RE: https://newsie.social/@TheConversationUS/116591472919935485
#ai and #hallucinations ... and more. Like the Hitler scene in Good Will Hunting. 🫢
RE: https://newsie.social/@TheConversationUS/116591472919935485
#ai and #hallucinations ... and more. Like the Hitler scene in Good Will Hunting. 🫢
🤪 Halupedia: Encyclopedia that hallucinates articles on the fly https://github.com/BaderBC/halupedia
Greetings from #Germany, native #English #language speakers, i come in peace! 🖖
We finally meet on equal ground; i've asked an #LLM (#DuckDuckGo / #DuckAI / #Mistral) to explain correct spelling, and comparison of AE vs BE.
👀 see screencap video demo - NO, it's NOT A #GIF! Your #Mastodon instances' UI might STILL misrepresent video/mp4 as image/gif - complain & +1 on #GitHub!
Apparently, it's wHicH, with 2 H!
Objections, anyone? (double-checking #AI #hallucinations.)
Yay, #InternetEnglish! 😅
LLM hallucinations in the wild: Large-scale evidence from non-existent citations
Zhenyue Zhao, Yihe Wang, Toby Stuart, Mathijs De Vaan, Paul Ginsparg, Yian Yin
"Large language models (LLMs) are known to generate plausible but false information across a wide range of contexts, yet the real-world magnitude and consequences of this hallucination problem remain poorly understood. Here we leverage a uniquely verifiable object - scientific citations - to audit 111 million references across 2.5 million papers in arXiv, bioRxiv, SSRN, and PubMed Central. We find a sharp rise in non-existent references following widespread LLM adoption, with a conservative estimate of 146,932 hallucinated citations in 2025 alone. These errors are diffusely embedded across many papers but especially pronounced in fields with rapid AI uptake, in manuscripts with linguistic signatures of AI-assisted writing, and among small and early-career author teams. At the same time, hallucinated references disproportionately assign credit to already prominent and male scholars, suggesting that LLM-generated errors may reinforce existing inequities in scientific recognition. Preprint moderation and journal publication processes capture only a fraction of these errors, suggesting that the spread of hallucinated content has outpaced existing safeguards. Together, these findings demonstrate that LLM hallucinations are infiltrating knowledge production at scale, threatening both the reliability and equity of future scientific discovery as human and AI systems draw on the existing literature."
https://arxiv.org/abs/2605.07723
#AI #GenerativeAI #LLMs #Hallucinations #AcademicPublishing #Science

Large language models (LLMs) are known to generate plausible but false information across a wide range of contexts, yet the real-world magnitude and consequences of this hallucination problem remain poorly understood. Here we leverage a uniquely verifiable object - scientific citations - to audit 111 million references across 2.5 million papers in arXiv, bioRxiv, SSRN, and PubMed Central. We find a sharp rise in non-existent references following widespread LLM adoption, with a conservative estimate of 146,932 hallucinated citations in 2025 alone. These errors are diffusely embedded across many papers but especially pronounced in fields with rapid AI uptake, in manuscripts with linguistic signatures of AI-assisted writing, and among small and early-career author teams. At the same time, hallucinated references disproportionately assign credit to already prominent and male scholars, suggesting that LLM-generated errors may reinforce existing inequities in scientific recognition. Preprint moderation and journal publication processes capture only a fraction of these errors, suggesting that the spread of hallucinated content has outpaced existing safeguards. Together, these findings demonstrate that LLM hallucinations are infiltrating knowledge production at scale, threatening both the reliability and equity of future scientific discovery as human and AI systems draw on the existing literature.
"A 44-page report titled “Points of Attack: Uncovering Cyber Threats and Fraud in Loyalty Systems” looks like many others that management consultancy EY publishes every year.
These types of reports are the bread and butter of the biggest consultancies on the planet — thought pieces about business that help cement their position as organizations to be commissioned to help companies understand their place in the world, and how to maintain it. EY’s consulting arm generated over $16.4 billion in revenue last year.
There’s just one problem. Dig into this particular report, published in December 2025 — particularly its “resources” section, which provides links to sources of the data and claims cited throughout the document — and things don’t add up.
“It’s riddled with hallucinations,” said Edward Tian, a former employee at journalism website Bellingcat and Princeton University researcher who set up GPTZero, an AI-detection firm that shared its investigation exclusively with Sherwood News.
EY didn’t respond to multiple requests for comment.
The document is a standard advisory report describing the state of cybersecurity weaknesses in the travel industry’s loyalty points ecosystem. But it appears to have issues with citing nonexistent sources."
https://sherwood.news/tech/ai-hallucinations-appear-to-be-creeping-into-consulting-reports/
South Africa Used AI To Write Its Now Withdrawn AI Policy. The Citations Were Fake.