Susan (Xueqing) Liu

250 Gateway South · Hoboken, NJ 07030 · USA · Email

Assistant professor at the Department of Computer Science of Stevens Institute of Technology.

I am actively looking for PhD students and post-docs working on NLP for SE/Security.

Research Interests

Natural language processing, text mining, information retrieval, and their application to software engineering and security are my areas of interest. Here is a list of topics I have worked on:

Education

University of Illinois Urbana-Champaign

Ph.D. in Computer Science

Tsinghua University, China

B.S. in Interdisciplinary Information Sciences (Yao Class)

Students

  • PhD students:
  • Alumni:
    • Murad Aleskerov (Aug 2023-Dec 2023)
    • Shubhankar Deol (Aug 2023-Dec 2023)
    • Shay Dineen (Feb 2021-Feb 2022): NLP for security
    • Zhipeng Lin (Aug 2020-Aug 2021): NLP for security

Publications

    • VulLibGen: Generating Names of Vulnerability-Affected Packages via a Large Language Model
      Tianyu Chen, Lin Li, Liuchuan Zhu, Zongyang Li, Xueqing Liu, Guangtai Liang, Qianxiang Wang, Tao Xie
      In the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024 Main Conference),
      Bangkok, Thailand, August 2024      .
      [Paper]

    • HateModerate: Testing Hate Speech Detectors against Content Moderation Policies
      Jiangrui Zheng, Xueqing Liu, Guanqun Yang, Mirazul Haque, Xing Qian, Ravishka Rathnasuriya, Wei Yang, Girish Budhrani
      In the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024 Finding),
      Mexico City, Mexico, June 2024      .
      [Paper]

    • Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference
      Chi Wang, Xueqing Liu, Ahmed H Awadallah
      In the AutoML Conference 2023,
      Berlin, Germany, September 2023      .
      [Paper]

    • Automated Machine Learning & Tuning with FLAML
      Chi Wang, Qingyun Wu, Xueqing Liu, Luis Quintanilla
      In the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022 Hands-on Tutorial),
      Washington D.C., US, August 2022      .
      [Paper]

    • TestAug: A Framework for Augmenting Capability-based NLP Tests
      Guanqun Yang, Mirazul Haque, Qiaochu Song, Wei Yang and Xueqing Liu
      To appear. In The 29th International Conference on Computational Linguistics (COLING 2022),
      Gyeongju, Republic of Korea, October 2022      .
      [Paper]

    • Few-Sample Named Entity Recognition for Security Vulnerability Reports by Fine-Tuning Pre-trained Language Models
      Guanqun Yang, Shay Dineen, Zhipeng Lin, Xueqing Liu
      In International Workshop on Deployable Machine Learning for Security Defense (MLHat @KDD 2021),
      Singapore, August 2021      .
      [Paper]

    • An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models
      Xueqing Liu, Chi Wang
      In The 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021 Main Conference),
      Virtual, August 2021      .
      [Paper]

    • Benchmarking Meaning Representations in Neural Semantic Parsing
      Jiaqi Guo, Qian Liu, Jian-Guang Lou, Zhenwen Li, Xueqing Liu, Tao Xie, Ting Liu
      In The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020 Main Conference),
      Virtual, November 2020      .
      [Paper]

    • Data-driven assistance for user decision making on mobile devices
      Ph.D. thesis. 2019
      [Thesis]

    • LinkSO: A Benchmark for Learning to Retrieve Similar Question-Answer Pairs on Software Development Forums
      X. Liu, Chi Wang, Yue Leng, ChengXiang Zhai.
      In ESEC/FSE Workshop on NLP for Software Engineering (NL4SE 2018),
      Lake Buena Vista, Florida, November 2018      .
      [Short Paper] [Dataset]

    • A Large-scale Empirical Study on Android Runtime-Permission Rationales
      X. Liu, Yue Leng, Wei Yang, Wenyu Wang, ChengXiang Zhai and Tao Xie.
      In Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2018), Lisbon, Portugal, October 2018.
      [Paper], [Dataset], [Slides]

    • Mining Android App Descriptions for Permission Requirements Recommendation
      X. Liu, Yue Leng, Wei Yang, ChengXiang Zhai and Tao Xie.
      In Proceedings of the IEEE International Requirements Engineering Conference (22.2%) (RE 2018),
      Banff, Canada, August 2018.
      [Paper], [Dataset], [Slides]

    • Visualizing Path Exploration to Assist Problem Diagnosis for Structural Test Generation
      Jiayi Cao, Angello Astorga, Siwakorn Srisakaokul, Zhengkai Wu, Xueqing Liu, Xusheng Xiao, and Tao Xie.
      In Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2018), Posters, Lisbon, Portugal, October 2018.
      [Short Paper], [Slides]

    • Information Retrieval Evaluation as Search Simulation: A General Formal Framework for IR Evaluation
      Yinan Zhang, X. Liu and ChengXiang Zhai.
      In Proceedings of the International Conference on the Theory of Information Retrieval (ICTIR 2017),
      Amsterdam, Netherland, October 2017.
      [Paper], [Demo]

    • Numerical Facet Range Partition: Evaluation Metric and Methods
      X. Liu, ChengXiang Zhai, Wei Han and Onur Gungor
      In Proceedings of the International on World Wide Web Conference (19.6%) (WWW 2017),
      Industry Track, Perth, Australia, April 2017.
      [Paper], [Slides]

    • User Fatigue in Online News Recommendation
      Hao Ma, X. Liu, Zhihong Shen
      In Proceedings of the International on World Wide Web Conference (17.3%) (WWW 2016),
      Industry Track, Montreal, Canada, April 2016.
      [Paper]

    • Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition Approach
      Chi Wang, X. Liu, Yanglei Song, Jiawei Han
      In Proceedings of the SIGKDD Conference on Knowledge Discovery and Data Mining (19.5%) (KDD 2015),
      Sydney, Australia, August 2015.
      [Paper], [Code]

    • Automatic Taxonomy Construction from Keywords via Scalable Bayesian Rose Trees
      Yangqiu Song, Shixia Liu, X. Liu, Haixun Wang
      In IEEE Transactions on Knowledge and Data Engineering (TKDE)
      Volume 27(7), Pages 1861 - 1874, July 2015.
      [Paper]

    • Scalable Moment-based Inference for Latent Dirichlet Allocation
      Chi Wang, X. Liu, Yanglei Song, Jiawei Han
      In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (23.8%) (ECML/PKDD 2014)
      Nancy, France, September 2014.
      [Paper]

    • Scalable Exact Inference for Topic Model
      Chi Wang, X. Liu, Yanglei Song, Jiawei Han
      In ICML Workshop on Moment Based Inference,
      Beijing, China, 2014.

    • Automatic Taxonomy Construction from Keywords
      X. Liu, Yangqiu Song, Shixia Liu, Haixun Wang
      In Proceedings of the SIGKDD Conference on Knowledge Discovery and Data Mining (17.6%) (KDD 2012),
      Beijing, China, August 2012.
      [Paper]

Teaching