Zhaopeng Tu

Principal Researcher
Tencent AI Lab
tuzhaopeng@gmail.com

Bio

Zhaopeng Tu is a principal researcher at Tencent AI Lab, whose research focuses on deep learning for natural language processing (NLP). He is currently working on neural machine translation (NMT) and Seq2Seq learning for other NLP tasks, such as dialogue and question answering. He has published over 40 papers in leading NLP/AI journals and conferences such as ACL, EMNLP, TACL, AAAI, and IJCAI. He served as ACL2019, EMNLP2018-2019, NAACL2019 machine translation area co-chair, and AAAI2019 senior PC member.

Publications

2020

• Zi-Yi Dou, Xing Wang, Shuming Shi, and Zhaopeng Tu*. Exploiting Deep Representations for Natural Language Processing. Journal of NeuroComputing, 2020.
• Jian Li, Xing Wang, Baosong Yang, Shuming Shi, Michael R. Lyu, and Zhaopeng Tu*. Neuron Interaction Based Representation Composition for Neural Machine Translation. AAAI 2020.
• Yong Wang, Longyue Wang, Shuming Shi, Victor O.K. Li, and Zhaopeng Tu. Go From the General to the Particular: Multi-Domain Translation with Domain Transformation Networks. AAAI 2020.
• Tianxiang Zhao, Lemao Liu, Guoping Huang, Zhaopeng Tu, Huayang Li, Yingling Liu, Guiquan Liu, and Shuming Shi. Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation. AAAI 2020.

2019

• Baosong Yang, Longyue Wang, Derek F. Wong, Lidia S. Chao, and Zhaopeng Tu*. Assessing the Ability of Self-Attention Networks to Learn Word Order. ACL 2019.
• Xing Wang, Zhaopeng Tu, Longyue Wang, and Shuming Shi. Exploiting Sentential Context for Neural Machine Translation. ACL 2019 (Short).
• Shilin He, Zhaopeng Tu*, Xing Wang, Longyue Wang, Michael R. Lyu, and Shuming Shi. Towards Understanding Neural Machine Translation with Word Importance. EMNLP 2019.
• Longyue Wang, Zhaopeng Tu, Xing Wang, and Shuming Shi. One Model to Learn Both: Zero Pronoun Prediction and Translation. EMNLP 2019.
• Jie Hao, Xing Wang, Shuming Shi, Jinfeng Zhang, and Zhaopeng Tu. Multi-Granularity Self-Attention for Neural Machine Translation. EMNLP 2019.
• Zaixiang Zheng, Shujian Huang, Zhaopeng Tu, Xinyu Dai, and Jiajun Chen. Dynamic Past and Future for Neural Machine Translation. EMNLP 2019.
• Deng Cai, Yan Wang, Wei Bi, Zhaopeng Tu, Xiaojiang Liu, and Shuming Shi. Retrieval-guided Dialogue Response Generation via a Matching-to-Generation Framework. EMNLP 2019.
• Xing Wang, Zhaopeng Tu, Longyue Wang, and Shuming Shi. Self-Attention Networks with Structural Position Encoding. EMNLP 2019 (Short).
• Jie Hao, Xing Wang, Shuming Shi, Jinfeng Zhang, and Zhaopeng Tu. Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons. EMNLP 2019 (Short).
• Jian Li, Baosong Yang, Zi-Yi Dou, Xing Wang, Michael R. Lyu, and Zhaopeng Tu*. Information Aggregation for Multi-Head Attention with Routing-by-Agreement. NAACL 2019.
• Jie Hao, Xing Wang, Baosong Yang, Longyue Wang, Jinfeng Zhang, and Zhaopeng Tu*. Modeling Recurrence for Transformer. NAACL 2019.
• Deng Cai, Yan Wang, Wei Bi, Zhaopeng Tu, Xiaojiang Liu, Wai Lam, and Shuming Shi. Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory. NAACL 2019.
• Baosong Yang, Longyue Wang, Derek F. Wong, Lidia S. Chao, and Zhaopeng Tu*. Convolutional Self-Attention Networks. NAACL 2019 (Short).
• Xiang Kong, Zhaopeng Tu*, Shuming Shi, Eduard Hovy, and Tong Zhang. Neural Machine Translation with Adequacy-Oriented Learning. AAAI 2019.
• Zi-Yi Dou, Zhaopeng Tu*, Xing Wang, Longyue Wang, Shuming Shi, and Tong Zhang. Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement. AAAI 2019.
• Baosong Yang, Jian Li, Derek F. Wong, Lidia S. Chao, Xing Wang, and Zhaopeng Tu*. Context-Aware Self-Attention Networks. AAAI 2019.

