AINeutralarXiv – CS AI · 14h ago6/10
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Agent^2 RL-Bench: Can LLM Agents Engineer Agentic RL Post-Training?
Researchers introduce Agent^2 RL-Bench, a benchmark testing whether LLM agents can autonomously design and execute reinforcement learning pipelines to improve foundation models. Testing across multiple agent systems reveals significant performance variation, with online RL succeeding primarily on ALFWorld while supervised learning pipelines dominate under fixed computational budgets.