User Attribute

User attribute research focuses on understanding how individual characteristics—like personality, demographics, and online behavior—influence interactions with systems, particularly recommender systems and large language models (LLMs). Current research emphasizes quantifying the impact of these attributes on system performance, fairness, and user experience, employing techniques like information theory, machine learning, and federated learning to analyze user profiles and predict preferences while addressing privacy concerns. This work is crucial for developing more effective, equitable, and personalized systems across various applications, improving user trust and satisfaction while mitigating biases and vulnerabilities.