Xueqing Liu
Assistant Professor
Charles V. Schaefer, Jr. School of Engineering and Science
Department of Computer Science
Research
Text mining and natural language processing, especially applications to software engineering and security, including: using NLP to assist security and software engineering tasks and automated machine learning for natural language processing
Experience
Research Intern, Allen Institute for AI, 2019
Research Intern, Walmart Labs, 2015
Research Intern, Microsoft Research, 2014
Research Intern, Walmart Labs, 2015
Research Intern, Microsoft Research, 2014
Institutional Service
- Faculty search committee Member
- DEI committee Member
- DEI committee Member
- Faculty search committee Member
- Faculty search committee Member
Professional Service
- NAACL, ACL, COLM 2024 Reviewer for ACL rolling review (Dec, Feb, April) and COLM 2024
- ASE 2023 Program Committee
- AAAI 2023 Program Committee
- NAACL 2022 Reviewer
- ACL 2022 Reviewer
- ACL 2021 Program committee member
- EMNLP 2020 reviewer
- NSF panelist
Selected Publications
Guanqun Yang, Mirazul Haque, Qiaochu Song, Wei Yang and Xueqing Liu. "TestAug: A Framework for Augmenting Capability-based NLP Tests." In The 29th International Conference on Computational Linguistics (COLING 2022).
Chi Wang, Qingyun Wu, Xueqing Liu, Luis Quintanilla. "Automated Machine Learning & Tuning with FLAML" In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022 Hands-on Tutorial).
Yang, Guanqun, Shay Dineen, Zhipeng Lin, and Xueqing Liu. "Few-Sample Named Entity Recognition for Security Vulnerability Reports by Fine-Tuning Pre-Trained Language Models." In Proceedings of The 2nd International Workshop on Deployable Machine Learning for Security Defense (MLHat@KDD 2021).
Liu, Xueqing, and Chi Wang. "An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models." In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021).
Guo, Jiaqi, Qian Liu, Jian-Guang Lou, Zhenwen Li, Xueqing Liu, Tao Xie, and Ting Liu. "Benchmarking meaning representations in neural semantic parsing." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1520-1540. 2020.
Chi Wang, Qingyun Wu, Xueqing Liu, Luis Quintanilla. "Automated Machine Learning & Tuning with FLAML" In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022 Hands-on Tutorial).
Yang, Guanqun, Shay Dineen, Zhipeng Lin, and Xueqing Liu. "Few-Sample Named Entity Recognition for Security Vulnerability Reports by Fine-Tuning Pre-Trained Language Models." In Proceedings of The 2nd International Workshop on Deployable Machine Learning for Security Defense (MLHat@KDD 2021).
Liu, Xueqing, and Chi Wang. "An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models." In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021).
Guo, Jiaqi, Qian Liu, Jian-Guang Lou, Zhenwen Li, Xueqing Liu, Tao Xie, and Ting Liu. "Benchmarking meaning representations in neural semantic parsing." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1520-1540. 2020.
Courses
CS284 Data Structure
CS589 Text Mining and Information Retrieval
CS589 Text Mining and Information Retrieval