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cs.AI2026
Dynamic Dual-Granularity Skill Bank for Agentic RL
Songjun Tu, Chengdong Xu, Qichao Zhang +5
Agentic RL can benefit substantially from reusable experience, yet existing skill-based methods mainly extract trajectory-level guidance and often lack principled mechanisms for ma…
cs.AI2025
Voting with the Graph: Stable RLAIF via Topological Consistency Maximization
Boyin Liu, Zhuo Zhang, Sen Huang +8
Reinforcement Learning from AI Feedback (RLAIF) relies on LLM judges as preference measurement instruments, yet these instruments are fundamentally limited by random measurement er…