no code implementations • 23 May 2024 • Hanzhang Tu, Ruizhi Shao, Xue Dong, Shunyuan Zheng, Hao Zhang, Lili Chen, Meili Wang, Wenyu Li, Siyan Ma, Shengping Zhang, Boyao Zhou, Yebin Liu
Altogether, our telepresence system demonstrates the sense of co-presence in real-life experiments, inspiring the next generation of communication.
1 code implementation • 9 Jan 2024 • Xue Dong, Xuemeng Song, Tongliang Liu, Weili Guan
Multi-interest learning method for sequential recommendation aims to predict the next item according to user multi-faceted interests given the user historical interactions.
no code implementations • 6 Feb 2023 • Yuan Zhang, Xue Dong, Weijie Ding, Biao Li, Peng Jiang, Kun Gai
Embedding-based retrieval (EBR) methods are widely used in modern recommender systems thanks to its simplicity and effectiveness.
no code implementations • 17 Dec 2022 • Yongshun Gong, Xue Dong, Jian Zhang, Meng Chen
Our method focuses on learning the low-dimensional representations of networks and capturing the evolving patterns of these learned latent representations simultaneously.
no code implementations • 24 Jan 2022 • Xue Dong, Xuemeng Song, Na Zheng, Yinwei Wei, Zhongzhou Zhao
Moreover, we can summarize a preferred attribute profile for each user, depicting his/her preferred item attributes.