3 papers
cs.IR2026
Towards Fair Large Language Model-based Recommender Systems without Costly Retraining
Jin Li, Huilin Gu, Shoujin Wang +5
Large Language Models (LLMs) have revolutionized Recommender Systems (RS) through advanced generative user modeling. However, LLM-based RS (LLM-RS) often inadvertently perpetuates…
cs.LG2025
Revealing Multimodal Causality with Large Language Models
Jin Li, Shoujin Wang, Qi Zhang +5
Uncovering cause-and-effect mechanisms from data is fundamental to scientific progress. While large language models (LLMs) show promise for enhancing causal discovery (CD) from uns…
cs.IR2025
Generating with Fairness: A Modality-Diffused Counterfactual Framework for Incomplete Multimodal Recommendations
Jin Li, Shoujin Wang, Qi Zhang +2
Incomplete scenario is a prevalent, practical, yet challenging setting in Multimodal Recommendations (MMRec), where some item modalities are missing due to various factors. Recentl…