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arXiv Machine Learning
Oct 3

EvoGen-Harness: Learning Where and How to Evolve Image-Generation Harnesses

EvoGen-Harness is a generator‑agnostic framework that enables multi‑responsibility evolution of image‑generation harnesses, allowing multiple external components to adapt around frozen generators. It introduces Trace, a method that aggregates evidence across stochastic runs, uses failure attribution as a search prior, and progressively re‑attributes residual failures to guide efficient evolution. The approach achieves significant performance gains on GenEval2, T2I‑CompBench++, and WISE, with high attribution recall, No‑Patch accuracy, and low regression rates.

By Jiabin Luo, Yinan Liu, Chunlei Meng, Yufei Guo
diffusion
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arXiv Computation and Language
5d ago

CoTrace: Data Recipes for Training Terminal Agents with Harness-Model Co-Evolution

arXiv:2610.10426v1 Announce Type: new Abstract: Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Exist...

By Jixuan Chen, Jiaxin Zhang, Qinyuan Ye, Yada Pruksachatkun, Haoxiang Zhang, Jingming Zhuo, Yifan Zhang, Yutong Dai, Juntao Tan, Xiangyu Peng, Silvio Savarese, Zeyuan Chen, Lianhui Qin, Chien-Sheng Wu
agentsreinforcement-learningfine-tuning
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arXiv AI
Sep 2

HarnessEvolve: Learning from Reference Trajectories for Reliable Agent Self-Evolution

HarnessEvolve is a self‑evolving framework that improves agent harnesses—prompts, skills, tools, and execution logic—by learning from reference trajectories. It separates execution, evaluation, optimization, and gating into independent modules, addressing credit assignment failure, shortcut learning, and catastrophic forgetting. The approach uses reference trajectories to extract error signals, applies quality and performance gates to candidate updates, and validates updates on held‑out data, consistently outperforming state‑of‑the‑art baselines across diverse benchmarks.

By Wen Jiang, Mingmin Chu, Yimeng Tian, Qianxin Zhang, Haofei Yang, Rui Yang, Yang Liu, Tao Lv, Fangming Li
agentsbenchmarks
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