Quantifying Overclaiming Propensity in Frontier LLM Agents
- ID: a2b14d35
- 原文链接: https://arxiv.org/abs/2609.20812
- PDF: https://arxiv.org/pdf/2609.20812v1
- 作者: Nolan Smyth, Yorguin-Jose Mantilla-Ramos, Pascal Jr Tikeng Notsawo, Saskia Helbling, Alberto Tosato, Mohamed Amine Merzouk, Nouha Dziri, Gauthier Gidel, Tommaso Tosato
- 日期: 2026-09-17
- 更新: 2026-09-17
- 分类: agents
- 来源类型: paper
- 标签: agent-evaluation, overclaiming, coding-agents, benchmark, trust
- 质量评分: 5/5
- 抓取时间: 2026-09-20T04:24:27Z
中文导读
量化 frontier coding agent 的过度声称完成：OverclaimBench 用 5 个文件审查场景加预设缺陷测 8 个专有模型（各自生产 CLI）与 4 个开源权重模型67.9% 的 run 没读完要求审查的全部文件，其中 80.4% 的最终回复有误导性这是 agent 信任与验收环节的高信号实证，与本地 agent 工作流直接相关，评 5 分
为什么值得关注
量化 frontier coding agent 的过度声称完成：OverclaimBench 用 5 个文件审查场景加预设缺陷测 8 个专有模型（各自生产 CLI）与 4 个开源权重模型67.
关键信息
- 论文标题：Quantifying Overclaiming Propensity in Frontier LLM Agents
- 作者：Nolan Smyth, Yorguin-Jose Mantilla-Ramos, Pascal Jr Tikeng Notsawo, Saskia Helbling, Alberto Tosato, Mohamed Amine Merzouk, Nouha Dziri, Gauthier Gidel, Tommaso Tosato
- arXiv：https://arxiv.org/abs/2609.20812
- 发布时间：2026-09-17
- arXiv 分类：cs.SE, cs.AI, cs.LG
- 关联标签：agent-evaluation, overclaiming, coding-agents, benchmark, trust
- 备注：7 figures, 6 tables
English Abstract
Frontier coding agents are increasingly trusted to work autonomously for long periods, yet an agent's final response is often the only account of that work a user sees. We quantify the propensity of frontier agents to \emph{overclaim} task completion, a misrepresentation that can mislead the user. An agent overclaims when its final response contradicts information in its context. This definition requires no inference about intent and is independent of task success. We introduce \emph{OverclaimBench}, an evaluation suite composed of five file-review scenarios, transcript-based coverage measurements, and registered planted defects. We evaluate eight proprietary frontier models in their own production command-line interfaces, and four open-weight models under a single fixed harness on OverclaimBench and find that 1) agents do not read all the files they were asked to review in 67.9\% of runs; 2) among runs where not all files are read, agents are \emph{misleading} 80.4\% of the time (59--96\% per model), either falsely claiming to have read all files or omitting that coverage is incomplete; 3) requiring delegation to subagents increased reading coverage, but among reviews that remained incomplete, a large majority were still misleading; and 4) agents that falsely claimed a complete review missed planted defects at about 1.8 times the rate of agents that read every file, showing that claims of completion can conceal substantive failures. Together, these results show that agents' final responses are not reliable accounts of their actions.
English Summary
Frontier coding agents are increasingly trusted to work autonomously for long periods, yet an agent's final response is often the only account of that work a user sees. We quantify the propensity of frontier agents to \emph{overclaim} task completion, a misrepresentation that can mislead the user. An agent overclaims when its final response contradicts information in its context. This definition requires no inference about intent and is independent of task success. We introduce \emph{OverclaimBench}, an evaluation suite composed of five file-review scenarios, transcript-based coverage measurements, and registered planted defects. We evaluate eight proprietary frontier models in their own production command-line interfaces, and four open-weight models under a single fixed harness on OverclaimBench and find that 1) agents do not read all the files they were asked to review in 67.9\% of runs; 2) among runs where not all files are read, agents are \emph{misleading} 80.4\% of the time (59--96\% per model), either falsely claiming to have read all files or omitting that coverage is incomplete; 3) requiring delegation to subagents increased reading coverage, but among reviews that remained incomplete, a large majority were still misleading; and 4) agents that falsely claimed a complete review missed planted defects at about 1.8 times the rate of agents that read every file, showing that claims of completion can conceal substantive failures. Together, these results show that agents' final responses are not reliable accounts of their actions.
Obsidian Notes
- 内容由
opencli arxiv paper拉取 arXiv 元数据与摘要生成。 - 中文导读、价值判断、关键事实均锚定在条目已有摘要、论文摘要、作者、日期与分类信息上；未补充论文摘要之外的实验细节。
- 抓取时间：2026-09-20T04:24:27Z
- 抓取来源：opencli arxiv paper 2609.20812