"fullname":"Zijian Cai","user":"yzxjb","type":"user"},{"_id":"668df98de9e585e8718f767f","avatarUrl":"/avatars/2be52f4ae88a0991c8ae584f8e870734.svg","isPro":false,"fullname":"Xiangyang Luo","user":"XiangyangLuo02","type":"user"},{"_id":"6a15cb24785864c80e393b2e","avatarUrl":"/avatars/3f9f78771acca608e769a7653c4584d5.svg","isPro":false,"fullname":"山下愛","user":"heanderson","type":"user"},{"_id":"6a15e8bdf28e1a7f4f2b4061","avatarUrl":"/avatars/06e1fb99c1f7421938c558569f613962.svg","isPro":false,"fullname":"罗子轩","user":"harperclark","type":"user"},{"_id":"6a1591afe68cf1a41e7c0bce","avatarUrl":"/avatars/5f2930a52af392950df761b06c4eade9.svg","isPro":false,"fullname":"優奈 阿部","user":"asher-garciahb","type":"user"},{"_id":"6a1470b7b28ec6a2ad92193c","avatarUrl":"/avatars/6243b0a5d5d3c8bec740d07bdbb12950.svg","isPro":false,"fullname":"Grayson Scott","user":"grascott99","type":"user"},{"_id":"6a14801df432ac02b881e091","avatarUrl":"/avatars/0cf3308977f6066b02e083598cb4726f.svg","isPro":false,"fullname":"Julian Perez","user":"julianpere32","type":"user"},{"_id":"6a147f9828c29f18c7dca547","avatarUrl":"/avatars/a0b42a9bda610a7fbc951085332c6dcb.svg","isPro":false,"fullname":"木村結月","user":"ameliarobinson","type":"user"},{"_id":"6a15c469d57ab19bdd02eb7d","avatarUrl":"/avatars/c576b96ba3190641d74ac85e938509f1.svg","isPro":false,"fullname":"佐藤颯太","user":"mateom8","type":"user"},{"_id":"6a15ed18c2fc8c23990d384e","avatarUrl":"/avatars/dd363f08ed49f8b0d4c7699391263b10.svg","isPro":false,"fullname":"加藤 大輝","user":"wyatth34","type":"user"},{"_id":"6a147d3193b9759a7f062980","avatarUrl":"/avatars/167f360f649939b767745a7b30e2ac7a.svg","isPro":false,"fullname":"Aurora Hill","user":"aurorahi8","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":3,"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2606/2606.21337.md","query":{}}">

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