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EvoHIL achieves unprecedented improvements in robotic manipulation by dynamically adapting reward models and ensuring action coherence, setting a new standard for human-in-the-loop learning.
ReTouch achieves a remarkable 18.4% improvement in success rates for dexterous manipulation by continuously refining tactile predictions in real-time.
