Contrastive Hypothesis Retrieval Improves Medical QA by Suppressing Hard Negatives
Researchers introduce Contrastive Hypothesis Retrieval (CHR), a framework that generates both a target hypothesis and a mimic hypothesis to explicitly suppress clinically plausible but incorrect answers during retrieval. In evaluations across three medical QA benchmarks, CHR outperforms all baselines by up to 10.4 percentage points, and in 85.2% of cases where CHR answers correctly but a strong baseline does not, the retrieved documents are entirely different.
Why it matters: CHR provides a novel approach to reducing hard-negative contamination in medical retrieval-augmented generation systems, potentially improving diagnostic accuracy.
Full story at: arXiv Information Retrieval ↗