Blood Pressure Prediction via Recurrent Models with Contextual Layer. - Xiaohan Li 001; Shu Wu; Liang Wang 001 (WWW, 2017)

Basket Recommendation with Multi-Intent Translation Graph Neural Network. - Zhiwei Liu 001; Xiaohan Li 001; Ziwei Fan 001; Stephen D. Guo; Kannan Achan; Philip S. Yu (IEEE BigData, 2020)

Heterogeneous Similarity Graph Neural Network on Electronic Health Records. - Zheng Liu 017; Xiaohan Li 001; Hao Peng 001; Lifang He 001; Philip S. Yu (IEEE BigData, 2020)

Dynamic Graph Collaborative Filtering. - Xiaohan Li 001; Mengqi Zhang; Shu Wu; Zheng Liu 017; Liang Wang 001; Philip S. Yu (ICDM, 2020)

Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. - Xiaohan Li 001; Zhiwei Liu 001; Stephen D. Guo; Zheng Liu 017; Hao Peng 001; Philip S. Yu; Kannan Achan (IEEE BigData, 2021)

Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. - Zheng Liu 017; Xiaohan Li 001; Zeyu You; Tao Yang 012; Wei Fan 001; Philip S. Yu (SIGIR, 2021)

Mitigating health disparities in EHR via deconfounder. - Zheng Liu 017; Xiaohan Li 001; Philip S. Yu (BCB, 2022)

Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. - Xiaohan Li 001; Yuqing Liu 003; Zheng Liu 017; Philip S. Yu (IEEE Big Data, 2022)

Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. - Xiaohan Li 001; Zheng Liu 017; Luyi Ma; Kaushiki Nag; Stephen D. Guo; Philip S. Yu; Kannan Achan (IEEE Big Data, 2022)

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation. - Xiaolong Liu; Liangwei Yang; Zhiwei Liu 001; Xiaohan Li 001; Mingdai Yang; Chen Wang 052; Philip S. Yu (IEEE Big Data, 2023)

A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder. - Zheng Liu 017; Xiaohan Li 001; Philip S. Yu (ICDM, 2023)

Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs. - Jiao Chen 005; Luyi Ma; Xiaohan Li 001; Nikhil Thakurdesai; Jianpeng Xu; Jason H. D. Cho; Kaushiki Nag; Evren Körpeoglu; Sushant Kumar; Kannan Achan (CoRR, 2023)

Mitigating Health Disparity on Biased Electronic Health Records via Deconfounder. - Zheng Liu 017; Xiaohan Li 001; Philip S. Yu (CoRR, 2023)

Multi-task Recommendation in Marketplace via Knowledge Attentive Graph Convolutional Network with Adaptive Contrastive Learning. - Xiaohan Li 001; Zezhong Fan; Luyi Ma; Kaushiki Nag; Kannan Achan (IEEE Big Data, 2024)

Improving Sequential Recommender Systems with Online and In-store User Behavior. - Luyi Ma; Aashika Padmanabhan; Anjana Ganesh; Shengwei Tang; Jiao Chen 005; Xiaohan Li 001; Lalitesh Morishetti; Kaushiki Nag; Malay Patel; Jason H. D. Cho; Sushant Kumar; Kannan Achan (IEEE Big Data, 2024)

3rd International Workshop on Industrial Recommendation Systems (IRS). - Luyi Ma; Xiaohan Li 001; Kamilia Ahmadi; Jianpeng Xu; Philip S. Yu; George Karypis (CIKM, 2024)

LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction. - Chenhao Fang; Xiaohan Li 001; Zezhong Fan; Jianpeng Xu; Kaushiki Nag; Evren Körpeoglu; Sushant Kumar; Kannan Achan (SIGIR, 2024)

Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding. - Zezhong Fan; Xiaohan Li 001; Kaushiki Nag; Chenhao Fang; Topojoy Biswas; Jianpeng Xu; Kannan Achan (WWW (Companion Volume), 2024)

Triple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior Recommendations. - Luyi Ma; Xiaohan Li 001; Zezhong Fan; Jianpeng Xu; Jason H. D. Cho; Praveenkumar Kanumala; Kaushiki Nag; Sushant Kumar; Kannan Achan (CoRR, 2024)

Relation labeling in product knowledge graphs with large language models for e-commerce. - Jiao Chen 005; Luyi Ma; Xiaohan Li 001; Jianpeng Xu; Jason H. D. Cho; Kaushiki Nag; Evren Körpeoglu; Sushant Kumar; Kannan Achan (Int. J. Mach. Learn. Cybern., 2024)