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Qingyao Li

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Preprint Aug 2026

Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories

This work introduces Harness-R1, the first method, to the authors' knowledge, that makes failure-conditioned, lifecycle-wide editing of an existing executable runtime a learned capability, and post-trains a dedicated harness engineer with online reinforcement learning so that its edits are optimized for the realized ta...

Shuai Shao, Kangning Zhang, Qingyao Li et al. · 10 citations · ⚡2
#artificial intelligence Preprint Aug 2026

EMAN: Optimization-Driven Capacity Growth through Path Emergence in Multi-Task Learning

The Emergent Modular Atomic Network (EMAN), an optimization-driven framework for exposing an antisymmetric growth direction through latent relative phases without instantiating a second path, and for monitoring multiple decision signals during training to transform local optimization evidence into a structural decision...

Chen Fang, Jingchen Li, Hong-Zong Li et al. · 0 citations

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