COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation.

arXiv:2609.26853v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved remarkable results across various benchmarks, their alignment with normative values often results in homogenized responses that fail to address diverse user pref