Not All Answers Are Contextually Persuadable: Inference Dynamics in Large Language Models under Contextual Influence

Excerpt

arXiv:2610.04791v1 Announce Type: new Abstract: At the core of modern prompting techniques is contextual sensitivity, the ability of large language models to adapt their predictions based on inference-time context. Despite its central role, inference behavior under strong contextual influence remains poorly understood, particularly at the level of internal inference dynamics. We introduce a theoretical framework for analyzing contextual influence through inference dynamics, enabling quantitative