Assessing Web Search Credibility and Response Groundedness in Chat Assistants

Ivan Vykopal, Matúš Pikuliak, Simon Ostermann, Marian Simko


Abstract
Chat assistants increasingly integrate web search functionality, enabling them to retrieve and cite external sources. While this promises more reliable answers, it also raises the risk of amplifying misinformation from low-credibility sources. In this paper, we introduce a novel methodology for evaluating assistants’ web search behavior, focusing on source credibility and the groundedness of responses with respect to cited sources. Using 100 claims across five misinformation-prone topics, we assess GPT-4o, GPT-5, Perplexity, and Qwen Chat. Our findings reveal differences between the assistants, with Perplexity achieving the highest source credibility, whereas GPT-4o exhibits elevated citation of non-credible sources on sensitive topics. This work provides the first systematic comparison of commonly used chat assistants for fact-checking behavior, offering a foundation for evaluating AI systems in high-stakes information environments.
Anthology ID:
2026.eacl-long.115
Volume:
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
March
Year:
2026
Address:
Rabat, Morocco
Editors:
Vera Demberg, Kentaro Inui, Lluís Marquez
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2539–2560
Language:
URL:
https://preview.aclanthology.org/ingest-eacl/2026.eacl-long.115/
DOI:
Bibkey:
Cite (ACL):
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann, and Marian Simko. 2026. Assessing Web Search Credibility and Response Groundedness in Chat Assistants. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2539–2560, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):
Assessing Web Search Credibility and Response Groundedness in Chat Assistants (Vykopal et al., EACL 2026)
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PDF:
https://preview.aclanthology.org/ingest-eacl/2026.eacl-long.115.pdf