2 citations · 3 across the 4 of their papers we have counts for
4 papers
SteerX: Disentangled Steering for LLM Personalization
Xiaoyan Zhao, Ming Yan, Yilun Qiu +5
Large language models (LLMs) have shown remarkable success in recent years, enabling a wide range of applications, including intelligent assistants that support users' daily life a…
Reinforced Strategy Optimization for Conversational Recommender Systems via Network-of-Experts
Xiaoyan Zhao, Ming Yan, Yang Zhang +6
Conversational Recommender Systems (CRSs) aim to provide personalized recommendations through multi-turn natural language interactions with users. Given the strong interaction and…
Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning
Keqin Bao, Ming Yan, Yang Zhang +4
Frequently updating Large Language Model (LLM)-based recommender systems to adapt to new user interests -- as done for traditional ones -- is impractical due to high training costs…
Text-like Encoding of Collaborative Information in Large Language Models for Recommendation
Yang Zhang, Keqin Bao, Ming Yan +3
When adapting Large Language Models for Recommendation (LLMRec), it is crucial to integrate collaborative information. Existing methods achieve this by learning collaborative embed…