The 17% Gap: Quantifying Epistemic Decay in AI-Assisted Survey Papers
- URL: http://arxiv.org/abs/2601.17431v1
- Date: Sat, 24 Jan 2026 12:00:55 GMT
- Title: The 17% Gap: Quantifying Epistemic Decay in AI-Assisted Survey Papers
- Authors: H. Kemal İlter,
- Abstract summary: "Hallucinated papers" are a known artifact, but the systematic degradation of valid citation chains remains unquantified.<n>We conducted a forensic audit of 50 recent survey papers in Artificial Intelligence published between September 2024 and January 2026.<n>We detect a persistent 17.0% Phantom Rate -- citations that cannot be resolved to any digital object despite aggressive forensic recovery.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The adoption of Large Language Models (LLMs) in scientific writing promises efficiency but risks introducing informational entropy. While "hallucinated papers" are a known artifact, the systematic degradation of valid citation chains remains unquantified. We conducted a forensic audit of 50 recent survey papers in Artificial Intelligence (N=5,514 citations) published between September 2024 and January 2026. We utilized a hybrid verification pipeline combining DOI resolution, Crossref metadata analysis, Semantic Scholar queries, and fuzzy text matching to distinguish between formatting errors ("Sloppiness") and verifiable non-existence ("Phantoms). We detect a persistent 17.0% Phantom Rate -- citations that cannot be resolved to any digital object despite aggressive forensic recovery. Diagnostic categorization reveals three distinct failure modes: pure hallucinations (5.1%), hallucinated identifiers with valid titles (16.4%), and parsing-induced matching failures (78.5%). Longitudinal analysis reveals a flat trend (+0.07 pp/month), suggesting that high-entropy citation practices have stabilized as an endemic feature of the field. The scientific citation graph in AI survey literature exhibits "link rot" at scale. This suggests a mechanism where AI tools act as "lazy research assistants," retrieving correct titles but hallucinating metadata, thereby severing the digital chain of custody required for reproducible science.
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