This is Xiaohan Li (李霄寒). I am a Senior Data Scientist at Walmart Global Tech. I got my Ph.D. in Computer Science from the University of Illinois at Chicago (UIC), under the supervision of Prof. Philip S. Yu.
My research interests are large language models, multi-modal language models, diffusion models, and recommender systems. Now I am working on Generative AI applications in e-commerce and recommender systems.
Publications (* means equal contribution)
Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding, ACM WWW 2024
Zezhong Fan, Xiaohan Li Chenhao Fang, Kaushiki Nag, Topojoy Biswas, Jianpeng Xu, Kannan
LLM-Ensemble: Optimal Large Language Models Ensemble Method for E-commerce Product Attribute Value Extraction. Tech Report
Chenhao Fang, Xiaohan Li, Zezhong Fan, Jianpeng Xu, Kaushiki Nag, Evren Korpeoglu, Sushant Kumar, Kannan Achan. PDF
Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation, IEEE BigData 2023 Regular Paper
Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S Yu PDF
A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder, IEEE ICDM 2023
Zheng Liu, Xiaohan Li, Philip Yu PDF
Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs. Tech Report
Jiao Chen*, Luyi Ma*, Xiaohan Li*, Nikhil Thakurdesai, Jianpeng Xu, Jason H.D. Cho, Kaushiki Nag, Evren Korpeoglu, Sushant Kumar, Kannan Achan PDF
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. IEEE BigData 2022 Regular Paper (Acceptance rate: 19.1%)
Xiaohan Li*, Yuqing Liu*, Zheng Liu, Philip Yu PDF
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. IEEE BigData 2022 Regular Paper (Acceptance rate: 19.1%)
Xiaohan Li*, Zheng Liu*, Luyi Ma, Kaushiki Nag, Stephen Guo, Philip Yu, Kannan Achan PDF
Mitigating Health Disparities in EHR via Deconfounder. ACM BCB 2022
Zheng Liu, Xiaohan Li, Philip Yu PDF
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. IEEE BigData 2021 Regular Paper (Acceptance rate: 19.9%)
Xiaohan Li, Zhiwei Liu, Stephen Guo, Zheng Liu, Hao Peng, Philip Yu, and Kannan Achan PDF
Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. ACM SIGIR 2021 short paper (Acceptance rate: 27.6%)
Zheng Liu* , Xiaohan Li*, Zeyu You, Tao Yang, Wei Fan, and Philip Yu PDF
Basket Recommendation with Multi-Intent Translation Graph Neural Network. IEEE BigData 2020 Regular Paper (Acceptance rate: 15.5%)
Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, and Philip S. Yu PDF
Heterogeneous Similarity Graph Neural Network on Electronic Health Record. IEEE BigData 2020 Regular Paper (Acceptance rate: 15.5%)
Zheng Liu, Xiaohan Li, Lifang He, Hao Peng, and Philip Yu PDF
Dynamic Graph Collaborative Filtering. IEEE ICDM 2020 Regular Paper (Acceptance rate: 9.8%)
Xiaohan Li*, Mengqi Zhang* , Shu Wu, Zheng Liu, Liang Wang, Philip S. Yu PDF
Blood Pressure Prediction via Recurrent Models with Contextual Layer. ACM WWW 2017 (Acceptance rate: 17.0%)
Xiaohan Li, Shu Wu, Liang Wang PDF