2018

• Yong Cheng, Zhaopeng Tu, Fandong Meng, Junjie Zhai, and Yang Liu. Towards Robust Neural Machine Translation. ACL 2018.
• Zi-Yi Dou, Zhaopeng Tu*, Xing Wang, Shuming Shi, and Tong Zhang. Exploiting Deep Representations for Neural Machine Translation. EMNLP 2018.
• Baosong Yang, Zhaopeng Tu*, Derek F. Wong, Fandong Meng, Lidia S. Chao, and Tong Zhang. Modeling Localness for Self-Attention Networks. EMNLP 2018.
• Jian Li, Zhaopeng Tu*, Baosong Yang, Michael R. Lyu, and Tong Zhang. Multi-Head Attention with Disagreement Regularization. EMNLP 2018 (Short).
• Longyue Wang, Zhaopeng Tu*, Andy Way, and Qun Liu. Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism. EMNLP 2018 (Short).
• Fandong Meng, Zhaopeng Tu, Yong Cheng, Haiyang Wu, Junjie Zhai, Yuekui Yang, and Di Wang. Neural Machine Translation with Key-Value Memory-Augmented Attention. IJCAI 2018.
• Longyue Wang, Zhaopeng Tu*, Shuming Shi, Tong Zhang, Yvette Graham, and Qun Liu. Translating Pro-Drop Languages with Reconstruction Models. AAAI 2018.
• Xintong Li, Lemao Liu, Zhaopeng Tu, Shuming Shi, and Max Meng. Target Foresight Based Attention for Neural Machine Translation. NAACL 2018.
• Zhaopeng Tu, Yang Liu, Shuming Shi, and Tong Zhang. Learning to Remember Translation History with a Continuous Cache. Transactions of the Association for Computational Linguistics (TACL), 2018.
• Zaixiang Zheng, Hao Zhou, Shujian Huang, Lili Mou, Xinyu Dai, Jiajun Chen, and Zhaopeng Tu. Modeling Past and Future for Neural Machine Translation. Transactions of the Association for Computational Linguistics (TACL), 2018.
• Xing Wang, Zhaopeng Tu, and Min Zhang. Incorporating Statistical Machine Translation Word Knowledge into Neural Machine Translation. IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2018.
• Zhaopeng Tu, Yong Jiang, Xiaojiang Liu, Lei Shu, and Shuming Shi. Generative Stock Question Answering. arXiv:1804.07942. [data]

2017

• Junhui Li, Deyi Xiong, Zhaopeng Tu, Muhua Zhu, and Guodong Zhou. Modeling Source Syntax for Neural Machine Translation. ACL 2017.
• Hao Zhou, Zhaopeng Tu, Shujian Huang, Xiaohua Liu, Hang Li, and Jiajun Chen. Chunk-Based Bi-Scale Decoder for Neural Machine Translation. ACL 2017 (Short).
• Xing Wang, Zhaopeng Tu, Deyi Xiong, and Min Zhang. Translating Phrases in Neural Machine Translation. EMNLP 2017.
• Longyue Wang, Zhaopeng Tu*, Andy Way, and Qun Liu. Exploiting Cross-Sentence Context for Neural Machine Translation. EMNLP 2017 (Short).
• Zhaopeng Tu, Yang Liu, Lifeng Shang, Xiaohua Liu, and Hang Li. Neural Machine Translation with Reconstruction. AAAI 2017. [code]
• Xing Wang, Zhengdong Lu, Zhaopeng Tu, Hang Li, Deyi Xiong, and Min Zhang. Neural Machine Translation Advised by Statistical Machine Translation. AAAI 2017.
• Zhaopeng Tu, Yang Liu, Zhengdong Lu, Xiaohua Liu, and Hang Li. Context Gates for Neural Machine Translation. Transactions of the Association for Computational Linguistics (TACL), 2017. [code]

