Email: thisisjcykcd AT gmail.com
- Aug. 2018 - Present
Ph.D. student, The Chinese University of Hong Kong
- Sept. 2015 - Mar. 2018
M.S., Dept. of Computer Science, Shanghai Jiao Tong University
- Sept. 2011 - Jun. 2015
B.E., Dept. of Computer Science, Xiamen University
- Jul. 2017 - Jan. 2018, Visiting scholar
Singapore University of Technology and Design, Advisor: Prof. Yue Zhang
- Feb. 2017 -Jun. 2017, Research intern
Tencent AI Lab, Mentors: Dr. Xiaojiang Liu, Dr. Shuming Shi
- Sept. 2015 -Feb. 2017, Research assistant
Shanghai Jiao Tong University, Supervisor: Prof. Hai Zhao
Publications: (Google Scholar)
- Translating Math Word Problem to Expression Tree.
Lei Wang, Yan Wang, Deng Cai, Dongxiang Zhang and Xiaojiang Liu In Proceedings of the EMNLP 2018 Conference, 2018. (EMNLP 2018).
- Fast and Accurate Neural Word Segmentation for Chinese. [paper] [code]
Deng Cai, Hai Zhao. In Proceedings of the ACL 2017 Conference, 2017. (ACL 2017).
- Chinese Word Segmentation, a decade review (2007-2017).
Zhao Hai, Cai Deng, Huang Changning, Kit Chunyu. The Frontier of Empirical and Corpus Linguistics, Chunyu Kit and Meijun Liu ed., China Social Sciences Press, 2017.
- A Hybrid Model for Chinese Spelling Check. [paper]
Deng Cai*, Hai Zhao* (first authors), Yang Xin, Yuzhu Wang, Zhongye Jia. ACM Transactions on Asian Low-Resource Language Information Process, 2017. (TALLIP).
- Neural Word Segmentation Learning for Chinese. [paper] [code] [slides]
Deng Cai and Hai Zhao. In Proceedings of the ACL 2016 Conference, 2016. (ACL 2016).
Open Source Projects: (Github Profile)
- Chinese Word Segmentation
Efficient and effective neural Chinese word segmentation algorithms. Our framwork directly models the structure of Chinese word sequence. This work has been presented at ACL2016
- Greedy Chinese Word Segmentation
Direct structured prediction approach for CWS with improved speed and accuracy. This work has been presented at ACL2017
- Dependency Parser
This is a Dynet version of Biaffine dependency parser, achieving state-of-the-art performance. I tested many domain daptation methods on this model.
I actively use and contribute to Dynet. A list of my contributions is here .
- Implicit Discourse Relation Classification
Pair-aware sentence modeling for Implicit Discourse Relation Classification. A summary of this work: [paper]
Awards and Honors:
- National Scholarship for Graduate Student (top 2% students), Ministry of Education of P.R.China, 2016
- Excellent Undergraduate Thesis Award, XMU, 2015
- Dean's List, 2014, School of Information Science and Engineering, XMU, 2014
- Gold Medal, The 5-th Fujian Provincial University Programming Contest, 2014
- Bronze Medal, ACM-ICPC Asia Regional Programming Contest, 2013