[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"aihot-art-87244":3},{"itemId":4,"vertical":5,"category":6,"source":7,"score":8,"title":9,"summary":10,"analysis":11,"url":12,"coverUrl":13,"direction":13,"marketSignal":13,"publishedAt":14},"87244","ai","论文研究","Elvis Saravia",58,"微软提出 OAT：轻量级智能体失败归因方法","微软提出 OAT 方法，仅用成功轨迹训练即可归因智能体失败步骤。","微软提出 OAT，一种轻量级智能体失败归因方法，无需失败数据。\n· OAT（One-class Attribution of Trajectories）仅用成功轨迹训练，通过神经受控微分方程建模其动态。\n· 然后标记失败轨迹中偏离成功流的步骤，实现归因。\n· 解决了大规模调试智能体轨迹时传统方案成本高、难以扩展的问题。\n· 该方法无需错误标签或失败数据，降低了应用门槛。\n影响\u002F看点：OAT 为智能体调试提供了高效、可扩展的新工具，有助于加速 AI 智能体的开发与部署。","https:\u002F\u002Fx.com\u002Fomarsar0\u002Fstatus\u002F2077418921536410080",null,"2026-07-15 23:44:02"]