long-horizon-adaptation

This paper shows that models adapting on their own generated text during inference destabilize over long (128K-token) horizons, and proposes a causal decomposition plus a 'Settlement' validation mechanism that tests candidate updates on independent text before retaining them, substantially reducing damage while preserving genuine adaptation.