TAO-RL
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Related Articles from SNS
Tool-Aware Optimization with Entropy Guidance for Efficient Agentic Reinforcement Learning
arXiv:2606.03762v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) equips large language models (LLMs) with tool-use capabilities that substantially improve reasoning on complex tasks. However, integrating external tools often destabilizes training: over-reliance on tools can induce input distribution shift, while overly conservative tool use limits effective exploration. To address this issue, we propose a unified framework TAO-RL that couples tool-aware trajectory...