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arXiv cs.CL·

From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning

Signal
72
Hype
28
In three linesLLM-as-Environment-Engineer framework: the policy model analyzes failure trajectories and proposes modifications to the next-stage RL training environment configuration. MAPF-FrozenLake testbed with multi-dimensional configurations. Qwen3-4B outperforms GPT and Gemini on proposed benchmarks.
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Reinforcement learningMulti-agentReasoningBenchmarksQwen

Summary generated by Claude — human-verified