3 papers
cs.CL2026
Beyond Isolated Behaviors: Hierarchical User Modeling for LLM Personalization
Liang Wang, Xinyi Mou, Xiaoyou Liu +3
Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse domains, yet personalizing their outputs to individual users remains an open challenge. Existi…
cs.CL2026
CURP: Codebook-based Continuous User Representation for Personalized Generation with LLMs
Liang Wang, Xinyi Mou, Xiaoyou Liu +2
User modeling characterizes individuals through their preferences and behavioral patterns to enable personalized simulation and generation with Large Language Models (LLMs) in cont…
cs.AI2026
PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoning
Xiaoyou Liu, Xinyi Mou, Shengbin Yue +5
As users increasingly expect LLMs to align with their preferences, personalized information becomes valuable. However, personalized information can be a double-edged sword: it can…