Vision-language-action (VLA) models handle long-horizon manipulation, yet success hinges on a few precision-critical phases where millimeter-scale errors undo all prior progress. Online reinforcement learning (RL) can optimize exactly these actions, but free exploration is far too costly on real robots, which makes hum...
Wei-Hui Zhao, Xiao Yan, Zu-Nian Wan et al.· 0 citations
This survey reviews blockchain consensus from a security-oriented lens and links distributed-systems fundamentals to concrete attack vectors and defense mechanisms and outlines open problems including the post-quantum cryptographic transition, cross-shard security and atomicity in sharded consensus, and adaptive defens...
This work introduces Continual Interactive Distillation for Embodied Reinforcement Learning (CIDER), a continual reinforcement learning framework that freezes the accumulated historical policy as a teacher before learning each new task and interleaves task learning with distillation-based retention.
Hou-Lin Li, Ming Xu, Guofeng Xu et al.· 0 citations
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