#source-evaluation News & Analysis

Trust, but Don't Verify: Epistemic Blind Spots in LLM Source Evaluation

A new study reveals that large language models can identify fabricated statistics in isolation but fail to apply this capability when synthesizing multiple sources, instead weighting sources based on analytical presentation style rather than numeric validity. This 'epistemic alignment' failure—where models prioritize how credible something sounds over whether it's actually true—persists across multiple model families and domains, with attempted fixes through prompting producing blanket skepticism rather than selective discernment.