Cheng Li
I got my Ph.D. in information science from the University of Michigan, Ann Arbor. My advisor is Qiaozhu Mei. I received my Bachelor's degree from the College of Computer Science and Technology at Zhejiang University, China. I am particularly interested in data mining, information retrieval, machine learning (especially deep learning), and natural language processing, with application to the retrieval, management, and analysis of data from Web, scientific literature, social networks, and various online communities. My publications can be found in Google Scholar
Authored Publications
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Bridging the Preference Gap between Retrievers and LLMs
Zixuan Ke
Qiaozhu Mei
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (2024) (to appear)
Learning to Rewrite Prompts for Personalized Text Generation
Qiaozhu Mei
Proceedings of the ACM Web Conference 2024
WSDM 2024 Workshop on Large Language Models for Individuals, Groups, and Society
Qiaozhu Mei
Vanessa Murdock
Jie Tang
Hongning Wang
Hamed Zamani
(2024) (to appear)
Job Type Extraction for Service Businesses
Yaping Qi
Hayk Zakaryan
Yonghua Wu
Companion Proceedings of the ACM Web Conference 2023
End-to-End Query Term Weighting
Karan Samel
Tao Chen
Swaraj Khadanga
Wensong Xu
Xingyu Wang
Kashyap Kolipaka
Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '23) (2023)
Learning Sparse Lexical Representations Over Expanded Vocabularies for Retrieval
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM '23) (2023)
SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23), ACM (2023) (to appear)
Multi-Aspect Dense Retrieval
Swaraj Khadanga
Wensong Xu
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM (2022)
LAMPRET: Layout-Aware Multimodal PreTraining for Document Understanding
Tao Chen
Te-Lin Wu
VIGIL-NAACL21 (2021)
