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arXiv cs.AI· Mohammadreza Sediqin, Shivali Dalmia, Srinivasa Karthikeya Reddy Kovvuri, Abhishek Mukherji·· 4 小时前AI 评分59

Agent 评估信任层论文提出四种事后校验,仅 22.6% 的基准通过结果通过全部检查

A Trust Layer for Agent Evaluation

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论文提出 Agent 评估信任层(Trust Layer for Agent Evaluation),一种事后附加框架,在基准分数旁报告其是否可信,校验结果是否有评分逻辑支持、是否来自可追溯计算、完成声明是否属实、以及重复运行是否稳定,且不修改原始分数。

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Abstract:Deterministic benchmark scores show that an agent received credit, but not whether that credit was earned, reported honestly, or would hold on a second run. We introduce a Trust Layer for Agent Evaluation, an additive post-hoc framework that reports, beside each recorded score, whether it should be believed. It verifies four properties: whether the result is supported by the benchmark's own grading logic, whether a passing answer was earned through traceable computation, whether the agent's completion claim matches what occurred, and whether the result is stable under repeated execution. The first three use only saved artifacts; the fourth re-runs the agent. Model judgments only label evidence under majority voting; all verdicts follow deterministic rules and never modify the recorded score. Applied to five agent configurations on 108 tasks from Agents' Last Exam, every model shows passing runs with no traceable computation (at rates varying tenfold), confirmed false completion claims, and unstable results: 18-46% of tasks do not stay in one score band over five runs. Only 22.6% of recorded passes clear all four checks (95% CI 15.0-32.6, n=84). Measuring what an agent can do and verifying that it did it are different problems, and current benchmarks address only the first.
Comments: Expanded version with additional experiments
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.07274 [cs.AI]
  (or arXiv:2610.07274v2 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2610.07274

arXiv-issued DOI via DataCite

Submission history

From: Mohammadreza Sediqin [view email]
[v1] Mon, 5 Oct 2026 19:15:37 UTC (90 KB)
[v2] Thu, 5 Nov 2026 17:16:16 UTC (92 KB)

来源:arXiv cs.AI · arxiv.org