EvoTrainer: Co-Evolving LLM Policies and Training Harnesses for Autonomous Agentic Reinforcement Learning

In three linesEvoTrainer co-evolves LLM policies and training harnesses via empirical feedback for autonomous agentic RL. Tested on mathematical reasoning, competitive programming code generation, and software engineering, the system matches or exceeds human-engineered RL baselines, with largest gains on long-horizon agentic SWE tasks.

Summary generated by Claude — human-verified