TRec: Sequential Recommender Based On Latent Item Trend Information. - Ye Tao 004; Can Wang 004; Lina Yao 001; Weimin Li 001; Yonghong Yu (IJCNN, 2020)

Enhancing recommender ensemble by estimating input fitness. - Ye Tao 004; Can Wang 004; Alan Wee-Chung Liew; Sebastian Binnewies (Comput. Electr. Eng., 2022)

Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systems. - Zhangchi Qiu; Ye Tao 004; Shirui Pan; Alan Wee-Chung Liew (CoRR, 2023)

Item trend learning for sequential recommendation system using gated graph neural network. - Ye Tao 004; Can Wang 004; Lina Yao 001; Weimin Li 001; Yonghong Yu (Neural Comput. Appl., 2023)

Dynamic weighted ensemble learning for sequential recommendation systems: The AIRE model. - Ye Tao 004; Can Wang 004; Alan Wee-Chung Liew (Future Gener. Comput. Syst., 2023)

A Reinforcement Learning Approach to Wi-Fi Rate Adaptation Using the REINFORCE Algorithm. - Ye Tao 004; Wee Lum Tan (WCNC, 2024)

Knowledge Graphs and Pretrained Language Models Enhanced Representation Learning for Conversational Recommender Systems. - Zhangchi Qiu; Ye Tao 004; Shirui Pan; Alan Wee-Chung Liew (IEEE Trans. Neural Networks Learn. Syst., 2025)