When Citations Mislead? A Claim-Level Benchmark for Legal Hallucination Detection
arXiv:2610.10971v1 Announce Type: new Abstract: Large language models are increasingly used in legal research and drafting, but they can still produce claims that sound convincing without being supported by the cited source. We introduce PARCEL, a benchmark for checking whether a legal claim is supp
Focus to learn more arXiv-issued DOI via DataCite (pending registration) Journal reference: In Proceedings of the 21st International Conference on Artificial Intelligence and Law (ICAIL 2026), June 08-12, 2026, Singapore. ACM, New York, NY, USA Related DOI: https://doi.org/10.1145/3836937.3836948 Focus to learn more DOI(s) linking to related resources Submission history From: M. Mikail Demir [ view email ] [v1] Wed, 7 Oct 2026 22:43:56 UTC (174 KB) Full-text links: Access Paper: View a PDF of the paper titled When Citations Mislead?
A Claim-Level Benchmark for Legal Hallucination Detection, by M. Mikail Demir and 1 other authors View PDF HTML (experimental) TeX Source view license Additional Features Audio Summary Current browse context: cs.CL < prev | next > new | recent | 2026-10 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading...
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