Dual-Teacher Knowledge Distillation for Strict Cold-Start Recommendation. - Weizhi Zhang 001; Liangwei Yang; Yuwei Cao; Ke Xu 018; Yuanjie Zhu; Philip S. Yu (IEEE Big Data, 2023)

Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering. - Ke Xu 018; Yuanjie Zhu; Weizhi Zhang 001; Philip S. Yu (ICDM, 2023)

Graph Collaborative Signals Denoising and Augmentation for Recommendation. - Ziwei Fan 001; Ke Xu 018; Zhang Dong; Hao Peng 001; Jiawei Zhang 001; Philip S. Yu (SIGIR, 2023)

Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation. - Weizhi Zhang 001; Liangwei Yang; Zihe Song 001; Henry Peng Zou; Ke Xu 018; Liancheng Fang; Philip S. Yu (CIKM, 2024)

Mixed Supervised Graph Contrastive Learning for Recommendation. - Weizhi Zhang 001; Liangwei Yang; Zihe Song 001; Henry Peng Zou; Ke Xu 018; Yuanjie Zhu; Philip S. Yu (CoRR, 2024)

LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation. - Weizhi Zhang 001; Liangwei Yang; Wooseong Yang; Henry Peng Zou; Yuqing Liu 003; Ke Xu 018; Sourav Medya; Philip S. Yu (EMNLP (Industry Track), 2025)

SGCL: Unifying Self-Supervised and Supervised Learning for Graph Recommendation. - Weizhi Zhang 001; Liangwei Yang; Zihe Song 001; Henry Peng Zou; Ke Xu 018; Yuanjie Zhu; Philip S. Yu (RecSys, 2025)

Graph Neural Controlled Differential Equations For Collaborative Filtering. - Ke Xu 018; Weizhi Zhang 001; Zihe Song 001; Yuanjie Zhu; Philip S. Yu (WWW (Companion Volume), 2025)

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making. - Xiaopeng Yuan; Xingjian Zhang; Ke Xu 018; Yifan Xu; Lijun Yu; Jindong Wang 001; Yushun Dong; Haohan Wang (CoRR, 2025)

LLM-MemCluster: Empowering Large Language Models with Dynamic Memory for Text Clustering. - Yuanjie Zhu; Liangwei Yang; Ke Xu 018; Weizhi Zhang 001; Zihe Song 001; Jindong Wang 001; Philip S. Yu (CoRR, 2025)