reclaim-evaluation

This paper shows that a language model with a lossy memory that retains a wrong conclusion but drops the evidence produces confident incorrect answers, whereas an empty memory leads to abstention. The authors propose a source-first compression policy that preserves recomputable sources instead of conclusions to maintain correctability, and demonstrate the mechanism across multiple models and dialogue systems.