Yinya Huang

Yinya Huang

Yinya Huang is a Postdoc Fellow at ETH AI Center, ETH Zürich, working with Prof. Mrinmaya Sachan and Prof. Elliot Ash. She received her Ph.D. Degree in Computer Science from Sun Yat-sen University, advised by Prof. Xiaodan Liang and Prof. Liang Lin.

Her research focues AI for math, AI for science, and reliable machine learning. She explores methodologies, high-quality data synthesis, and evaluations for general mathematical reasoning and formal theorem proving with LLMs. She investigates LLM reasoning capabilities to physics reasoning and other scientific and industrial fields. She studies reliable machine learning, including logical consistency, step-wise verification, and commonsense awareness.

She has published papers in TPAMI, NeurIPS, ICLR, ACL, EMNLP, NAACL, AAAI, and so forth. She won the 2024 ACM SIGCSE China Excellent Doctoral Dissertation Award and the 2023 SAAI Outstanding Doctoral Dissertation Award. She serves as a Senior Area Chair for EMNLP, an Area Chair for ACL ARR, a program committee member for ICML, ICLR, NeurIPS, ACL, EMNLP, and AAAI, and a reviewer for TNNLS and JAIR. She is also the primary organizer for the ICML AI for Math Workshop Series (2024, 2025).

Yinya Huang is looking for self-motivated master’s (thesis) students who can devote sufficient time to research. Email me if you are interested.

Drop an email if you are interested in collaboration.

News

All Publications

Kun Xiang, Heng Li, Terry Jingchen Zhang, Yinya Huang, Zirong Liu, Peixin Qu, Jixi He, Jiaqi Chen, Yu-Jie Yuan, Jianhua Han, Hang Xu, Hanhui Li, Mrinmaya Sachan, Xiaodan Liang (2025). SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning. arXiv.

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Yu Fan, Jingwei Ni, Jakob Merane, Etienne Salimbeni, Yang Tian, Yoan Hermstrüwer, Yinya Huang, Mubashara Akhtar, Florian Geering, Oliver Dreyer, Daniel Brunner, Markus Leippold, Mrinmaya Sachan, Alexander Stremitzer, Christoph Engel, Elliott Ash, Joel Niklaus (2025). LEXam: Benchmarking Legal Reasoning on 340 Law Exams. arXiv.

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Zhiyuan Wang, Bokui Chen, Yinya Huang, Qingxing Cao, Ming He, Jianping Fan, Xiaodan Liang (2025). ORMind: A Cognitive-Inspired End-to-End Reasoning Framework for Operations Research. Industry Track Paper of The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025).

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Zhicheng Yang, Zhijiang Guo, Yinya Huang, Xiaodan Liang, Yiwei Wang, Jing Tang (2025). TreeRPO: Tree Relative Policy Optimization. arXiv.

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Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, Jing Tang (2025). OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling. The Thirteenth International Conference on Learning Representations (ICLR 2025).

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Jianqiao Lu, Yingjia Wan, Yinya Huang, Jing Xiong, Zhengying Liu, Zhijiang Guo (2025). FormalAlign: Automated Alignment Evaluation for Autoformalization. The Thirteenth International Conference on Learning Representations (ICLR 2025).

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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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Sichun Luo, Yuxuan Yao, Bowei He, Yinya Huang, Aojun Zhou, Xinyi Zhang, Yuanzhang Xiao, Mingjie Zhan, Linqi Song (2023). Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation. arXiv preprint arXiv:2312.16018.

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Sichun Luo, Bowei He, Haohan Zhao, Yinya Huang, Aojun Zhou, Zongpeng Li, Yuanzhang Xiao, Mingjie Zhan, Linqi Song (2023). RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation. arXiv preprint arXiv:2312.16018.

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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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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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Yinya Huang, Hongming Zhang, Ruixin Hong, Xiaodan Liang, Changshui Zhang, Dong Yu (2022). MetaLogic: Logical Reasoning Explanations with Fine-Grained Structure. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Abu Dhabi, United Arab Emirates, December 7-11, 2022.

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Professional Service

Workshops:

Program Chair:

  • 2nd AI for Math Workshop (ICML 2025)
  • AI for Math Workshop (ICML 2024)

Senior Area Chair:

  • EMNLP (2025)

Area Chair:

Program Committee Member:

  • ICML (2025)
  • ICLR (2025, 2024)
  • NeurIPS (2025, 2024, 2023)
  • ACL (2024, 2023)
  • EMNLP (2024, 2023, 2022)
  • NAACL (2024)
  • COLM (2024)
  • ACM MM (2024)
  • IJCAI (2024)
  • ICLR Workshop (2021)
  • COLING (2020)
  • AAAI (2020)

Journal Reviewer:

Awards