Research2d ago
Distilling Hallucination Signals Into Model Representations
A new framework uses a 15,000-sample dataset from SQuAD v2 to label responses as grounded or hallucinated. Researchers distilled external verification signals directly into internal transformer activations. This removes the need for retrieval systems or judge models during inference. Practitioners can now detect hallucinations using only the model's own internal state.