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.
A typed-contract harness with containerized 'chambers' and robotics-specific agent skills lets a coding LLM turn a single natural-language prompt into working reproduction, evaluation, and deployment workflows for robot learning.
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
A typed-contract harness with containerized 'chambers' and robotics-specific agent skills lets a coding LLM turn a single natural-language prompt into working reproduction, evaluation, and deployment workflows for robot learning.