A survey of credit assignment techniques in LLM reinforcement learning that distinguishes maturing methods for reasoning from new approaches needed for agentic settings and provides supporting resources.
Enhancing agentic rl with progressive reward shaping and value-based sampling policy optimization.arXiv preprint arXiv:2512.07478
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From Reasoning to Agentic: Credit Assignment in Reinforcement Learning for Large Language Models
A survey of credit assignment techniques in LLM reinforcement learning that distinguishes maturing methods for reasoning from new approaches needed for agentic settings and provides supporting resources.