Yinya Huang

Yinya Huang

Yinya Huang is currently a postdoctoral fellow in the Department of Computer Science at the City University of Hong Kong. She received her Ph.D. degree in Computer Science from Sun Yat-sen University, where she was adviced by Prof. Xiaodan Liang and Prof. Liang Lin at the Human Cyber Physical Intelligence Integration Lab (HCP-I2 Lab). She was meanwhile a research intern at Tencent AI Lab, Seattle led by Dr. Dong Yu, where she had the honor to work with Prof. Meng Fang, Prof. Liwei Wang, Dr. Kun Xu, and Dr. Hongming Zhang. She also received a strong background in logic and computational linguistics from the Institute of Logic and Cognition at Sun Yat-sen University, which has deepened and widened her research on complex reasoning in natural language processing.

Her recent interest in general lies in evaluating and improving models’ system 2 thinking, especially large language models’ complex reasoning (e.g., mathematical reasoning, theorem proving, logical reasoning, counterfactual thinking, and commonsense reasoning) and further applications (e.g., operations research problem solving, automated assistants).

Yinya Huang is on the job market! Feel free to contact if you are interested in research collaborations or have any job recommendations :D

Interests
  • Large Language Models
  • Complex Reasoning
  • Theorem Proving
Education

  • Ph.D. in Computer Science, 2023

    HCP Lab, Sun Yat-sen University

  • MPhil in Logic, 2018

    Institute of Logic and Cognition, Sun Yat-sen University

  • BPhil in Logic, 2015

    Institute of Logic and Cognition, Sun Yat-sen University

News

All Publications

Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, Jing Tang (2024). OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling. arXiv preprint arXiv:2407.09887.

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Xiaohan Lin, Qingxing Cao, Yinya Huang, Haiming Wang, Jianqiao Lu, Zhengying Liu, Linqi Song, Xiaodan Liang (2024). FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving. The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS 2024 D&B Track).

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Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang (2024). Proving Theorems Recursively. The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024).

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Jianqiao Lu, Zhengying Liu, Yingjia Wan, Yinya Huang, Haiming Wang, Zhicheng Yang, Jing Tang, Zhijiang Guo (2024). Process-Driven Autoformalization in Lean 4. arXiv preprint arXiv:2406.01940.

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Jianqiao Lu, Zhiyang Dou, Hongru Wang, Zeyu Cao, Jianbo Dai, Yingjia Wan, Yinya Huang, Zhijiang Guo (2024). AUTOCV: Empowering Reasoning with Automated Process Labeling via Confidence Variation. arXiv preprint arXiv:2405.16802.

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Yinya Huang, Ruixin Hong, Hongming Zhang, Wei Shao, Zhicheng Yang, Dong Yu, Changshui Zhang, Xiaodan Liang, Linqi Song (2024). CLOMO: Counterfactual Logical Modification with Large Language Models. The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).

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Xiaohan Lin, Qingxing Cao, Yinya Huang, Zhicheng Yang, Zhengying Liu, Zhenguo Li, Xiaodan Liang (2024). ATG: Benchmarking Automated Theorem Generation for Generative Language Models. 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024 Findings).

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Yinya Huang, Xiaohan Lin, Zhengying Liu, Qingxing Cao, Huajian Xin, Haiming Wang, Zhenguo Li, Linqi Song, Xiaodan Liang (2024). MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data. The Twelfth International Conference on Learning Representations (ICLR 2024).

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Haiming Wang, Huajian Xin, Chuanyang Zheng, Lin Li, Zhengying Liu, Qingxing Cao, Yinya Huang, Jing Xiong, Han Shi, Enze Xie, Jian Yin, Zhenguo Li, Heng Liao, Xiaodan Liang (2024). LEGO-Prover: Neural Theorem Proving with Growing Libraries. The Twelfth International Conference on Learning Representations (ICLR 2024).

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Zhicheng Yang, Yinya Huang, Jing Xiong, Liang Feng, Xiaodan Liang, Yiwei Wang, Jing Tang (2024). AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations. The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024 Findings).

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Yinya Huang, Lemao Liu, Kun Xu, Meng Fang, Liang Lin, Xiaodan Liang (2023). Discourse-Aware Graph Networks for Textual Logical Reasoning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).

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Jing Xiong, Jianhao Shen, Ye Yuan, Haiming Wang, Yichun Yin, Zhengying Liu, Lin Li, Zhijiang Guo, Qingxing Cao, Yinya Huang, Chuanyang Zheng, Xiaodan Liang, Ming Zhang, Qun Liu (2023). TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Sentosa, Singapore, December 6-10, 2023.

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Selected Experience

  • Research Intern, Tencent AI Lab, Seattle (remote), 2021.12 - 2022.8
    Topic: Natural language explanation
    Mentors: Dr. Hongming Zhang, Dr. Lemao Liu, Dr. Dong Yu
  • Research Intern, Tencent AI Lab, Seattle (remote), 2020.5 - 2021.12
    Topic: Natural language reasoning
    Mentors: Prof. Liwei Wang, Prof. Meng Fang, Dr. Kun Xu, Dr. Dong Yu
  • Teaching Assistant, Sun Yat-sen University, 2019.9 - 2020.1
    Course Title: Introduction to Deep Learning
    Instructor: Prof. Xiaodan Liang
  • Teaching Assistant, Sun Yat-sen University, 2018.3 - 2018.7
    Course Title: Deep Learning in Practice
    Instructor: Prof. Liang Lin

Professional Service

Workshops

Program Committee Member:

  • ICLR (2024)
  • NeurIPS (2024, 2023)
  • ACL (2024, 2023)
  • EMNLP (2024, 2023, 2022)
  • NAACL (2024)
  • COLM (2024)
  • COLING (2020)
  • ACM MM (2024)
  • IJCAI (2024)
  • ICLR Workshop (2021)

Journal Reviewer:

Awards