Research

We show that RAG systems exhibit systematic overconfidence when retrieved context contradicts the model's parametric knowledge, and propose a lightweight calibration intervention.

Tried to use GPT-4 to pre-screen papers for a workshop. The reviews were superficially plausible but consistently missed domain-specific errors that any expert would catch. Abandoned after testing on 20 papers.