Yong Jiang

Alibaba DAMO Academy

Biography

Hi! I currently work at Alibaba DAMO Academy. I received my Ph.D from the joint program of ShanghaiTech University and University of Chinese Academy of Sciences. I was very fortunate to be advised by Prof. Kewei Tu. I am interested in machine learning and natural language processing.

My current research mainly focuses on multilingual NLP, structured prediction and so on. Ex amples are here. In my PhD time, I mainly worked on learning latent variable models for NLP problems and ML problems.

We have some research intern positions available in Alibaba DAMO Academy. If you are interested in NLP and ML, please feel free to contact me: jiangyong.ml@@gmail.com.

Interests

Natural Language Processing
Machine Learning
Deep Learning

Education

PhD in Computer Science, 2019

ShanghaiTech University
PhD in Computer Science, 2019

University of Chinese Academy of Sciences

Experience

Research Intern

Tencent AI Lab

Jan 2018 – Oct 2018 Shenzhen

Research Intern

Tencent

Jul 2017 – Sep 2017 Shanghai

Visiting Scholar

UC Berkeley

Aug 2016 – Feb 2016 California

Selected Publications

** indicates the intern/student author, * denotes equal contribution

Songlin Yang**, Yong Jiang, Wenjuan Han, Kewei Tu (2020). Second Order Unsupervised Neural Dependency Parsing. COLING 2020.

Wenjuan Han*, Yong Jiang*, Hwee Tou Ng, Kewei Tu (2020). A Survey of Unsupervised Dependency Parsing. COLING 2020.

Xinyu Wang**, Yong Jiang, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu (2020). AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network. EMNLP 2020.

Zechuan Hu**, Yong Jiang, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu (2020). An Investigation of Potential Function Designs for Neural CRF. Findings of EMNLP 2020.

Xinyu Wang**, Yong Jiang, Nguyen Bach, Tao Wang, Fei Huang, Kewei Tu (2020). More Embeddings, Better Sequence Labelers?. Findings of EMNLP 2020.

Wenjuan Han*, Liwen Zhang*, Yong Jiang, Kewei Tu (2020). Adversarial Attack and Defense of Structured Prediction Models. EMNLP 2020.

Jun Li**, Yifan Cao, Jiong Cai, Yong Jiang, Kewei Tu (2020). An Empirical Comparison of Unsupervised Constituency Parsing Methods. ACL 2020.

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Xinyu Wang**, Yong Jiang, Nguyen Bach, Tao Wang, Fei Huang, Kewei Tu (2020). Structure-Level Knowledge Distillation For Multilingual Sequence Labeling. ACL 2020.

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Wenjuan Han, Ge Wang, Yong Jiang, Kewei Tu (2019). Multilingual Grammar Induction with Continuous Language Identification. EMNLP 2019.

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Yong Jiang, Wenjuan Han, Kewei Tu (2019). A Regularization-Based Framework for Bilingual Grammar Induction. EMNLP 2019.

Wenjuan Han, Yong Jiang, Kewei Tu (2019). Enhancing Unsupervised Generative Dependency Parser with Contextual Information. ACL 2019.

Yunzhe Yuan**, Yong Jiang, Kewei Tu (2019). Bidirectional Transition-Based Dependency Parsing. AAAI 2020.

Jiong Cai**, Yong Jiang, Kewei Tu (2017). CRF Autoencoder for Unsupervised Dependency Parsing. EMNLP 2017.

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Yong Jiang, Wenjuan Han, Kewei Tu (2017). Combining Generative and Discriminative Approaches to Unsupervised Dependency Parsing via Dual Decomposition. EMNLP 2017.

Wenjuan Han, Yong Jiang, Kewei Tu (2017). Dependency Grammar Induction with Neural Lexicalization and Big Training Data. EMNLP 2017.

Shanbo Chu, Yong Jiang, Kewei Tu (2017). Latent Dependency Forest Models. AAAI 2017.

Jun Mei**, Yong Jiang, Kewei Tu (2017). Maximum A Posteriori Inference in Sum-Product Networks.

Xiao Zhang, Yong Jiang, Hao Peng, Kewei Tu, Dan Goldwasser (2017). Semi-supervised Structured Prediction with Neural CRF Autoencoder. EMNLP 2017.

Jiang Yong, Wenjuan Han, Kewei Tu (2016). Unsupervised Neural Dependency Parsing. EMNLP 2016.

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