DSSP is a history-conditioned diffusion state space policy that uses SSMs to encode full observation streams with an auxiliary dynamics objective and hierarchical fusion, achieving SOTA results with reduced model size in robot manipulation.
Wang, Hanyi Zhang, Qian Wang, Rudolf Lioutikov, and Gerhard Neumann
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EgoDex delivers the largest egocentric dataset with native 3D hand tracking for dexterous manipulation, enabling imitation learning policies for hand trajectory prediction on 194 tasks.
NAUTILUS is a prompt-driven harness that automates plug-and-play adapters, typed contracts, and validation for policies, benchmarks, and robots in learning research.
citing papers explorer
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DSSP: Diffusion State Space Policy with Full-History Encoding
DSSP is a history-conditioned diffusion state space policy that uses SSMs to encode full observation streams with an auxiliary dynamics objective and hierarchical fusion, achieving SOTA results with reduced model size in robot manipulation.
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EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video
EgoDex delivers the largest egocentric dataset with native 3D hand tracking for dexterous manipulation, enabling imitation learning policies for hand trajectory prediction on 194 tasks.
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Nautilus: From One Prompt to Plug-and-Play Robot Learning
NAUTILUS is a prompt-driven harness that automates plug-and-play adapters, typed contracts, and validation for policies, benchmarks, and robots in learning research.