Tianqing Fang

Tianqing Fang

final-year Ph.D. in HKUST

Tianqing Fang

I’m a final year Ph.D. student at the Department of Computer Science and Engineering in Hong Kong University of Science and Technology (HKUST), supervised by Prof. Yangqiu Song. I’m visiting EPFL, working with Prof. Antoine Bosselut. Previously, I was a visiting research scholar at University of Southern California, working with Prof. Muhao Chen. I received my B.E. degree from Zhejiang University in 2019, supervised by Prof. Yang Yang. Here is my Curriculum Vitae (Oct 2023).

I’m actively seeking a postdoc position worldwide!

I will attend EMNLP 2023 in 🇸🇬Singapore in person. Feel free to reach out to me for a chat☕️.

Research Interest

  • Knowledge Acquisition: Commonsense knowledge acquisition at scale using information extraction (ASER) and knowledge base population (DISCOS, CKBP, PseudoReasoner); Conceptualization knowledge acquisition (AbstractATOMIC, CAT).
  • Reasoning with knowledge for (Large) Language Models: Integration of (abstract) commonsense knowledge to language models (CAR). Knowledge constrained decoding for LLMs (KCTS). Knowledge conflicts detection and mitigation (CDA).
  • Machine Learning for NLP: Data denoising (ODDA), training dynamics (QAD), …

News

  • 10/2023: Invited to serve as the PC for COLING-LREC 2024, and the reviewer for EACL 2023 (ARR).
  • 10/2023: 5 papers accepted to EMNLP. Topics includes zero-shot commonsense QA (2 findings), knowledge-constrained decoding (main), a benchmark for analogy reasoning (main), a benchmark for academic writing formalization (main).
  • 9/2023: Invited to serve as the PC for SDM 2024.
  • 6/2023: Invited to serve as the PC for AAAI 2024.
  • 5/2023: Two paper accepted to ACL 2023 main conference.
  • 4/2023: Preprints about ChatGPT on discourse relations and an updated benchmark of CSKB Population are released.

Publication

Preprint

  • Tianqing Fang, Zhaowei Wang, Wenxuan Zhou, Hongming Zhang, Yangqiu Song, Muhao Chen.
    Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoning, 2023
    [paper]

  • Tianqing Fang*, Quyet V. Do*, Sehyun Choi, Weiqi Wang, Yangqiu Song.
    CKBP v2: An Expert-Annotated Evaluation Set for Commonsense Knowledge Base Population, 2023 [paper] [code&data]

  • Chunkit Chan, Jiayang Cheng, Weiqi Wang, Yuxin Jiang, Tianqing Fang, Xin Liu, Yangqiu Song.
    ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relations, 2023 [paper]

  • Tianqing Fang, Wenxuan Zhou, Fangyu Liu, Hongming Zhang, Yangqiu Song, and Muhao Chen.
    On-the-fly Denoising for Data Augmentation in Natural Language Understanding, 2022.
    [paper]

  • Mutian He, Tianqing Fang, Weiqi Wang, and Yangqiu Song.
    Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization, 2022.
    [paper] [code]

Journal

2022

  • Hongming Zhang*, Xin Liu*, Haojie Pan*, Haowen Ke, Jiefu Ou, Tianqing Fang, and Yangqiu Song.
    ASER: Towards Large-scale Commonsense Knowledge Acquisition via Higher-order Selectional Preference over Eventualities.
    Artificial Intelligence, 2022. [paper] [arxiv] [code] [homepage]

Conference

2023

  • Sehyun Choi, Tianqing Fang, Zhaowei Wang, Yangqiu Song
    KCTS: Knowledge-Constrained Tree Search Decoding with Token-Level Hallucination Detection
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023 (Main Conference), [paper] [code]

  • Jiayang Cheng, Lin Qiu, Tsz Ho CHAN, Tianqing Fang, Weiqi Wang, Chunkit Chan, Qipeng Guo, Hongming Zhang, Yangqiu Song, Yue Zhang, Zheng Zhang
    STORYANALOGY: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023 (Main Conference), [paper] [code&data]

  • Shizhe Diao, Yongyu Lei, Liangming Pan, Tianqing Fang, Wangchunshu Zhou, Sedrick Scott Keh, Min-Yen Kan, Tong Zhang
    Doolittle: Benchmarks and Corpora for Academic Writing Formalization
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023 (Main Conference), [paper] [code&data]

  • Weiqi Wang*, Tianqing Fang*, Wenxuan Ding, Baixuan Xu, Xin Liu, Yangqiu Song, Antoine Bosselut.
    CAR: Conceptualization-Augmented Reasoner for Zero-Shot Commonsense Question Answering, 2023
    Findings of Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP), 2023. [paper] [code]

  • Haochen SHI, Weiqi Wang, Tianqing Fang, Baixuan Xu, Wenxuan Ding, Xin Liu, Yangqiu Song
    QADYNAMICS: Training Dynamics-Driven Synthetic QA Diagnostic for Zero-Shot Commonsense Question Answering
    Findings of Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP), 2023. [paper] [code]

  • Weiqi Wang*, Tianqing Fang*, Baixuan Xu, Chun Yi Louis Bo, Yangqiu Song, Lei Chen.
    🐈CAT: A Contextualized Conceptualization and Instantiation Framework for Commonsense Reasoning
    Annual Meeting of the Association for Computational Linguistics (ACL), 2023. [pdf] [code].

