Lazy Grounding: Attacking Search Agents with Factual Evidence

Abstract:Search agents reduce hallucination by grounding answers in retrieved web evidence. Yet reliance on retrieval also creates an attack surface: poisoned corpora with false or malicious documents can cause agents to reproduce misinformation. We show that falsehood is not necessary -- a search agent can be misled by factual evidence for a nearby question, adopting that nearby answer even when it does not answer the current question. We call this failure lazy grounding. We expose lazy grounding using nearby evidence from answer-changing rewrites of benchmark questions. Each document truthfully supports a neighboring rewritten question, but is surfaced for the original question. Across 12 model-benchmark pairs, nearby evidence reduces accuracy by 5.9 points on average and by up to 17.3 points, while inducing nearby-answer adoption in every setting. The effect is stronger when nearby evidence appears later or is more answer-shaped. Our results show that robust search agents must defend against not only misinformation but also the misapplication of factual evidence. The code is publicly available at this https URL.

Accepted to EMNLP 2026 (Main Conference). Code: this https URL

Computation and Language (cs.CL)

arXiv:2608.30303 [cs.CL]

(or arXiv:2608.30303v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.30303 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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