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Principal Research Manager, Microsoft Cognitive Services Research Group Ph.D., Computer Science Department, Stanford University M.S., Statistics Department, Stanford University B. Eng., Computer Science & Technology Department, Tsinghua University Email: A [at] B, where A=chezhu and B is microsoft.com [ Google Scholar | Books | Publications | Patents | Mentored Interns ] |
I organize the Distinguished Talk Series in Microsoft Cognitive Services Research Group. If you're interested in giving a talk, please contact me.
Jan. 13, 2021: My team has achieved 1st place on CommonGen leaderboard.
Jan. 12, 2021: One paper accepted at ICLR 2021.
Dec. 4, 2020: My team has achieved 1st place on CommonsenseQA leaderboard.
Oct. 18, 2020: My team has achieved 1st place on FEVER leaderboard on fact verification in label accuracy.
Knowledge Graph, Text Summarization, Task-Oriented Dialogue
My recent work covers:
How to simultaneously pre-train knowledge graph and language model [ Paper ]
Increase factual correctness of abstractive summaries [ Paper ]
Summarize multi-party meeting transcripts [ Paper ]
Utilize positional bias in news articles for zero-shot summarization [ Paper ]
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Machine Reading Comprehension: Algorithm and Practice (Chinese Edition) 《机器阅读理解:算法与实践》 Chenguang Zhu China Machine Press (机械工业出版社) , 2020.03 [ Amazon.com | China-pub | jd.com | dangdang.com | tmall.com | Amazon.cn ] [ GitHub Code ] |
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Machine Reading Comprehension: Algorithm and Practice Chenguang Zhu Elsevier, 2021.05 [ Amazon.com | Google Books ] [ GitHub Code ] |
Text Summarization
文本摘要:浓缩的才是精华
Chenguang Zhu, Nanshan Zeng
Communications of the China Computer Federation (CCCF), 《中国计算机学会通讯》,Jul. 2020.
Machine Reading Comprehension: How to Make Computer Understand Articles
机器阅读理解:如何让计算机读懂文章
Chenguang Zhu
Communications of the China Computer Federation (CCCF), 《中国计算机学会通讯》,Feb. 2019.
Fusing Context Into Knowledge Graph for Commonsense Reasoning
Yichong Xu*, Chenguang Zhu*, Ruochen Xu, Yang Liu, Michael Zeng, Xuedong Huang
(*: Equal contribution)
arXiv preprint arXiv: 2012.04808, 2020.
[1st place on CommonsenseQA leaderboard, 2020.12.02]
A Survey of Knowledge-Enhanced Text Generation
Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu, Qingyun Wang, Heng Ji, Meng Jiang
arXiv preprint arXiv: 2010.04389, 2020.
JAKET: Joint Pre-training of Knowledge Graph and Language Understanding
Donghan Yu*, Chenguang Zhu*, Yiming Yang, Michael Zeng
(*: Equal contribution)
arXiv preprint arXiv: 2010.00796, 2020.
Semi-Supervised Speech-Language Joint Pre-Training for Spoken Language Understanding
Yu-An Chung*, Chenguang Zhu*, Michael Zeng
(*: Equal contribution)
arXiv preprint arXiv: 2010.02295, 2020.
Make Lead Bias in Your Favor: Zero-shot Abstractive News Summarization
[ Demo | Poster ]
Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
Conference on Neural Information Processing Systems (NeurIPS), Self-Supervised Learning - Theory and Practice Workshop, Vancouver, Canada, 2020.
[ arXiv ]
TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising
[ arXiv ]
Ziyi Yang*, Chenguang Zhu*, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
(*: Equal contribution)
Empirical Methods in Natural Language Processing (EMNLP), 2020.
A Hierarchical Network for Abstractive Meeting Summarization with Cross-Domain Pretraining
[ arXiv | Talk | Code ]
Chenguang Zhu*, Ruochen Xu*, Michael Zeng, Xuedong Huang
(*: Equal contribution)
Empirical Methods in Natural Language Processing (EMNLP), 2020.
Injecting Entity Types into Entity-Guided News Generation
Xiangyu Dong, Wenhao Yu, Chenguang Zhu and Meng Jiang
arXiv preprint arXiv: 2009.13401, 2020.
Mixed-Lingual Pre-training for Cross-lingual Summarization
[ arXiv ]
Ruochen Xu*, Chenguang Zhu*, Yu Shi, Michael Zeng, Xuedong Huang
(*: Equal contribution)
Asia-Pacific Chapter of the Association for Computational Linguistics (AACL), Suzhou, China, 2020.
Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization
[ arXiv | Poster ]
Beliz Gunel, Chenguang Zhu, Michael Zeng, Xuedong Huang
Conference on Neural Information Processing Systems (NeurIPS), Knowledge Representation & Reasoning Meets Machine Learning (KR2ML workshop), Vancouver, Canada, 2019.
RADDLE: An Evaluation Benchmark and Analysis Platform for Robust Task-oriented Dialog Systems
[ Leaderboard ]
Baolin Peng, Chunyuan Li, Zhu Zhang, Chenguang Zhu, Jinchao Li, Jianfeng Gao
arXiv preprint arXiv: 2012.14666, 2020.
Few-shot Natural Language Generation for Task-Oriented Dialog
[ arXiv | Code & Demo ]
Baolin Peng, Chenguang Zhu, Chunyuan Li, Xiujun Li, Jinchao Li, Michael Zeng, Jianfeng Gao
Empirical Methods in Natural Language Processing (EMNLP), 2020.
Boosting Naturalness of Language in Task-oriented Dialogues via Adversarial Training
[ Talk ]
Chenguang Zhu
Special Interest Group on Discourse and Dialogue (SIGdial), Boise, Idaho, 2020.
Meta Dialogue Policy Learning
Yumo Xu, Chenguang Zhu, Baolin Peng, Michael Zeng
arXiv preprint arXiv: 2006.02588, 2020.
Multi-task Learning for Natural Language Generation in Task-Oriented Dialogue
[ Poster ]
Chenguang Zhu, Michael Zeng, Xuedong Huang
Empirical Methods in Natural Language Processing (EMNLP), Hong Kong, China, 2019.
SIM: A Slot-Independent Neural Model for Dialogue State Tracking
[ Talk at Stanford HAI OVAL | Poster ]
Chenguang Zhu, Michael Zeng, Xuedong Huang
Special Interest Group on Discourse and Dialogue (SIGdial), Stockholm, Sweden, 2019.
Filtered Inner Product Projection for Multilingual Embedding Alignment
Vin Sachidananda, Ziyi Yang, Chenguang Zhu
International Conference on Learning Representations (ICLR), Vienna, Austria, 2021.
[ arXiv ]
Parameter-free Sentence Embedding via Orthogonal Basis
[ Code | Slides | Talk ]
Ziyi Yang, Chenguang Zhu, Weizhu Chen
Empirical Methods in Natural Language Processing (EMNLP), Hong Kong, China, 2019.
Embedding Imputation with Grounded Language Information
[ Poster ]
Ziyi Yang, Chenguang Zhu, Vin Sachidananda, Eric Darve
Association for Computational Linguistics (ACL), Florence, Italy, 2019.
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering
[ Code | Poster ]
Jianmo Ni, Chenguang Zhu, Weizhu Chen, Julian McAuley.
North American Chapter of the Association for Computational Linguistics (NAACL), Minneapolis, USA, 2019.
SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering
[ Code ]
Chenguang Zhu, Michael Zeng, Xuedong Huang.
arXiv preprint arXiv: 1812.03593, 2018.
FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension
[ Code | Poster ]
Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen, Weizhu Chen.
International Conference on Learning Representations (ICLR), Vancouver, Canada, 2018.
Reducing Inefficiencies in Taxi Systems
Chenguang Zhu, Balaji Prabhakar.
56th IEEE Conference on Decision and Control (CDC), Melbourne, Australia, 2017.
Measuring the Pulse of a City Via Taxi Operation: Case Study
Chenguang Zhu, Balaji Prabhakar.
Transportation Research Board 96th Annual Meeting, Washington, D.C., 2017.
Reducing Road Congestion Through Incentives: A Case Study
Chenguang Zhu, Jia Shuo Yue, Chinmoy V. Mandayam, Deepak Merugu, Hossein Karkeh Abadi, Balaji Prabhakar.
Transportation Research Board 94th Annual Meeting, Washington, D.C., 2015.
Featured on The New York Times, The Wall Street Journal, International Business Times, Ars Technica and Stanford News
Polling One's Friends: A Graph Theoretic View
Chenguang Zhu, Hossein Karkeh Abadi, Balaji Prabhakar.
53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2015.
Information Diffusion and External Influence in Networks
Seth A. Myers, Chenguang Zhu, Jure Leskovec.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2012
A Novel Click Model and Its Applications to Online Advertising
Zeyuan Allen Zhu, Weizhu Chen, Tom Minka, Chenguang Zhu, Zheng Chen.
