ProFA achieves the strongest reported agent-level and step-level failure-attribution accuracies among the listed methods on the held-in HotPotQA, ChartQAPro, and Mind2Web datasets and on the held-out Algorithm-Generated and Hand-Crafted subsets.

ProFA achieves the strongest reported agent-level and step-level failure-attribution accuracies among the listed methods on the held-in HotPotQA, ChartQAPro, and Mind2Web datasets and on the held-out Algorithm-Generated and Hand-Crafted subsets. · CiteArk

测量结果

已评估 0/3 项

获得支持 0有争议或冲突 0尚未评估 3

保留同一结论下的完整结果组。已有评估排在前面；单项判断不替代整组结论。展开行查看条件、来源与历次证据。

每行是一项测量，分别显示论文报告、最近可用实测和累计证据状态。
指标与条件	论文报告	最近可用实测	证据判断
split: held-in · method: ProFA · dataset: HotPotQA · value_scope: test set of constructed Who & When Pro dataset · accuracy_level: agent	0.85 fraction	—	尚未评估
split: held-out Algorithm-Generated · method: ProFA · dataset: Who & When · failure_logs: 184 · accuracy_level: step	0.53 fraction	—	尚未评估
split: held-out Hand-Crafted · method: ProFA · dataset: Who & When · failure_logs: 184 · accuracy_level: step	0.2 fraction	—	尚未评估

ProFA achieves the strongest reported agent-level and step-level failure-attribution accuracies among the listed methods on the held-in HotPotQA, ChartQAPro, and Mind2Web datasets and on the held-out Algorithm-Generated and Hand-Crafted subsets.

报告指标与观测值

Assessment（0）

关联运行（0）

测量结果