Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding. - Xinzhou Jin; Jintang Li; Yuanzhen Xie; Liang Chen 001; Beibei Kong; Lei Cheng 005; Bo Hu; Zang Li; Zibin Zheng (ICDM, 2023)

Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm. - Yuanzhen Xie; Xinzhou Jin; Tao Xie; Mingxiong Lin; Liang Chen 001; Chenyun Yu; Cheng Lei; Chengxiang Zhuo; Bo Hu; Zang Li (ACL (Findings), 2024)

State Space Models on Temporal Graphs: A First-Principles Study. - Jintang Li; Ruofan Wu; Xinzhou Jin; Boqun Ma; Liang Chen 001; Zibin Zheng (NeurIPS, 2024)

Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm. - Yuanzhen Xie; Xinzhou Jin; Tao Xie; Mingxiong Lin; Liang Chen 001; Chenyun Yu; Lei Cheng 005; Chengxiang Zhuo; Bo Hu; Zang Li (CoRR, 2024)

L2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering. - Xinzhou Jin; Jintang Li; Liang Chen 001; Chenyun Yu; Yuanzhen Xie; Tao Xie; Chengxiang Zhuo; Zang Li; Zibin Zheng (CoRR, 2024)

Revisiting and Benchmarking Graph Autoencoders: A Contrastive Learning Perspective. - Jintang Li; Ruofan Wu; Yuchang Zhu; Huizhe Zhang; Xinzhou Jin; Guibin Zhang; Zulun Zhu; Zibin Zheng; Liang Chen 001 (CoRR, 2024)

Heterogeneous graph contrastive learning for cold start cross-domain recommendation. - Yuanzhen Xie; Chenyun Yu; Xinzhou Jin; Lei Cheng 005; Bo Hu; Zang Li (Knowl. Based Syst., 2024)