  • Zhaowei Wang, Quyet V. Do, Hongming Zhang, Jiayao Zhang, Weiqi Wang, Tianqing Fang, Yangqiu Song, Ginny Y. Wong, Simon See
    COLA: Contextualized Commonsense Causality Reasoning from the Causal Inference Perspective
    Annual Meeting of the Association for Computational Linguistics (ACL), 2023. [pdf] [code].

2022

  • Tianqing Fang, Quyet V. Do, Hongming Zhang, Yangqiu Song, Ginny Y. Wong and Simon See.
    PseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Population.
    Findings of Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP), 2022. [pdf] [code].
    Internship work at NVIDIA

  • Ying Su, Zihao Wang, Tianqing Fang, Hongming Zhang, Yangqiu Song and Tong Zhang.
    MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation.
    Findings of Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP), 2022. [pdf] [code].

  • Zhaowei Wang, Hongming Zhang, Tianqing Fang, Yangqiu Song, Ginny Y. Wong and Simon See.
    SubeventWriter: Iterative Sub-event Sequence Generation with Coherence Controller.
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022. [pdf] [code].

  • Ziqian Zeng, Weimin Ni, Tianqing Fang, Xiang Li, Xinran Zhao, and Yangqiu Song.
    Weakly Supervised Text Classification using Supervision Signals from a Language Model.
    Findings of Annual Conference of the North American Chapter of the Association for Computational Linguistics (Findings of NAACL), 2022. [pdf] [code].

2021

  • Tianqing Fang*, Weiqi Wang*, Sehyun Choi, Shibo Hao, Hongming Zhang, Yangqiu Song, Bin He.
    Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Dataset.
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021 (Main Conference), [pdf] [code] [video]

  • Tianqing Fang, Haojie Pan, Hongming Zhang, Yangqiu Song, Kun Xu, Dong Yu.
    Do Boat and Ocean Suggest Beach? Dialogue Summarization with External Knowledge.
    Conference on Automated Knowledge Base Construction (AKBC), 2021. [pdf] [code]
  • Nedjma Ousidhoum, Xinran Zhao, Tianqing Fang, Yangqiu Song, and Dit-Yan Yeung.
    Probing Toxic Content in Large Pre-Trained Language Models.
    Annual Meeting of the Association for Computational Linguistics (ACL), 2021. [pdf] [code]
  • Tianqing Fang, Hongming Zhang, Weiqi Wang, Yangqiu Song, and Bin He.
    DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense Knowledge.
    The Web Conference (WWW), 2021. [pdf] [code] [video]

*: Equal Contribution

Awards

  • HKUST Overseas Research Award (2023)
  • HKUST RedBird Academic Excellence Award for Continuing PhD Students in 2022/23 (2023)
  • HKUST RedBird Academic Excellence Award for Continuing PhD Students in 2021/22 (2022)
  • Hong Kong Ph.D. Fellowship (2019-2023)
  • Special Scholarship for Undergraduate Students in Zhejiang University (one of the top honor in ZJU) (2018)
  • Provincial Scholarship (top 5%, ZJU, 2018)
  • 1st Place and MATLAB Innovation Award (1st/36K+) in Contemporary Undergraduate Mathematical Contest in Modeling (2017)
  • Provincial Scholarship (top 5%, ZJU, 2017)
  • National Scholarship (top 3%, ZJU, 2016)

Teaching

  • MSBD 5018: Natural Language Processing (Spring 2022)
  • COMP5222/MATH5471: Statistical Learning Models for Text and Graph Data. (Fall 2021)
  • MSBD6000H: Natural Language Processing. (Spring 2021)
  • COMP4901K/MATH4824B: Machine Learning for Natural Language Processing. (Fall 2020)
  • COMP4332/RMBI4310: Big Data Mining. (Spring 2020)

Academic Service

  • Conference Reviewer: ACL Rolling Review, AAAI’23, ACL’23, COLING’22, EMNLP’22, IJCAI’23, KDD’23
  • Conference External Reviewer: KDD’20, 21, ACL’21, EMNLP’21

Miscs:

I take pictures on weekends. Check out the highlights on unsplash.