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New framework CiteAnchor tackles hallucinated citations in scientific papers

By PulseAugur Editorial · [1 sources] ·

Researchers have developed CiteAnchor, a framework designed to improve the detection and resolution of hallucinated citations in scientific literature. This system adapts its retrieval and verification methods based on the source type, allowing it to separately assess citation validity and the recoverability of a unique source. When tested with GPT-5.6 Luna, CiteAnchor achieved a notable 0.841 F1 score on an existing detection benchmark, significantly outperforming baseline methods. The framework also demonstrated strong performance on a new benchmark of real-world hallucinated citations, achieving 74.7% task success. AI

IMPACT Improves scientific literature integrity and research reproducibility by enhancing citation verification.

RANK_REASON The item describes a new framework and benchmark for detecting and resolving hallucinated citations in scientific papers, presented in an arXiv preprint. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework CiteAnchor tackles hallucinated citations in scientific papers

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The item describes a new framework and benchmark for detecting and resolving hallucinated citations in scientific papers, presented in an arXiv preprint. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Chenyi Tong, Ping Nie, Yu Zhang ·

    CiteAnchor: Source-Aware Grounding for Hallucinated Citation Detection and Resolution

    arXiv:2610.30355v1 Announce Type: new Abstract: Hallucinated citations make it harder to trace sources and verify the evidence behind scientific claims. Detecting them is difficult because bibliographic records can be incomplete or differ across source types and publication versi…

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