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Learning Meta-Skills for Agent Harness Design in Test-Time AI4AI

Qian, Cheng et al.
arXiv (All) · Papers
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computation-and-languagemachine-learning
Agent performance depends on both reasoning ability and the environment in which it acts. We study test-time AI-for-AI, asking how a Builder can learn to construct better execution environments for a Target while both models' weights remain fixed. To make the Builder's experience reusable, we introd
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