Google 与香港大学发布 VeriCUA 论文，用机器状态验证计算机智能体任务完成声明
Google 与香港大学发布 VeriCUA 论文：用机器状态验证计算机智能体的任务完成声明
Google 与香港大学发布 VeriCUA 论文，主张计算机使用智能体的“任务完成”自报不能作为证据，应检查保存的文件和应用数据。VeriCUA 先探索应用构建需求清单，再运行屏幕或代码检查逐项核实；在 ScienceBoard 上误报率为 5.4%，低于 VLM 评审的 24.8% 和生成脚本校验器的 21.7%，并在 3 个在线环境中拒绝约 80% 的虚假完成报告。
Rohan Paul· @rohanpaul_ai · X·2026-11-03 10:37· 40 分钟前AI 评分52
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Google 与香港大学的 VeriCUA 论文主张计算机使用智能体自己报告的“任务完成”不能作为证据，应检查保存的文件和应用数据。VeriCUA 先探索应用构建需求清单，再运行屏幕或代码检查逐项核实；在 ScienceBoard 上误报率为 5.4%，低于 VLM 评审的 24.8% 和生成脚本校验器的 21.7%，并在 3 个在线环境中拒绝约 80% 的虚假完成报告。
正文 · 原文
New Google and University of Hong Kong paper argues that when AI agents use computers, their own “task done” message should never count as proof, and the saved files and app data should be checked instead.
Computer-use agents can report a task done when edits were never saved or only part was finished. Common checkers either judge a few screenshots or run 1 generated script, and both can miss the deciding evidence.
VeriCUA explores the app to build a requirement checklist, then runs screen or code checks, like file reads, until each item is settled. The agent's own claim of success never counts as proof.
On ScienceBoard, its false-positive rate was 5.4%, against 24.8% for a VLM judge and 21.7% for a generated script verifier. Across 3 online environments, it rejected about 80% of false completion reports.
If agent runs feed your evals, training data, or RL rewards, check saved machine state instead of trusting screenshots or the agent's report.
来源：Rohan Paul · x.com
来源：RadarAI · aihot.news