Portrait of Nan Duan

Nan Duan

Lead Researcher


Dr. Nan DUAN (段楠) is a Lead Researcher in the Natural Language Computing group at Microsoft Research Asia. He is working on fundamental NLP tasks, especially on:

  • Natural Language Understanding & Generation
  • (Conversational) Question Answering & Search
  • Multi-modal NLP with Text, Vision and Speech
  • Task-Oriented Dialogue System
  • Task-Oriented Open IE

Before joining Microsoft Research in Feb. 2012, he received his Ph.D. on Statistical Machine Translation from Tianjin University in 2011, under supervision of Dr. Ming ZHOU and Dr. Mu LI.

We are hiring researchers and interns now! If you have strong publications and experiences in above areas and are willing to work in MSRA, hit me up. 



  • 段楠,周明. 《智能问答》. 高等教育出版社, 2018. (published!)

Publication (#: students I mentored/collaborated in MSRA)

  • Daya Guo, Duyu Tang, Nan Duan, Jian Yin, Ming Zhou, “Dialog-to-Action: Conversational Question Answering over a Large-Scale Knowledge Base”, NIPS, 2018.
  • Daya Guo, Yibo Sun, Duyu Tang, Nan Duan, Ming Zhou, Jian Yin, “Question Generation from SQL Queries Improves Neural Semantic Parsing”, EMNLP, 2018.
  • Junwei Bao#, Yeyun Gong, Nan Duan, Ming Zhou, Tiejun Zhao, “Question Generation with Doubly-Adversarial Nets”, Transactions on Audio, Speech and Language Processing, 2018.
  • Pan Lu#, Lei Ji, Wei Zhang, Nan Duan, Ming Zhou, Jianyong Wang, “R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering”, KDD (long presentation), 2018.
  • Yibo Sun#, Duyu Tang, Nan Duan, Jianshu Ji, Guihong Cao, Xiaocheng Feng, Bing Qin, Ting Liu, Ming Zhou, “Semantic Parsing with Syntax- and Table-Aware SQL Generation”, ACL, 2018.
  • Zhao Yan#, Nan Duan, Junwei Bao, Peng Chen, Ming Zhou, Zhoujun Li, “Response Selection from Unstructured Documents for Human-Computer Conversation Systems”, Knowledge-Based System (Journal), 2018.
  • Yikang Li#Nan DuanBolei ZhouXiao ChuWanli OuyangXiaogang Wang, Ming Zhou, “Visual Question Generation as Dual Task of Visual Question Answering”, CVPR, 2018.
  • Duyu Tang, Nan Duan, Zhao Yan, Zhirui Zhang, Yibo Sun, Shujie Liu, Yuanhua Lv, Ming Zhou, “Learning to Collaborate for Question Answering and Asking”, NAACL, 2018.
  • Junwei Bao#, Duyu Tang, Nan Duan, Zhao Yan, Yuanhua Lv, Ming Zhou, Tiejun Zhao, “Table-to-Text: Describing Table Region with Natural Language”, AAAI, 2018.
  • Zhao Yan#, Duyu Tang, Nan Duan, Shujie Liu, Wendi Wang, Daxin Jiang, Ming Zhou, Zhoujun Li, “Assertion-based QA with Question-Aware Open Information Extraction”, AAAI, 2018.
  • Nan Duan and Duyu Tang, “Overview of the NLPCC 2017 Shared Task: Open Domain QA”, NLPCC, 2017.
  • Duyu TangNan DuanTao QinZhao YanMing Zhou, “Question Answering and Question Generation as Dual Tasks”, arXiv, 2017.
  • Zhao Yan#Duyu TangNan DuanJunwei BaoYuanhua LvMing ZhouZhoujun Li, “Content-Based Table Retrieval for Web Queries”, arXiv, 2017.
  • Nan Duan, Duyu Tang, Peng Chen, Ming Zhou, “Question Generation for Question Answering”, EMNLP, 2017.
  • Zhao Yan#, Nan Duan, Peng Chen, Ming Zhou, Jianshe Zhou, Zhoujun Li, “Building Task-Oriented Dialogue Systems for Online Shopping”, AAAI, 2017.
  • Zhao Yan#, Nan Duan, Ming Zhou, Zhoujun Li, “An Open Domain Topic Prediction Model for Answer Selection”, NLPCC-ICCPOL, 2016.
  • Nan Duan, “Overview of the NLPCC-ICCPOL 2016 Shared Task: Open Domain QA”, NLPCC-ICCPOL, 2016.
  • Junwei Bao#, Nan Duan, Zhao Yan, Ming Zhou, Tiejun Zhao, “Constraint-Based Question Answering with Knowledge Graph”, COLING, 2016.
  • Zhao Yan#, Nan Duan, Junwei Bao, Peng Chen, Ming Zhou, Zhoujun Li, Jianshe Zhou, “DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents”, ACL, 2016.
  • Nan Duan, “Overview of the NLPCC 2015 Shared Task: Open Domain QA”, NLPCC, 2015.
  • Pengcheng Yin#, Nan Duan, Ben Kao, Junwei Bao, Ming Zhou, “Answering Questions with Complex Semantic Constraints on Open Knowledge Bases”, CIKM, 2015.
  • Min-Chul Yang#, Nan Duan, Ming Zhou, Hae-Chang Rim, “Joint Relational Embeddings for Knowledge-based Question Answering”, EMNLP, 2014.
  • Junwei Bao#, Nan Duan, Ming Zhou, Tiejun Zhao, “Knowledge-based Question Answering as Machine Translation”, ACL, 2014.
  • 段楠, “从图谱搜索看搜索技术的发展趋势”, 《中国计算机学会通讯》, 2013.
  • Nan Duan, “Minimum Bayes Risk based Answer Re-ranking for Question Answering”, ACL, 2013.
  • Chenguang Wang#, Nan Duan, Ming Zhou, Ming Zhang, “Paraphrasing Adaptation for Web Search Ranking”, ACL, 2013.
  • Hong Sun#, Nan Duan, Yajuan Duan, Ming Zhou, “Answer Extraction from Passage Graph for Factoid Question Answering”, IJCAI, 2013.
  • Nan Duan, Mu Li, Ming Zhou, “Forced Derivation Tree based Model Training to Statistical Machine Translation”, EMNLP, 2012.
  • Nan Duan, “Consensus Decoding to Statistical Machine Translation”, Ph.D. thesis. (Chinese)
  • Nan Duan, Mu Li, Ming Zhou, “Improving Phrase Extraction via MBR Phrase Scoring and Pruning”, MT Summit XIII, 2011.
  • Nan Duan, Mu Li, Ming Zhou, “A Comparative Analysis of Consensus Decoding Methods for Statistical Machine Translation”, Journal of Chinese Information Processing, 2011. (Chinese)
  • Nan Duan, Mu Li, Ming Zhou, “Hypothesis Mixture Decoding for Statistical Machine Translation”, ACL, 2011.
  • Chi-Ho Li, Nan Duan, Yinggong Zhao, Shujie Liu, Lei Cui, Mei-yuh Hwang, Amittai Axelrod, Jianfeng Gao, Yaodong Zhang, Li Deng, “The MSRA Machine Translation System for IWSLT 2010”, IWSLT, 2010.
  • Nan Duan, Hong Sun, Ming Zhou, “Translation Model Generalization using Probability Averaging for Machine Translation”, COLING, 2010.
  • Nan Duan, Mu Li, Dongdong Zhang, Ming Zhou, “Mixture Model-based Minimum Bayes Risk Decoding using Multiple Machine Translation Systems”, COLING, 2010.
  • Nan Duan, Mu Li, Tong Xiao, Ming Zhou, “The Feature Subspace Method for SMT System Combination”, EMNLP, 2009.
  • Mu Li, Nan Duan, Dongdong Zhang, Chi-Ho Li, Ming Zhou, “Collaborative Decoding: Partial Hypothesis Re-ranking using Translation Consensus between Decoders”, ACL, 2009.
  • Dongdong Zhang, Chi-Ho Li, Nan Duan, Shujie Liu, Mu Li, Ming Zhou, “MSRA Technical Report for the 5th China Workshop on Machine Translation”, in CWMT, 2009.
  • Dongdong Zhang, Mu Li, Nan Duan, Chi-Ho Li, Ming Zhou, “Measure Word Generation for English-Chinese SMT Systems”, ACL, 2008.

