A Deep Read of Selective Context Trust

Learning When to Trust: Measuring and Training Selective Trust with Selective Context Preference Optimization

A deep read of Learning When to Trust via Selective Context Preference Optimization: MIST holds each reasoning item fixed while varying clean, misleading, correct-context, and irrelevant-context signals; SC2W isolates clean-correct flips, and SCOPE reduces them with balanced DPO preference quartets while retaining the paper's text-only, contamination, and deployment-prevalence boundaries.