arXiv:cs.AI· Feng Chen, Ritam Dutt, Atnaz Taheri, Alex Williams·· 5 小时前AI 评分47
邮件智能体为何"听不懂人话":请求表述变化如何破坏检索与行动
Lost in the Request: How Communication Variation Disrupts Retrieval and Action in Email Agents
AI 导读
一项被 NeurIPS 2026 Workshop on Evaluation of Interactive Agents 接收的研究发现,当用户以不同沟通风格或英语变体表达同一请求时,邮件助手的表现会下降。
正文
Abstract:An email assistant should not complete less work simply because a user phrases the same request differently. Yet most benchmarks test each task with only one canonical request, leaving this form of robustness largely unmeasured. We test whether email assistants remain reliable when the requested information, available evidence, and expected outcome stay fixed, but the communication style or English variety changes. We construct validated variants along five communication-style axes and four rule-based dialect conditions, and evaluate them on three benchmarks: a retrieval-augmented generation (RAG) pipeline and two tool-using agents. Indirect requests reduce performance on all three benchmarks, while formal requests reduce performance on both agentic benchmarks. Examining the systems more closely shows that these failures have different causes. Verbose requests mainly hurt a lexical retriever by making the relevant email harder to find. By contrast, indirect and dialect variants remain harmful even when the relevant email is retrieved. In the agentic setting, indirect and formal requests mainly cause the agents to omit required actions, not to take more unsupported actions. These results show that a successful response is not enough to establish robustness: evaluations should vary how requests are expressed and separately measure whether agents complete the requested work.
| Comments: | Accepted by NeurIPS 2026 Workshop on Evaluation of Interactive Agents |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.02627 [cs.AI] |
| (or arXiv:2610.02627v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.02627 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Feng Chen [view email]
[v1]
Fri, 2 Oct 2026 00:35:05 UTC (129 KB)
来源:arXiv:cs.AI · arxiv.org