HALLMARK: How to Diagnose LLM Citation Verifiers and When to Deploy Them
GPTZero found 53 NeurIPS 2025 accepted papers with hallucinated citations, and venues now screen submissions with automated reference checkers. Rule- and Large Language Model (LLM)-based verifiers are emerging, but many are released without a shared evaluation and each flags a different kind of error, so it is unclear which to trust or when to deploy them. We address this with HALLMARK (Hallucination benchmark): 2,526 BibTeX entries spanning 14 hallucination types, with per-type and diagnostic sub-test labels and further temporal, cross-domain, and real-world evaluation splits. We evaluate zero-shot and tool-augmented LLMs, a DOI-lookup baseline, and our own co-designed rule-based verifie...
| Authors | Kayoon Kim, Wieland Brendel, Patrik Reizinger |
|---|---|
| Primary category | cs.CR |
| Published | 20 July 2026 |
| Last updated at source | 11 October 2026 |
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