2016

• Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, and Hang Li. Modeling Coverage for Neural Machine Translation. ACL 2016. [code]
• Longyue Wang, Zhaopeng Tu, Xiaojun Zhang, Hang Li, Andy Way, and Qun Liu. A Novel Approach for Dropped Pronoun Translation. NAACL 2016.
• Longyue Wang, Xiaojun Zhang, Zhaopeng Tu, Hang Li, and Qun Liu. Dropped Pronoun Generation for Dialogue Machine Translation. ICASSP 2016.
• Baishakhi Ray, Vincent Hellendoorn, Saheel Godhane, Zhaopeng Tu, Alberto Bacchelli, and Premkumar Devanbu. On the "Naturalness" of Buggy Code. ICSE 2016.
• Anh Nguyen, Zhaopeng Tu, and Tien Nguyen. Do Contexts Help in Phrase-based, Statistical Source Code Migration? ICSME 2016.
• Longyue Wang, Xiaojun Zhang, Zhaopeng Tu, Andy Way, and Qun Liu. The Automatic Construction of Discourse Corpus for Dialogue Translation. LREC 2016.
• Longyue Wang, Zhaopeng Tu, Xiaojun Zhang, Siyou Liu, Hang Li, Andy Way, and Qun Liu. A Novel and Robust Approach for Pro-Drop Language Translation. Journal of Machine Translation, 2016.

2015

• Zhaopeng Tu, Baotian Hu, Zhengdong Lu, and Hang Li. Context-Dependent Translation Selection Using Convolutional Neural Network. arXiv 2015. (Short version is accepted by ACL 2015 (Short))
• Christine Franks, Zhaopeng Tu, Prem Devanbu, and Vincent Hellendoorn. CACHECA: A Cache Language Model Based Code Suggestion Tool. ICSE 2015 - Demonstration Track. (Demo of the "localness" work)
• Fandong Meng, Zhengdong Lu, Zhaopeng Tu, Hang Li, and Qun Liu. A Deep Memory-based Architecture for Sequence-to-Sequence Learning. arXiv 2015.

2014

• Zhaopeng Tu, Zhendong Su, and Prem Devanbu. On the Localness of Software. FSE 2014. [code] [data]

2010 ~ 2013

• Qun Liu, Zhaopeng Tu, and Shouxun Lin. A Novel Graph-based Compact Representation of Word Alignment. ACL 2013 (Short).
• Zhaopeng Tu, Yifan He, Jennifer Foster, Josef van Genabith, Qun Liu, and Shouxun Lin. Identifying High-Impact Sub-Structures for Convolution Kernels in Document-level Sentiment Classification. ACL 2012 (Short).
• Junhui Li, Zhaopeng Tu, Guodong Zhou, and Josef van Genabith. Head-Driven Hierarchical Phrase-based Translation. ACL 2012 (Short).
• Zhaopeng Tu, Yang Liu, Yifan He, Josef van Genabith, Qun Liu, and Shouxun Lin. Combining Multiple Alignments to Improve Machine Translation. COLING 2012. [data]
• Junhui Li, Zhaopeng Tu, Guodong Zhou, and Josef van Genabith. Using Syntactic Head Information in Hierarchical Phrase-based Translation. WMT 2012.
• Zhaopeng Tu, Wenbin Jiang, Qun Liu, and Shouxun Lin. Dependency Forest for Sentiment Analysis. NLP&CC 2012.
• Zhaopeng Tu, Yang Liu, Qun Liu, and Shouxun Lin. Extracting Hierarchical Rules from a Weighted Alignment Matrix. IJCNLP 2011.
• Zhaopeng Tu, Yang Liu, Young-Sook Hwang, Qun Liu, and Shouxun Lin. Dependency Forest for Statistical Machine Translation. COLING 2010.