{ "schema_version": "paper_public_manifest_v1", "paper_id": "koda_2026_10", "slug": "koda", "title": "KODA：人类示范转成人形全身数据", "authors": [], "source": { "arxiv_id": "2610.21152", "pdf_url": "https://arxiv.org/pdf/2610.21152", "project_url": "", "github_url": "", "huggingface_url": "", "original_source": "https://arxiv.org/abs/2610.21152" }, "site": { "post_url": "/posts/koda", "canonical_url": "https://haiguangboy.com/posts/koda", "cover_image": "https://static.haiguangboy.com/papers/koda/cover.webp" }, "taxonomy": { "domain": "embodied_ai", "track": "vla", "tasks": [ "embodied_ai", "vla", "action_generation", "robotics", "state_prediction", "具身智能", "人形机器人", "人类示范", "全身控制", "gr00t" ], "related_topics": [ { "paper_id": "an_open_foundation_model_towards_2026_07", "title": "An_Open_Foundation_Model_Towards", "url": "https://haiguangboy.com/posts/an_open_foundation_model_towards", "relation": "contrast", "summary": "真机训练使用机器人与转换人类数据共训 contradicts 联合co-training异构人机数据是结构性次优方案", "strength": "strong" }, { "paper_id": "openwam_an_open_modular_exploration_towards_systematic_world_action_model_pretra_2026_09", "title": "OpenWAM:正确答案会随规模变", "url": "https://haiguangboy.com/posts/openwam_an_open_modular_exploration_towards_systematic_world_action_model_pretra", "relation": "contrast", "summary": "OpenWAM:正确答案会随规模变", "strength": "strong" }, { "paper_id": "transformer-transformer_blog_transformer_transformer_a_unified_20260807_2026_08", "title": "Transformer Transformer: A Unified Model for Motion-Conditioned Robot Co-design", "url": "https://haiguangboy.com/posts/transformer-transformer-codesign", "relation": "contrast", "summary": "跨控制器复用仍限定同一本体且需再生成监督 contradicts 同一 DiT 通过改变条件掩码，在生成器、设计器和跨本体控制器之间切换", "strength": "strong" }, { "paper_id": "nvidia_gr00t_n1_7_egoscale_blog_20260417_2026_08", "title": "nvidia_gr00t_n1_7_egoscale_blog_20260417", "url": "https://haiguangboy.com/posts/nvidia_gr00t_n1_7_egoscale_blog_20260417", "relation": "contrast", "summary": "数据增量趋势不足以确立scaling law contradicts NVIDIA GR00T N1.7押的是\"人类第一视角视频规模化\"路线:2万+小时EgoScale预训练,官方称发现了\"首条灵巧度scaling law\"——数据从1000小时到2万小时,平均任务完成度提升超过一倍,不靠海量遥操作", "strength": "strong" }, { "paper_id": "flex_pi_a_multi_stream_world_action_model_with_compute_flexibility_2026_08", "title": "把RGB、3D几何、物体语义揉进同一个表征——这才是它比π0.5、Fast-WAM更准的根本原因", "url": "https://haiguangboy.com/posts/flex_pi_a_multi_stream_world_action_model_with_compute_flexibility", "relation": "contrast", "summary": "FLEX-π:更全面的联合表征", "strength": "strong" }, { "paper_id": "dexora_open_source_vla_for_high_dof_bimanual_dexterity_2026_08", "title": "遥操作数据的噪声得进损失函数", "url": "https://haiguangboy.com/posts/dexora", "relation": "contrast", "summary": "跨控制器复用仍限定同一本体且需再生成监督 contradicts 跨本体前提:高自由度策略把低自由度本体当作子空间,降维比升维容易", "strength": "strong" } ] }, "analyst_take": { "type": "author_opinion", "text": "💡 工程启发\n监督不匹配也可能负迁移：SONIC加入未做命令优化的转换数据后，已覆盖条件成功率为48.75%，低于仅用机器人数据的62.5%。\n与WholeBodyWAM的跨控制器结果对照，数据可复用和策略免适配是两层问题。KODA把复用放在运动与观测记录，把接口差异留给监督生成。后续要看：更多控制器下，能否保住任务收益并减少重复转换成本。" }, "ruling": { "importance_score": 3.0, "one_sentence": "KODA：人类示范转成人形全身数据" }, "asset_base_url": "https://static.haiguangboy.com/papers/koda", "assets": [ { "type": "pdf_screenshot", "object_key": "papers/koda/page_01.webp", "content_type": "image/webp", "upload_status": "uploaded", "bucket": "paper-assets", "url": "https://static.haiguangboy.com/papers/koda/page_01.webp", "role": "paper_first_page", "size_bytes": 182346 }, { "type": "pdf_screenshot", "object_key": "papers/koda/key_figure.webp", "content_type": "image/webp", "upload_status": "uploaded", "bucket": "paper-assets", "url": "https://static.haiguangboy.com/papers/koda/key_figure.webp", "role": "method_figure", "size_bytes": 181416 }, { "type": "cover_image", "object_key": "papers/koda/cover.webp", "content_type": "image/webp", "upload_status": "uploaded", "bucket": "paper-assets", "url": "https://static.haiguangboy.com/papers/koda/cover.webp", "role": "post_cover", "size_bytes": 72076 }, { "type": "public_brief", "object_key": "papers/koda/public_brief.md", "content_type": "text/markdown; 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