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ORCIDXiaohan Li 0001
Person information
- affiliation: Walmart Global Tech, Sunnyvale, CA, USA
- affiliation: University of Illinois at Chicago, IL, USA
Other persons with the same name
- Xiaohan Li — disambiguation page
- Xiaohan Li 0002
![[0000-0002-0206-9031]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-0206-9031")
— TU Berlin, Faculty of Mechanical Engineering and Transport Systems, Human-Machine Systems, Germany - Xiaohan Li 0003 — Tianjin University, School of Electrical and Information Engineering, China
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Conference and Workshop Papers
- 2024
[c13]Chenhao Fang, Xiaohan Li, Zezhong Fan, Jianpeng Xu, Kaushiki Nag, Evren Körpeoglu, Sushant Kumar, Kannan Achan:
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction. SIGIR 2024: 2910-2914- [c12]Zezhong Fan, Xiaohan Li, Kaushiki Nag, Chenhao Fang, Topojoy Biswas, Jianpeng Xu, Kannan Achan:
Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding. WWW (Companion Volume) 2024: 1530-1537 - 2023
- [c11]Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu:
Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation. IEEE Big Data 2023: 393-402 - [c10]Zheng Liu, Xiaohan Li, Philip S. Yu:
A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder. ICDM 2023: 1175-1180 - 2022
- [c9]Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating health disparities in EHR via deconfounder. BCB 2022: 6:1-6:6 - [c8]Xiaohan Li, Zheng Liu, Luyi Ma, Kaushiki Nag, Stephen Guo, Philip S. Yu, Kannan Achan:
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. IEEE Big Data 2022: 616-625 - [c7]Xiaohan Li, Yuqing Liu, Zheng Liu, Philip S. Yu:
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. IEEE Big Data 2022: 626-635 - 2021
- [c6]Xiaohan Li, Zhiwei Liu, Stephen Guo, Zheng Liu, Hao Peng, Philip S. Yu, Kannan Achan:
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. IEEE BigData 2021: 457-468 - [c5]Zheng Liu, Xiaohan Li, Zeyu You, Tao Yang, Wei Fan, Philip S. Yu:
Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. SIGIR 2021: 1965-1969 - 2020
- [c4]Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu:
Basket Recommendation with Multi-Intent Translation Graph Neural Network. IEEE BigData 2020: 728-737 - [c3]Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu:
Heterogeneous Similarity Graph Neural Network on Electronic Health Records. IEEE BigData 2020: 1196-1205 - [c2]Xiaohan Li, Mengqi Zhang, Shu Wu, Zheng Liu, Liang Wang, Philip S. Yu:
Dynamic Graph Collaborative Filtering. ICDM 2020: 322-331 - 2017
- [c1]Xiaohan Li, Shu Wu, Liang Wang:
Blood Pressure Prediction via Recurrent Models with Contextual Layer. WWW 2017: 685-693
Informal and Other Publications
- 2024
- [i12]Chenhao Fang, Xiaohan Li, Zezhong Fan, Jianpeng Xu, Kaushiki Nag, Evren Körpeoglu, Sushant Kumar, Kannan Achan:
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction. CoRR abs/2403.00863 (2024) - [i11]Zezhong Fan, Xiaohan Li, Chenhao Fang, Topojoy Biswas, Kaushiki Nag, Jianpeng Xu, Kannan Achan:
Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding. CoRR abs/2404.11589 (2024) - 2023
- [i10]Xiaohan Li, Yuqing Liu, Zheng Liu, Philip S. Yu:
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. CoRR abs/2301.03780 (2023) - [i9]Jiao Chen, Luyi Ma, Xiaohan Li, Nikhil Thakurdesai, Jianpeng Xu, Jason H. D. Cho, Kaushiki Nag, Evren Körpeoglu, Sushant Kumar, Kannan Achan:
Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs. CoRR abs/2305.09858 (2023) - [i8]Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating Health Disparity on Biased Electronic Health Records via Deconfounder. CoRR abs/2308.11819 (2023) - [i7]Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu:
Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation. CoRR abs/2311.09577 (2023) - 2022
- [i6]Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating Health Disparities in EHR via Deconfounder. CoRR abs/2210.15901 (2022) - [i5]Xiaohan Li, Zheng Liu, Luyi Ma, Kaushiki Nag, Stephen Guo, Philip S. Yu, Kannan Achan:
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. CoRR abs/2211.09072 (2022) - 2021
- [i4]Xiaohan Li, Mengqi Zhang, Shu Wu, Zheng Liu, Liang Wang, Philip S. Yu:
Dynamic Graph Collaborative Filtering. CoRR abs/2101.02844 (2021) - [i3]Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu:
Heterogeneous Similarity Graph Neural Network on Electronic Health Records. CoRR abs/2101.06800 (2021) - [i2]Xiaohan Li, Zhiwei Liu, Stephen Guo, Zheng Liu, Hao Peng, Philip S. Yu, Kannan Achan:
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. CoRR abs/2111.14036 (2021) - 2020
- [i1]Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu:
Basket Recommendation with Multi-Intent Translation Graph Neural Network. CoRR abs/2010.11419 (2020)
Coauthor Index
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