Turbo Harness: Instance-Adaptive Harness Optimization· Turbo Harness: 实例自适应套件优化
Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations typically produce a single global harness that is applied uniformly across task instances. However, a harness that works well on average may not be optimal for every instance. We introduce Turbo Harness, a framework that can adapt a globally optimized harness to each instance by reusing information generated during the original optimization process. Specifically, Turbo Harness recycles artifacts produced during a completed global harness optimization run, and summarizes them into a structured playbook. We train a harness editor to leverage this prior optimization experience to generate instance-specific patches to the global harness. At infer
Turbo Harness 通过重用全局优化过程中的信息，为每个任务实例生成自适应的优化套件。
- 核心方法
- Turbo Harness 通过总结全局优化过程中产生的信息，训练一个套件编辑器为特定实例生成优化补丁。
- 适合谁读
- 研究者
- 要解决的问题
- 现有套件优化方法通常生成全局套件，但这种套件对所有任务实例可能不是最优的。
- 关键实验
- 未提供
- 主要贡献
- 提出了一种实例自适应的套件优化框架，能够有效利用之前的优化经验。
- 意义与局限
- Turbo Harness 可以提高代理在特定任务实例上的性能，促进递归自我改进，但实验结果尚未公布。