no code implementations • 27 Feb 2024 • Xiaokun Zhang, Bo Xu, Chenliang Li, Yao Zhou, Liangyue Li, Hongfei Lin
Emerging efforts incorporate various kinds of side information into their methods for enhancing task performance.
no code implementations • 17 Dec 2023 • Chenglin Li, Qianglong Chen, Liangyue Li, Caiyu Wang, Yicheng Li, Zulong Chen, Yin Zhang
While large language models (LLMs) have demonstrated exceptional performance in recent natural language processing (NLP) tasks, their deployment poses substantial challenges due to high computational and memory demands in real-world applications.
no code implementations • 12 Nov 2023 • Zhenghao Liu, Zulong Chen, Moufeng Zhang, Shaoyang Duan, Hong Wen, Liangyue Li, Nan Li, Yu Gu, Ge Yu
This paper proposes the User Viewing Flow Modeling (SINGLE) method for the article recommendation task, which models the user constant preference and instant interest from user-clicked articles.
no code implementations • 6 May 2022 • Beidi Zhao, Boxin Du, Zhe Xu, Liangyue Li, Hanghang Tong
Graph Neural Networks (GNNs) have achieved tremendous success in a variety of real-world applications by relying on the fixed graph data as input.
no code implementations • 21 Apr 2022 • Senrong Xu, Yuan YAO, Liangyue Li, Wei Yang, Feng Xu, Hanghang Tong
In this work, we study the victim node detection problem under topology attacks against GNNs.
no code implementations • 14 Mar 2018 • Muge Li, Liangyue Li, Feiping Nie
Despite success, these approaches rely on fixed-weight graphs, making ranking sensitive to the input affinity matrix.
no code implementations • 3 Apr 2015 • Liangyue Li, Hanghang Tong
Understanding the dynamic mechanisms that drive the high-impact scientific work (e. g., research papers, patents) is a long-debated research topic and has many important implications, ranging from personal career development and recruitment search, to the jurisdiction of research resources.