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单一全局 harness 撑不住异构长程:Google Cloud OO-Harness,最高 +15% abs

单一全局 harness 撑不住异构长程:Google Cloud OO-Harness,最高 +15% abs

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异构任务要不同执行策略,一个全局 harness 会互相拖累。

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Authors:Gaotang Li, Bhavana Dalvi Mishra, Yifei Ming, Yanfei Chen, Zhongying CuiZhu, Lesly Miculicich, Long T. Le, Rui Meng, Chun-Liang Li, Hanghang Tong, Chen-Yu Lee, Tomas Pfister

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Abstract:Agent harnesses are executable code that specifies the prompts, tools, and control flow around a language model. A single global harness can struggle with heterogeneous tasks that require different execution strategies. In this work, we introduce Object-Oriented Harness (OO-Harness), a harness optimization framework that evolves a hierarchy of executable harness classes using object-oriented design. During training, an evolution agent uses execution records to create a family of specialized harnesses, each implemented as a subclass of the base or an existing specialized harness via inheritance. At test time, a harness router uses routing lessons accumulated during training to select a specific harness for each task. Across three long-horizon benchmarks spanning business workflows, workspace tasks, and tool use, OO-Harness achieves the best performance among the compared methods, with an absolute improvement of up to 15% over the base. Extensive ablation studies examine the contributions of its core components.
Comments: 20 pages, 10 figures
Subjects: Computation and Language (cs.CL); Software Engineering (cs.SE)
Cite as: arXiv:2610.28380 [cs.CL]
  (or arXiv:2610.28380v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2610.28380

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Gaotang Li [view email]
[v1] Tue, 20 Oct 2026 15:32:52 UTC (4,910 KB)

Source: Agent Control Flash News · arxiv.org

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