General-purpose models outperform medical-specialized ones (76.6% vs 51.3% hallucination-free). CoT cuts errors in 86.4% of cases; residual failures are mostly reasoning-based. 91.8% of clinicians encountered them. #MedicalAI #LLMHallucination #FoundationModels arxiv.org/abs/2503.05777

Ever wonder why LLMs sometimes make up data? Dive into PhantomFill, the new trick that forces GPT‑5.5 into JSON‑schema output—exposing hallucinations, benchmark hacks, and wild fabrications. Curious? Read on! #PhantomFill #LLMHallucination #StructuredOutput

🔗 aidailypost.com/news/phantom...

A new study shows the first token of a hallucinated span offers a stronger detection signal than later tokens, using RAGTruth token‑level data. This pattern holds for model sizes. https://getnews.me/first-hallucinated-token-shows-stronger-signal-for-llm-error-detection/ #llmhallucination #ragtruth

My "5 Easy Steps Guide" to using AI.
#LLMHallucination #MLSky

The Twin Liars of Samothrace comes to mind.

Should I ask the Magic Eight Ball again?