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Bridging the action-sufficiency gap in robotic manipulation, GIFT achieves up to 12.6 points improvement over existing models by integrating structured intermediate features.
MemChain redefines memory management in LLMs, achieving state-of-the-art performance while slashing context overhead by transforming retrieved memories into a structured evidence context.
UCOB achieves unprecedented performance in agentic reinforcement learning by dynamically refining skill usage through credit-aware self-distillation.
