Accepted at ICML 2026.</p>\n","updatedAt":"2026-06-08T03:51:39.843Z","author":{"_id":"63c3e8abc7d7f4c63a515a02","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63c3e8abc7d7f4c63a515a02/npMHnVP2hHLbvoUGe7C4O.jpeg","fullname":"Zekun Qi","name":"qizekun","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":8,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.9193037748336792},"editors":["qizekun"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/63c3e8abc7d7f4c63a515a02/npMHnVP2hHLbvoUGe7C4O.jpeg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2606.06953","authors":[{"_id":"6a263bd3e4c258a02949204b","name":"Yu Guan","hidden":false},{"_id":"6a263bd3e4c258a02949204c","name":"Zekun Qi","hidden":false},{"_id":"6a263bd3e4c258a02949204d","name":"Chenghuai Lin","hidden":false},{"_id":"6a263bd3e4c258a02949204e","name":"Xuchuan Chen","hidden":false},{"_id":"6a263bd3e4c258a02949204f","name":"Dairu Liu","hidden":false},{"_id":"6a263bd3e4c258a029492050","name":"Wenyao Zhang","hidden":false},{"_id":"6a263bd3e4c258a029492051","name":"Jilong Wang","hidden":false},{"_id":"6a263bd3e4c258a029492052","name":"Xinqiang Yu","hidden":false},{"_id":"6a263bd3e4c258a029492053","name":"He Wang","hidden":false},{"_id":"6a263bd3e4c258a029492054","name":"Li Yi","hidden":false}],"publishedAt":"2026-06-05T00:00:00.000Z","submittedOnDailyAt":"2026-06-08T00:00:00.000Z","title":"LIMMT: Less is More for Motion Tracking","submittedOnDailyBy":{"_id":"63c3e8abc7d7f4c63a515a02","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63c3e8abc7d7f4c63a515a02/npMHnVP2hHLbvoUGe7C4O.jpeg","isPro":false,"fullname":"Zekun Qi","user":"qizekun","type":"user","name":"qizekun"},"summary":"We argue that high-quality motion data can steer tracking policies toward better optimization trajectories early in training. In this work, we introduce LIMMT (Less Is More for Motion Tracking). To our knowledge, this is the first data-centric study for physics-based humanoid motion tracking. We go beyond simply removing low-quality and erroneous clips, but define motion data quality through three dimensions: physics feasibility, diversity, and complexity. We show that even training with under 3% of AMASS yields better tracking performance than training with the full dataset. We further conduct data cleaning on the estimated web-sourced mocap data. Extensive experiments and analyses validate the effectiveness of our framework.","upvotes":12,"discussionId":"6a263bd3e4c258a029492055","projectPage":"https://giraffeguan.github.io/limmt/","ai_summary":"Training with high-quality motion data improves tracking policy optimization trajectories, with minimal data subsets outperforming full datasets in physics-based humanoid motion tracking.","ai_keywords":["motion tracking","physics-based humanoid motion tracking","data-centric study","motion data quality","physics feasibility","diversity","complexity","AMASS","data cleaning","mocap data"],"ai_summary_model":"Qwen/Qwen2.5-Coder-32B-Instruct","organization":{"_id":"6842da337b70d258bfb51b79","name":"GalaxyGeneralRobotics","fullname":"galbot","avatar":"https://cdn-avatars.huggingface.co/v1/production/uploads/6842d3b4297a588f54e85f84/q9PZ3SXbzzluHhhMjLD-3.jpeg"}},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"63c3e8abc7d7f4c63a515a02","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63c3e8abc7d7f4c63a515a02/npMHnVP2hHLbvoUGe7C4O.jpeg","isPro":false,"fullname":"Zekun Qi","user":"qizekun","type":"user"},{"_id":"66839c7f7b0920f40d7ff3e0","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/66839c7f7b0920f40d7ff3e0/nuOh5acjmb9QZK3wNQxt1.jpeg","isPro":false,"fullname":"Dairu Liu","user":"dairuliu","type":"user"},{"_id":"65f9533b136fb8ddbd14e1fa","avatarUrl":"/avatars/d88f75da0448093ccd1babba2a37d73f.svg","isPro":false,"fullname":"Zhang","user":"WenyaoZhang","type":"user"},{"_id":"69b9764fa55df6c73e7c1a34","avatarUrl":"/avatars/9ee539f5c13817fc516cfbd18bdded65.svg","isPro":false,"fullname":"Yintianrun Zhang","user":"Zyrobotics","type":"user"},{"_id":"68b5b682fbd18ef2d9c011fb","avatarUrl":"/avatars/1f8c7738001da98db5add914dca82fe4.svg","isPro":false,"fullname":"Chenghuai Lin","user":"chenghuailin","type":"user"},{"_id":"67cffc3aebbaf3f0c2c93b1c","avatarUrl":"/avatars/325d187256d2fa1f0a00e162010261d7.svg","isPro":false,"fullname":"yu guan","user":"rainguan","type":"user"},{"_id":"683ff9810278714998705654","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/xhvcLacOLbx27WiHY0BZf.png","isPro":false,"fullname":"chenxin ding","user":"chenxin-ding","type":"user"},{"_id":"683ff8138c64413c0d7bfbba","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/ZmBD-cyEuag_Y6JHrd5Il.png","isPro":false,"fullname":"Xukun Cai","user":"ikun-kun","type":"user"},{"_id":"683ffeb9967d02230641c8ad","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/z2WZJkllrCKTCliLEMrr-.png","isPro":false,"fullname":"linkai wang","user":"linkai-wang","type":"user"},{"_id":"683ff8b1f9f5cf052b4db216","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/ugYm9NE_FIGM2Wgp98UQ7.png","isPro":false,"fullname":"jiaqima","user":"jiaqi-ma","type":"user"},{"_id":"68cb1b1ff283dbb922dc8e9c","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/zylXL3XGKy5E8tISylviX.png","isPro":false,"fullname":"Yangbowen","user":"Bowen-Yang","type":"user"},{"_id":"6a26830030ee6257332bd0b9","avatarUrl":"/avatars/e25aa32557ae5285ef5e63a41febc070.svg","isPro":false,"fullname":"Hero","user":"hero2312","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":0,"organization":{"_id":"6842da337b70d258bfb51b79","name":"GalaxyGeneralRobotics","fullname":"galbot","avatar":"https://cdn-avatars.huggingface.co/v1/production/uploads/6842d3b4297a588f54e85f84/q9PZ3SXbzzluHhhMjLD-3.jpeg"},"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2606/2606.06953.md"}">

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