[HUGGINGFACE]score: 0.76

ReTerm: Self-Improving Terminal Agents via Recovery Training

October 12, 2026

ReTerm uses a customized ReTerm-10K dataset and a ReTerm-GRPO online RL algorithm to train terminal agents to recover from execution errors. The method forks from failure states to generate multiple independent recovery attempts, improving long-running task success rates.

HOW THIS AFFECTS YOU

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builderYou can use the ReTerm-10K dataset and GRPO-based recovery training to make your coding agents more resilient to command failures.

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researcherThis provides a new approach for training agents to handle error recovery via RL-based state forking.

read original ↗huggingface.co

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