How Much Do Legal RAG Systems Still Hallucinate?
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Computer Science > Computation and Language
Title:How Much Do Legal RAG Systems Still Hallucinate?
Abstract:Hallucination is a major challenge for retrieval-augmented generation (RAG) systems in the legal domain, where ungrounded answers can lead to serious consequences. To better understand this problem, we conduct a fine-grained analysis of hallucination behavior in eight legal RAG systems across two legal corpora, the GDPR (in English) and a national civil law (in French). Using claim-level and answer-level evaluation, we report on hallucination density and severity, analyze performance across question categories and user personas, and validate our findings on an independent set of 142 legal-expert-authored questions. Our results show that hallucinations remain pervasive, ranging from less than 10% of responses for the best-performing systems to nearly half in the worst case. We further find that false-premise questions, containing incorrect assumptions that must be rejected, produce high hallucination rates on the manually-drafted questions.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2608.14210 [cs.CL] |
| (or arXiv:2608.14210v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.14210
arXiv-issued DOI via DataCite (pending registration)
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