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cs.AI2026
From Verdict to Process: Agentic Reinforcement Learning for Multi-Stage Fact Verification
Rongxin Yang, Shenghong He, Siyuan Zhu +1
Recent approaches combining Large Language Models (LLMs) with retrieval-augmented reasoning have shown promise for automated fact verification. To process complex claims, these ver…
cs.AI2025
Planner-R1: Reward Shaping Enables Efficient Agentic RL with Smaller LLMs
Siyu Zhu, Yanbin Jiang, Hejian Sang +6
We investigated Agentic RL with large language models on the \textsc{TravelPlanner} benchmark. Our approach, \textsc{Planner-R1}, achieved a \textbf{56.9\%} final-pass rate with on…