Transfers & Patents

Technology Transfer

  1. QA-aware Pretraining for Bing (joint work with Yaobo Liang), 2018.
  2. Neural Semantic Parser for Cortana (joint work with Yeyun Gong and Duyu Tang), 2018.
  3. Question-aware Neural Open IE for Bing QA (joint work with Duyu Tang and Yaobo Liang), 2018.
  4. Text-based QA for Bing QA (joint work with Duyu Tang), 2017.
  5. Table-based QA for Bing QA (joint work with Duyu Tang), 2017.
  6. List-based QA for Bing QA (joint work with Duyu Tang), 2017.
  7. Knowledge-based QA for Xiaoice Core Chat, 2017.
  8. DocChat for Xiaoice Customer Service, 2016.
  9. Text Paraphrasing for EMOI Service in Sogou Mobile IME, 2016.
  10. Task-Oriented Dialogue System for Xiaoice Shopping Assistant on JD.COM, 2015.
  11. Query Rewriting for Bing Ads & Relevance, 2014.
  12. SCFG-based Semantic Parsing for Bing QA, 2014.
  13. NLP Ranker for Bing Relevance, 2013.


  1. Multi-modal QA/Chat, 2018.
  2. Conversational Question Answering, 2018.
  3. Assertion-based Question Answering, 2017.
  4. Generation of Text from Structured Data, 2017.
  5. Document-based Chat (DocChat), 2016.

Activities & Talks


  • Evaluation Co-Chair. NLPCC, 2016, 2017, 2018.
  • Distinguished Speaker. CCF, 2017.
  • Secretary of Committee on Terminology. CCF, 2016-2017.


  • Knowledge-enhanced NLP: Progress and Challenge. NLPCC Technical Workshops, 2018.
  • Latest Progress of Question Answering. CCF Tech Frontier-04, 2017.
  • Building Informational Bot (InfoBot) with Question Answering & Generation. CCF ADL-86, 2017.
  • Latest Progress of Question Answering. Tianjin University, Tsinghua University, and Peking University, 2017.
  • Knowledge-based Question Answering. CCF ADL-55, 2014.


  1. Multi-grade Semantic Parsing Dataset (English)
  2. Assertion-based QA Dataset (English)
  3. Knowledge-based QA Dataset (Chinese)
  4. Text-based QA Dataset (Chinese)
  • Download links will be updated soon~