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cs.CL2026
Dense Process Supervision for Search Agents via Fact Utility Estimation
Rongzhi Zhu, Xiangyu Liu, Yi Liu +7
Reinforcement learning (RL) for search agents typically relies on outcome rewards. However, it often fails to achieve effective credit assignment, due to the unclear value of inter…
cs.CL2026
ActMem: Bridging the Gap Between Memory Retrieval and Reasoning in LLM Agents
Xiaohui Zhang, Zequn Sun, Chengyuan Yang +3
Memory management is essential for LLM agents in long-term interactions. Current memory frameworks typically treat agents as passive ``recorders'' and retrieve information without…