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News/Why Multi-Step Tool-Use Reinforcement Learning Collapses and How Supervisory Signals Fix It
arxiv
PublishedJune 25, 2026 at 4:00 AM
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Why Multi-Step Tool-Use Reinforcement Learning Collapses and How Supervisory Signals Fix It

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arXiv:2606.26027v1 Announce Type: new Abstract: Tool use enables large language models (LLMs) to perform complex tasks, and recent agentic reinforcement learning (RL) methods show promise for enhancing model capabilities. However, RL alone often leads to instability or limited gains in tool-use task

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Read original ↗All from arxiv →
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#machine-learning#reinforcement-learning#large-language-models#tool-use

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