Aligning Deep Implicit Preferences by Learning to Reason Defensively 事件

Aligning Deep Implicit Preferences by Learning to Reason Defensively arXiv:2510.11194v3 Announce Type: replace Abstract: Personalized alignment is crucial for enabling Large Language Models (LLMs) to engage effectively in user-centric interactions. However, current methods face a dual challenge: they fail to infer users' deep implicit preferences (including unstated goals, semantic context and risk tolerances), and they lack the defensive reasoning required to navigate real-world ambiguity. Thi