131 citations · 131 across the 1 of their papers we have counts for
5 papers
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
Jizhi Zhang, Keqin Bao, Yang Zhang +3
The remarkable achievements of Large Language Models (LLMs) have led to the emergence of a novel recommendation paradigm -- Recommendation via LLM (RecLLM). Nevertheless, it is imp…
Vague Preference Policy Learning for Conversational Recommendation
Gangyi Zhang, Chongming Gao, Wenqiang Lei +6
Conversational recommendation systems (CRS) commonly assume users have clear preferences, leading to potential over-filtering of relevant alternatives. However, users often exhibit…
Information Discovery in e-Commerce
Zhaochun Ren, Xiangnan He, Dawei Yin +1
Electronic commerce, or e-commerce, is the buying and selling of goods and services, or the transmitting of funds or data online. E-commerce platforms come in many kinds, with glob…
Knowledge Graph Embedding by Normalizing Flows
Changyi Xiao, Xiangnan He, Yixin Cao
A key to knowledge graph embedding (KGE) is to choose a proper representation space, e.g., point-wise Euclidean space and complex vector space. In this paper, we propose a unified…
Mitigating Hidden Confounding Effects for Causal Recommendation
Xinyuan Zhu, Yang Zhang, Fuli Feng +3
Recommender systems suffer from confounding biases when there exist confounders affecting both item features and user feedback (e.g., like or not). Existing causal recommendation m…