no code implementations • 11 Apr 2024 • Lihui Liu, Jinha Kim, Vidit Bansal
Recent advancements in contrastive learning have revolutionized self-supervised representation learning and achieved state-of-the-art performance on benchmark tasks.
no code implementations • 17 Mar 2024 • Lihui Liu, ZiHao Wang, Ruizhong Qiu, Yikun Ban, Eunice Chan, Yangqiu Song, Jingrui He, Hanghang Tong
Through the utilization of both knowledge graph reasoning and LLMs, it successfully derives answers for each subquestion.
no code implementations • 27 Dec 2023 • Lihui Liu, Blaine Hill, Boxin Du, Fei Wang, Hanghang Tong
CornNet adopts a teacher-student architecture where a teacher model learns question representations using human writing reformulations, and a student model to mimic the teacher model's output via reformulations generated by LLMs.
no code implementations • 11 Apr 2023 • Boxin Du, Lihui Liu, Jiejun Xu, Fei Wang, Hanghang Tong
Graph Neural Networks (GNNs) have been widely applied on a variety of real-world applications, such as social recommendation.
no code implementations • 6 Nov 2020 • Lihui Liu, Boxin Du, Heng Ji, Hanghang Tong
In detail, we develop KompaRe, the first of its kind prototype system that provides comparative reasoning capability over large knowledge graphs.