arXiv Robotics — research abstracts· Yusuf Umut Ciftci, Joonwon Kang, Ajay Suresha Sathya, Somil Bansal·· 1 days agoEditorial score42
Quantifying Critical States in Imitation Learning for Robotics
Where Small Mistakes Matter: Quantifying State Criticality for Imitation Learning
Summary
SCRIM measures state criticality by assessing action perturbation impact. It improves imitation learning by reweighting losses and enabling efficient data selection.
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Source：arXiv Robotics — research abstracts · arxiv.org