1 citations · 2 across the 6 of their papers we have counts for
8 papers
SPRINT: Single-Step Generative Recommendation via Average Probability Velocity
Zhuo Cai, Shoujin Wang, Peilin Zhou +3
Semantic ID (SID) based generative recommendation represents each item as a sequence of discrete tokens, and recommends by generating the SID of the item a user would like to inter…
DKCD: Domain Knowledge-Enhanced Causal Discovery from Unstructured Data
Xin Li, Jin Li, Shoujin Wang +2
Causal discovery from unstructured data is a challenging yet underexplored task in high-expertise domains such as healthcare, finance, and education. Existing methods typically lev…
Neural Federated Learning for Livestock Growth Prediction
Shoujin Wang, Mingze Ni, Wei Liu +6
Livestock growth prediction is essential for optimising farm management and improving the efficiency and sustainability of livestock production, yet it remains underexplored due to…
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…
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…
A Survey on Enhancing Causal Reasoning Ability of Large Language Models
Xin Li, Zhuo Cai, Shoujin Wang +2
Large language models (LLMs) have recently shown remarkable performance in language tasks and beyond. However, due to their limited inherent causal reasoning ability, LLMs still fa…
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…
Causal Learning for Trustworthy Recommender Systems: A Survey
Jin Li, Shoujin Wang, Qi Zhang +5
Recommender Systems (RS) have significantly advanced online content filtering and personalized decision-making. However, emerging vulnerabilities in RS have catalyzed a paradigm sh…