19 citations · 26 across the 3 of their papers we have counts for
6 papers
Continuous-time Discrete-space Diffusion Model for Recommendation
Chengyi Liu, Xiao Chen, Shijie Wang +2
In the era of information explosion, Recommender Systems (RS) are essential for alleviating information overload and providing personalized user experiences. Recent advances in dif…
CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent
Liang-bo Ning, Shijie Wang, Wenqi Fan +4
Recently, Large Language Model (LLM)-empowered recommender systems (RecSys) have brought significant advances in personalized user experience and have attracted considerable attent…
Towards Next-Generation Recommender Systems: A Benchmark for Personalized Recommendation Assistant with LLMs
Jiani Huang, Shijie Wang, Liang-bo Ning +4
Recommender systems (RecSys) are widely used across various modern digital platforms and have garnered significant attention. Traditional recommender systems usually focus only on…
Computational Protein Science in the Era of Large Language Models (LLMs)
Wenqi Fan, Yi Zhou, Shijie Wang +5
Considering the significance of proteins, computational protein science has always been a critical scientific field, dedicated to revealing knowledge and developing applications wi…
Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation
Shijie Wang, Wenqi Fan, Yue Feng +4
Recommender systems have become increasingly vital in our daily lives, helping to alleviate the problem of information overload across various user-oriented online services. The em…
Score-based Generative Diffusion Models for Social Recommendations
Chengyi Liu, Jiahao Zhang, Shijie Wang +2
With the prevalence of social networks on online platforms, social recommendation has become a vital technique for enhancing personalized recommendations. The effectiveness of soci…