Yue ZHANG, Ph.D.

Natural Language Processing Lab


Email: zhangyue@westlake.edu.cn


yue zhang westlake university
yue zhang westlake university

Yue ZHANG, Ph.D.

Natural Language Processing Lab


Email: zhangyue@westlake.edu.cn


"It has been exciting joining Westlake University, where colleagues are conducting innovative research in different areas of natural and mathematical sciences. I have been enjoying my work with my lab members, and wish that our research will contribute to this great environment."


Dr. Yue Zhang currently works as a tenured full professor at Westlake University. From Sep 2018 to Jun 2022, he worked as a tenured associate professor at Westlake University. From Jul 2012 to Aug 2018, he worked as an assistant professor at Singapore University of Technology and Design (SUTD). Before joining SUTD, Yue Zhang worked as a postdoctoral research associate at the University of Cambridge. He received a Ph.D. from the University of Oxford in Dec 2009 and an MSc degree from the University of Oxford in Oct 2006, working on statistical machine translation from Chinese to English by parsing. Yue Zhang received his undergraduate degree in Computer Science from Tsinghua University, China. He served as the reviewer for top journals such as Computational Linguistics, Transaction of Association of Computational Linguistics (action editor), IEEE Transaction on Big Data (associate editor), ACM Transactions on Asian and Low Resource Language Information Processing (associate editor) and Journal of Artificial Intelligence Research. He was the PC co-chair at EMNLP 2022, IALP 2017 and CCL 2020. He was also the area chair of ACL 2017/18/19/20, COLING 2014/18, NAACL 2015/19, EMNLP 2015/17/19/20, EACL 2021 and IJCAI 2021.


Yue Zhang leads the text intelligence lab on language technologies research. The main goal is to investigate robust open domain human language understanding and synthesis technologies and their downstream uses. Current work can be categorized into three tiers. On the bottom level, machine learning algorithms are investigated on fundamental representations and languages, including syntax, semantics and world knowledge information. We are currently working on deep learning and transfer learning algorithms. On the second level, fundamental NLP tasks such as syntactic and semantic analysis and text synthesis for Chinese and English are investigated, and information extraction tasks involving entities, relations, events and sentiments are explored. On the top level, text mining tasks that leverage our language technologies are also investigated, and we have worked on financial technologies based on text understanding, bio NLP and educational tasks. 

Representative Publications

1. Leyang Cui, Yu Wu, Shujie Liu, Yue Zhang and Ming Zhou. 2020. MuTual: A Dataset for Multi-Turn Dialogue Reasoning. In Proceedings of ACL.

2. Wenyu Du, Zhouhan Lin, Yikang Shen, Timothy J. O’Donnell, Yoshua Bengio and Yue Zhang. 2020. Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach. In Proceedings of ACL.

3. Yuan Zhang, Yue Zhang. 2019. Tree Communication Models for Sentiment Analysis. In Proceedings of ACL.

4. Chen Jia, Xiaobo Liang, Yue Zhang. 2019. Cross-Domain NER using Cross-Domain Language Modeling. In Proceedings of ACL.

5. Yue Zhang and Jie Yang. Chinese NER Using Lattice LSTM. In Proceedings of ACL 2018.

6. Yue Zhang, Qi Liu and Linfeng Song. Sentence-State LSTM for Text Representation. In Proceedings of ACL 2018.

7. Jiangming Liu, Yue Zhang. 2017. In-Order Transition-based  Constituent Parsing. In Transactions of the Association of ComputationalLinguistics (TACL).

8. Jie Yang, Yue Zhang, Fei Dong. Neural Word Segmentation with Rich Pretraining. In Proceedings of the 55th Annual Meeting of the Association forComputational Linguistics (ACL 2017). Vancouver, Canada, July.

9. Ching-Yun Chang, Yue Zhang, Zhiyang Teng, Zahn Bozanic, Bin Ke. Measuring the Information Content of Financial News. In Proceedings of the 2016 International Conference on Computational Linguistics (Coling). Osaka, Japan, December.

10. Duy-Tin Vo and Yue Zhang. Target-dependent Twitter Sentiment Classification with Rich Automatic Features. In Proceedings of IJCAI 2015, Buenos Aires, Argentina, July.

11. Fei Dong and Yue Zhang. Automatic Features for Essay Scoring -- An Empirical Study. In Proceeddings of EMNLP 2016. Austin, Texas, USA, November. 

12. Hao Zhou, Yue Zhang, Shujian Huang and Jiajun Chen. A Neural Probabilistic Structured-Prediction Model fo Transition-based Dependency Parsing. In Proceedings of ACL 2015, Beijing, China, July.

13. Yue Zhang and Stephen Clark. 2015. Syntax-based word ordering using learning-guided search. In Computational Linguistics 41(3). September. Pages 503 – 538.

14. Yue Zhang, Kai Song, Linfeng Song, Jingbo Zhu and Qun Liu. Syntactic SMT Using a Discriminative Text Generation Model. In Proceedings of EMNLP 2014. Doha, Qatar, October.

15. Ji Ma, Yue Zhang and Jingbo Zhu. Tagging The Web: Building A Robust Web Tagger with Neural Network. In Proceedings of ACL 2014. Baltimore, USA, June. 

16. Meishan Zhang, Yue Zhang, Wanxiang Che and Ting Liu. Chinese Parsing Exploiting Characters. In proceedings of ACL 2013. Sophia, Bulgaria. August.

17. Muhua Zhu, Yue Zhang, Wenliang Chen, Min Zhang and Jingbo Zhu. Fast and Accurate Shift-Reduce Constituent Parsing. In proceedings of ACL 2013. Sophia, Bulgaria. August.

18. Yue Zhang, Graeme Blackwood and Stephen Clark. Syntax-Based Word Ordering Incorporating a Large-Scale Language Model. In proceedings of EACL 2012. Avignon, France. April.

19. Yue Zhang and Joakim Nivre. Analyzing the Effect of Global Learning and  Beam-Search for Transition-Based Dependency Parsing. In proceedings of COLING 2012, posters. Mumbai, India. December. 

20. Yue Zhang and Joakim Nivre. Transition-Based Dependency Parsing with Rich Non-Local Features. In proceedings of ACL 2011, short papers. Portland, USA. June.

21. Yue Zhang and Stephen Clark. 2011. Syntactic Processing Using the Generalized Perceptron and Beam Search. In Computational Linguistics 37(1). March. Pages 105 – 151.

22. Yue Zhang, Byung-Gyu Ahn, Stephen Clark, Curt Van Wyk, James R. Curran and Laura Rimell. Chart Pruning for Fast Lexicalised-Grammar Parsing. In proceedings of COLING 2010. Beijing, China. August.

23. Yue Zhang and Stephen Clark. Transition-Based Parsing of the Chinese Treebank Using  a Global Discriminative Model. In proceedings of IWPT 2009. Paris, France. October.

24. Yue Zhang and Stephen Clark. A Tale of Two Parsers: Investigating and Combining Graph-Based And transition-Based Dependency Parsing Using Beam-search.In proceedings of EMNLP 2008. Hawaii, USA. October.

25. Yue Zhangand Stephen Clark. Chinese Segmentation Using a Word-Based Perceptron Algorithm. In proceedings of ACL 2007.  Prague, Czech Republic. June.