Fei Liu
Associate Professor
Department of Computer Science
Emory University, Atlanta, GA 30322
Email: fei.liu@emory.edu
Office: W302-G
Short Biography
Dr. Fei Liu is an Associate Professor in the Computer Science Department at Emory University. Her areas of expertise include natural language processing, deep learning, large language models, and artificial intelligence. Dr. Liu is committed to advancing the state of the art in natural language understanding and generation by developing innovative model architectures, training methodologies, and robust evaluation metrics. With an excess of information available from various sources, Dr. Liu's research plays a vital role in devising efficient techniques to process and make sense of this vast amount of data.
Dr. Liu held a postdoctoral fellowship at Carnegie Mellon University and was a member of Noah's ARK. She also worked as a senior scientist at Bosch Research in Palo Alto, California. Bosch is one of the largest German companies and a leading provider of intelligent car systems and home appliances. Liu received her Ph.D. in computer science from the University of Texas at Dallas, supported by the Erik Jonsson Distinguished Research Fellowship, and holds bachelor's and master's degrees in computer science from Fudan University. Dr. Liu has published over 80 peer-reviewed papers in leading conferences and journals and she regularly serves on the program committees of major international conferences. In 2015, she was selected for the "MIT Rising Stars in EECS" program. Her research has been recognized with several awards, including a Best Paper Award Finalist at WWW 2016, an Area Chair Favorite Paper at COLING 2018, an Amazon AWS Machine Learning Research award in 2020, and NSF's CAREER award in 2022.
Research Interests
- Large Language Models
- Automatic Summarization
- Generative AI
- Natural Language Processing
- Deep Learning
Recent Publications [Full List] [Google Scholar]
- SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs
Yebowen Hu, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Hassan Foroosh, Dong Yu and Fei Liu
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), 2024
- InFoBench: Evaluating Instruction Following Ability in Large Language Models
Yiwei Qin, Kaiqiang Song, Yebowen Hu, Wenlin Yao, Sangwoo Cho, Xiaoyang Wang, Xuansheng Wu, Fei Liu, Pengfei Liu and Dong Yu
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), Findings, 2024
- Rescue: Ranking LLM Responses with Partial Ordering to Improve Response Generation
Yikun Wang, Rui Zheng, Haoming Li, Qi Zhang, Tao Gui and Fei Liu
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), SRW, 2024
- DecipherPref: Analyzing Influential Factors in Human Preference Judgments via GPT-4
Yebowen Hu, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Hassan Foroosh and Fei Liu
In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
- MeetingBank: A Benchmark Dataset for Meeting Summarization
Yebowen Hu, Tim Ganter, Hanieh Deilamsalehy, Franck Dernoncourt, Hassan Foroosh and Fei Liu
In Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics (ACL), 2023
- Generating User-Engaging News Headlines
Pengshan Cai, Kaiqiang Song, Sangwoo Cho, Hongwei Wang, Xiaoyang Wang, Hong Yu, Fei Liu and Dong Yu
In Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics (ACL), 2023
- Toward Unifying Text Segmentation and Long Document Summarization
Sangwoo Cho, Kaiqiang Song, Xiaoyang Wang, Fei Liu and Dong Yu
In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
- Towards Abstractive Grounded Summarization of Podcast Transcripts
Kaiqiang Song, Chen Li, Xiaoyang Wang, Dong Yu and Fei Liu
In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL), 2022
- StreamHover: Livestream Transcript Summarization and Annotation
Sangwoo Cho, Franck Dernoncourt, Tim Ganter, Trung Bui, Nedim Lipka, Walter Chang, Hailin Jin, Jonathan Brandt, Hassan Foroosh and Fei Liu
In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
- CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021
- MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance
Wei Zhao, Maxime Peyrard, Fei Liu, Yang Gao, Christian M. Meyer and Steffen Eger
In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP), Hong Kong, China, 2019
- Toward Abstractive Summarization Using Semantic Representations
Fei Liu, Jeffrey Flanigan, Sam Thomson, Norman Sadeh and Noah A. Smith
In Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL), Denver, Colorado, 2015
Professional Service
- Senior area chair, NAACL 2024, ACL 2024, Natural Language Generation track
- Editor, Artificial Intelligence Journal (AIJ), 2024--
- Associate Editor, Journal of Artificial Intelligence Research (JAIR), 2023--
- Action Editor, Transactions of the ACL (TACL), 2022--
- Senior area chair, EMNLP 2021, 2022
- Area chair, NAACL 2021, ACL 2021
- General Publications Chair, EMNLP 2020
- Senior area chair, ACL 2020
- Senior program committee, AAAI 2020, 2022
- Area chair, NAACL 2019, ACL 2019
- Publications chair, EMNLP 2019
- Demonstrations chair, ACL 2018
- Area chair, EMNLP 2018
- Co-organizer, EMNLP Workshop on New Frontiers in Summarization, biennially 2017--2023
- NSF/IIS Panel and Ad-hoc Reviewer, 2016, 2019--2023