BibTeX Citation Errors in Scientific Publishing Agents: Evaluation and Mitigation
Large language models with web search are increasingly used in scientific publishing agents, yet they produce BibTeX entries with pervasive field-level errors stemming from omission, partial corruption, substitution, and hallucination. We construct a benchmark of 931 papers across four domains and three citation tiers---popular, low-citation, and recent post-cutoff---with version-aware ground truth. Three search-enabled frontier models (GPT-5, Claude Sonnet-4.6, Gemini-3 Flash) generate approximately 23,000 field-level observations. Overall accuracy is 83.6%, but only 50.9% of entries are fully correct; accuracy drops 27.7 pp from popular to recent papers, revealing heavy reliance on para...
| Authors | Delip Rao, Chris Callison-Burch |
|---|---|
| Primary category | cs.DL |
| Published | 3 April 2026 |
| Last updated at source | 8 August 2026 |
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