"Stabilizing On-Policy Targeted Guidance in Agentic Reinforcement Learning"
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"Stabilizing On-Policy Targeted Guidance in Agentic Reinforcement Learning" Traditional RL can reinforce behaviors an LLM already knows, but it fails to teach entirely new behaviors that the base model rarely or never performs. So researchers from Cursor introduce Targeted Guidance, which uses textual feedback to show the model how to correct specific mistakes. It trains the model to imitate its own feedback-guided predictions, but only on failed turns, while continuing standard RL to preserve existing capabilities. On Qwen3-Coder-30B, the method improves adherence to multiple formatting an
Posted by alphaXiv (60.5k followers) 1 days ago · 67 likes · 4.9k views · view the original post on X. Kept by the AI Radar as AI research. Tools mentioned: alphaXiv.
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