Quantifying Critical States in Imitation Learning for Robotics
Overview
SCRIM measures state criticality by assessing action perturbation impact, improving imitation learning through loss reweighting and efficient data selection. Published in arXiv Robotics, 2026-10-14.
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- arXiv Robotics — research abstractsQuantifying Critical States in Imitation Learning for Robotics
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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