4 papers
ExplainRec: Towards Explainable Multi-Modal Zero-Shot Recommendation with Preference Attribution and Large Language Models
Bo Ma, LuYao Liu, ZeHua Hu +1
Recent advances in Large Language Models (LLMs) have opened new possibilities for recommendation systems, though current approaches such as TALLRec face challenges in explainabilit…
LLM4Rec: Large Language Models for Multimodal Generative Recommendation with Causal Debiasing
Bo Ma, Hang Li, ZeHua Hu +3
Contemporary generative recommendation systems face significant challenges in handling multimodal data, eliminating algorithmic biases, and providing transparent decision-making pr…
AgentRec: Next-Generation LLM-Powered Multi-Agent Collaborative Recommendation with Adaptive Intelligence
Bo Ma, Hang Li, ZeHua Hu +3
Interactive conversational recommender systems have gained significant attention for their ability to capture user preferences through natural language interactions. However, exist…
Bridging Collaborative Filtering and Large Language Models with Dynamic Alignment, Multimodal Fusion and Evidence-grounded Explanations
Bo Ma, LuYao Liu, Simon Lau +3
Recent research has explored using Large Language Models for recommendation tasks by transforming user interaction histories and item metadata into text prompts, then having the LL…