Ke Zeng
2 indexed papers
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SelSkill introduces a dual-granularity preference learning framework that treats skill use as a 'skill-or-skip' decision, significantly improving agent performance and execution precision in complex agentic tasks.
SIRI introduces a self-internalizing reinforcement learning framework that allows LLM agents to autonomously discover and integrate reusable skills directly into their core policy, significantly improving performance on complex tasks without external skill generators.
Papers
SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Training
Zhongyu He, Yuanfan Li, Fei Huang, Tianyu Chen +8 more
SIRI introduces a self-internalizing reinforcement learning framework that allows LLM agents to autonomously discover and integrate reusable skills directly into their core policy, significantly impro…