1 citations · 1 across the 8 of their papers we have counts for
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SeeQ: Training Generalist Value Functions for Long-Horizon Robotic Manipulation
Saksham Singh, Zheyuan Hu, Max Sobol Mark +3
Despite rapid progress, generalist robot policies remain brittle on complex, long-horizon tasks that comprise multiple stages or require repeated attempts and deliberation on the s…
BPP: Long-Context Robot Imitation Learning by Focusing on Key History Frames
Max Sobol Mark, Jacky Liang, Maria Attarian +4
Many robot tasks require attending to the history of past observations. For example, finding an item in a room requires remembering which places have already been searched. However…
RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction
Zheyuan Hu, Robyn Wu, Naveen Enock +4
Modern paradigms for robot imitation train expressive policy architectures on large amounts of human demonstration data. Yet performance on contact-rich, deformable-object, and lon…