ACM International Conference on Web Search and Data Mining (WSDM), 2010
A General Magnitude-Preserving Boosting Algorithm for Search Ranking
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang Wang, Dong Wang, Zheng Chen.
ACM Conference on Information and Knowledge Management (CIKM), 2009
Inverse Time Dependency in Convex Regularized Learning
Zeyuan Allen Zhu, Weizhu Chen, Chenguang Zhu, Gang Wang, Haixun Wang, Zheng Chen.
IEEE International Conference of Data Mining (ICDM), 2009 Best Student Paper Award Runner-Up
P-packSVM: Parallel Primal Gradient Descent Kernel SVM
Zeyuan Allen Zhu, Weizhu Chen, Gang Wang, Chenguang Zhu, Zheng Chen.
IEEE International Conference of Data Mining (ICDM), 2009
Using machine comprehension to answer a question (US 20190156220)
Chenguang Zhu, Hsin-Yuan Huang, Pengcheng He, Weizhu Chen, Yelong Shen, Zheng Chen.
Conversational Virtual Assistant (US 20180232376)
Chenguang Zhu, Weizhu Chen, Jianwen Zhang, Xuedong Huang, Zheng Chen.
Caching Content Addressable Data Chunks for Storage Virtualization (US 20140280664)
Sudipta Sengupta, Chenguang Zhu, Chun Ho Cheung, Jin Li, Abhishek Gupta.
I am very fortunate to have mentored and worked with talented interns.
Donghan Yu (2020 summer), Carnegie Mellon University.
Yu-An Chung (2020 summer), MIT.
Yumo Xu (2020 spring), University of Edinburgh.
Ziyi Yang (2018 summer and 2019 summer), Stanford University. Our paper on word embedding was published in ACL 2019. Our paper on sentence embeddings was published in EMNLP 2019. Our paper on unsupervised text summarization was published in EMNLP 2020. Our paper on zero-shot news summarization was published in NeurIPS 2020 Self-Supervised Learning Workshop. Our paper on multilingual embedding alignment was published in ICLR 2021.
Beliz Gunel (2019 summer), Stanford University. Our paper on knowledge-boosted text summarization was published in NeurIPS 2019 workshop of KR2ML.
Jianmo Ni (2018 summer), UC San Diego. Our paper on machine reading comprehension was published in NAACL 2019.
Hsin-Yuan Huang (2017 summer), Caltech. Our paper on machine reading comprehension was published on ICLR 2018.
Program committee member of EMNLP 2019, ACL 2019, NeurIPS 2019.
Program committee member of ACL 2018 Machine Reading and Question Answering workshop (MRQA).
Knowledge Graph and Its Applications in NLP. Seminar at Department of Computer Science and Engineering, University of Notre Dame, 2020.09 [Link]
Machine Reading Comprehension
Research Progress in Task-Oriented Dialogue. First Open Virtual Assistant Workshop, Stanford University, 2019.10 [Video]
SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering. Stanford NLP Seminar, Stanford University, 2019.01
FusionNet: Fusing with Fully Aware Attention in Machine Reading Comprehension
Stanford Platform Lab Seminar, Stanford University, 2018.02
Guest lecture at EE392K, Stanford University, 2018.02
Reducing Inefficiencies in Taxi Systems. Presented at IEEE CDC 2017, Melbourne, Australia, 2017.12
Analysis and Modeling of Large-scale Transportation Systems
Guest lecture at EE392K, Stanford University, 2016.02
Presented at Google Research, Mountain View, CA, USA, 2016.02
Presented at Microsoft Research, Redmond, WA, USA, 2016.02
Polling One’s Friends: A Graph Theoretic View. Presented at Allerton 2015, Monticello, Illinois, USA, 2015.09
Reducing Road Congestion Through Incentives: A Case Study. Presented at TRB 2015, Washington DC, USA, 2015.01
A General Magnitude-Preserving Boosting Algorithm for Search Ranking. Presented at ACM CIKM 2009, Hong Kong, China, 2009.11
ACM International Collegiate Programming Contest (ICPC), World Finals 2012: 13th place (Representing Stanford University)
Winner of Stanford Local Programming Contest, 2010, 2011
Best Student Paper Award Runner-Up at IEEE International Conference of Data Mining (ICDM), 2009
Yao Award (named after the Turing Award Laureate Andrew Yao), Tsinghua University
Scholarship for excellent academic performance, Tsinghua University (awarded to top 2% students)
National champion in US National Table Tennis Championships U2000 Division D, Dec. 2015
Second Runner-up in men's singles table tennis match of Tsinghua University