Pre-training Graph Neural Network for Cross Domain Recommendation. - Chen Wang 052; Yueqing Liang; Zhiwei Liu 001; Tao Zhang 055; Philip S. Yu (CogMI, 2021)

Pre-training Graph Neural Network for Cross Domain Recommendation. - Chen Wang 018; Yueqing Liang; Zhiwei Liu 001; Tao Zhang 055; Philip S. Yu (CoRR, 2021)

Artificial Intelligence Algorithms for Treatment of Diabetes. - Mudassir M. Rashid; Mohammad-Reza Askari; Canyu Chen; Yueqing Liang; Kai Shu; Ali Cinar (Algorithms, 2022)

Joint Adversarial Learning for Cross-domain Fair Classification. - Yueqing Liang; Canyu Chen; Tian Tian; Kai Shu (CoRR, 2022)

On Fair Classification with Mostly Private Sensitive Attributes. - Canyu Chen; Yueqing Liang; Xiongxiao Xu; Shangyu Xie; Yuan Hong 001; Kai Shu (CoRR, 2022)

Fair classification via domain adaptation: A dual adversarial learning approach. - Yueqing Liang; Canyu Chen; Tian Tian; Kai Shu (Frontiers Big Data, 2022)

Collaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language Model. - Chen Wang 052; Liangwei Yang; Zhiwei Liu 001; Xiaolong Liu; Mingdai Yang; Yueqing Liang; Philip S. Yu (CoRR, 2023)

Beyond Detection: Unveiling Fairness Vulnerabilities in Abusive Language Models. - Yueqing Liang; Lu Cheng 001; Ali Payani; Kai Shu (CoRR, 2023)

Investigating Gender Euphoria and Dysphoria on TikTok: Characterization and Comparison. - SJ Dillon; Yueqing Liang; H. Russell Bernard; Kai Shu (ASONAM (3), 2024)

Collaborative Alignment for Recommendation. - Chen Wang 052; Liangwei Yang; Zhiwei Liu 001; Xiaolong Liu; Mingdai Yang; Yueqing Liang; Philip S. Yu (CIKM, 2024)

Understanding the concerns and choices of public when using large language models for healthcare. - Yunpeng Xiao; Kyrie Zhixuan Zhou; Yueqing Liang; Kai Shu (CoRR, 2024)

Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction. - Chen Wang 018; Fangxin Wang 003; Ruocheng Guo; Yueqing Liang; Kay Liu; Philip S. Yu (CoRR, 2024)

Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting. - Xiongxiao Xu; Yueqing Liang; Baixiang Huang; Zhiling Lan; Kai Shu (CoRR, 2024)

Taxonomy-Guided Zero-Shot Recommendations with LLMs. - Yueqing Liang; Liangwei Yang; Chen Wang 018; Xiongxiao Xu; Philip S. Yu; Kai Shu (COLING, 2025)

Piecing It All Together: Verifying Multi-Hop Multimodal Claims. - Haoran Wang 005; Aman Rangapur; Xiongxiao Xu; Yueqing Liang; Haroon Gharwi; Carl Yang 001; Kai Shu (COLING, 2025)

Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation Systems. - Yuwei Cao; Liangwei Yang; Zhiwei Liu 001; Yuqing Liu 003; Chen Wang 052; Yueqing Liang; Hao Peng 001; Philip S. Yu (WWW (Companion Volume), 2025)

Benchmarking LLMs for Political Science: A United Nations Perspective. - Yueqing Liang; Liangwei Yang; Chen Wang; Congying Xia; Rui Meng; Xiongxiao Xu; Haoran Wang 005; Ali Payani; Kai Shu (CoRR, 2025)

Can Multimodal LLMs Perform Time Series Anomaly Detection? - Xiongxiao Xu; Haoran Wang 005; Yueqing Liang; Philip S. Yu; Yue Zhao 016; Kai Shu (CoRR, 2025)