Jianguo Zhang 张建国

Ph.D in Computer Science

University of Illinois at Chicago (UIC),
Chicago, IL, U.S.

Email: jzhan51@uic.edu


I am a research scientist at Salesforce AI Research. I received Ph.D. in the Department of Computer Science at the University of Illinois at Chicago. During my doctoral study, I was advised by Prof. Philip S. Yu in the BDSC Lab. My previous research (before March 2019) focuses on adversarial training and its applications, and currently, I am mainly studying Conversational AI. My mission is to create accurate and smart dialog systems. My current research focuses on:
  • Natural language understanding, e.g., (few-shot) natural language understanding/classification/generation
  • Multi-domain dialog management, e.g., accurate (multimodal) dialog state tracking
  • End-to-end dialogue system, e.g., e2e (task-oriented) dialogue systems with/without complicated pipelines
  • Multi-modal dialog, e.g., multi-modal task-oriented dialog systems


  • News

  • Jan 2022: I will join Salesforce AI Research as a Research Scientist.
  • Sep 2021: Finished my internship at Facebook AI Research (FAIR). The project focuses on few-shot end-to-end task-oriented dialgue systems.
  • Aug 2021: Two paper are accepted by EMNLP 2021 main conference as short papers. One first-author work collaborates with Adobe Research and it focuses on natural language understanding.
  • June 2021: Check our new released paper and public resources for few-shot intent detection w/ and w/o out-of-scope queries.
  • May 2021: I finished my internship at Adobe Research and submitted one research paper, where I also discover PhotoShop user intents and improve intent detection performance using large-scale unlabeled PhotoShop user queries.
  • Dec 2020: Our toolkit NaturalCC has been released in GitHub, which can be accessed via the Homepage.
  • Nov 2020: We have released the paper, video for the EMNLP 2020 paper, and the corresponding code is available here!
  • Sep 2020: One first-author work collaborated with Salesforce Research is accepted by *SEM 2020 as a long paper. The work focuses on multi-domain dialog state tracking and it originally got borderline scores on ACL 2020. We have updated the paper!
  • Sep 2020: One first-author work collaborated with Salesforce Research is accepted by EMNLP 2020 main conference as a long paper. The work focuses on natural language understanding.
  • June 2020: One work collaborated with Google Research is accepted by ACL 2020 NLP4ConvAI, and the modified high-quality version of MultiWOZ 2.2 dataset with additional annotation corrections and state tracking baselines is released here!
  • Publications

    (Last Update: March 2022)
  • Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection  

          Jianguo Zhang, Kazuma Hashimoto, Yao Wan, Zhiwei Liu, Ye Liu, Caiming Xiong, Philip Yu

          In Proceedings of ACL 2022 Workshop on NLP for Conversational AI

          [Paper] [Resources]

  • NaturalCC: An Open-Source Toolkit for Code Intelligence  

          Yao Wan, Yang He, Zhangqian Bi, Jianguo Zhang, Yulei Sui, Hongyu Zhang, Kazuma Hashimoto, Hai Jin, Guandong Xu, Caiming Xiong and Philip Yu

          In Proceedings of ICSE 2022 Demo Track

          [Toolkit]

  • HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization  

          Ye Liu, Jianguo Zhang, Yao Wan, Congying Xia, Lifang He and Philip Yu

          In Proceedings of EMNLP 2021 short paper (Oral)

          [Paper]

  • Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning  

          Jianguo Zhang, Trung Bui, Seunghyun Yoon, Xiang Chen, Zhiwei Liu, Congying Xia, Quan Hung Tran, Walter Chang and Philip Yu

          In Proceedings of EMNLP 2021 short paper (Oral)

          [Paper]

  • Enriching Non-Autoregressive Transformer with Syntactic and Semantic Structures for Neural Machine Translation  

          Ye Liu, Yao Wan, Jianguo Zhang, Wenting Zhao, Philip Yu

          In Proceedings of EACL 2021

          [Paper]

  • Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference  

          Jianguo Zhang, Kazuma Hashimoto, Wenhao Liu, Chien-Sheng Wu, Yao Wan, Philip S Yu, Richard Socher, Caiming Xiong

          In Proceedings of EMNLP 2020

          [Paper] / [Slide] / [Video] / [Code]

  • Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking  

          Jianguo Zhang, Kazuma Hashimoto, Chien-Sheng Wu, Yao Wan, Philip S Yu, Richard Socher, Caiming Xiong

          In Proceedings of *SEM 2020

          [Paper] / [Slide] / [Video] (Oral)

  • MultiWOZ 2.2 : A Dialogue Dataset with Additional Annotation Corrections and State Tracking Baselines  

          Xiaoxue Zang, Abhinav Rastogi, Srinivas Sunkara, Raghav Gupta, Jianguo Zhang, Jindong Chen

          In Proceedings of ACL 2020 Workshop on NLP for Conversational AI

          [Paper] / [Dataset ][Video]

  • Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce  

          Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong, Philip S Yu

          In Proceedings of NAACL-HLT 2019

          [Paper] (Oral)

  • Product Title Refinement via Multi-Modal Generative Adversarial Learning  

          Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Ye Liu, Xiuming Pan, Yu Gong, Philip S Yu

          NeurIPS 2018 Workshop on ViGIL (A short arXiv version of the NAACL-HLT 2019 paper and no Proceedings for the Workshop)

  • Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction  

          Jianguo Zhang*, Ji Wang*, Lifang He, Zhao Li, Philip S Yu (* indicates equal contribution)

          In Proceedings of ICDM 2018

          [Paper]

  • Not just privacy: Improving performance of private deep learning in mobile cloud  

          Ji Wang*, Jianguo Zhang* , Weidong Bao, Xiaomin Zhu, Bokai Cao, Philip S Yu

          In Proceedings of KDD 2018

          [Paper]



  • Experience

    Facebook AI Research (FAIR), New York, US

           Research Intern,   June 2021 - Sep. 2021

           Mentor: Stephen Roller

    Adobe Research, San Jose, US

           Research Intern,   Mar. 2021 - May 2021

           Collaborators: Trung Bui, David Seunghyun Yoon and Walter Chang.

    Salesforce Research, Palo Alto, US

           Research Intern,   Spring 2019 - Summer 2020

           Mentors: Kazuma Hashimoto, Caiming Xiong, Chien-Sheng Wu and Richard Socher.

           (I become an NLPer from here!)

    Alibaba Group, Hangzhou, China

           Research Intern,   Summer 2018

           Mentors: Pengcheng Zou and Zhao Li.

    Service

  • Program Committee/Reviewer: NLPCC 2019/2020; EMNLP 2020/2021; COLING 2020; NAACL-HLT 2021; ACL-IJCNLP 2021/2022; ACL Rolling Review; Transactions on Audio, Speech and Language Processing.
  • Session Chair: COLING 2020 (industry track: Dialogue).


  • Misc

    I am a photographer (Keep learning), guitar lover, pet lover (My cat name is Maomao), Chinese literature (Already read and forget many books) and basketball (Go Lakers, Metamind Lebron) fan.

    This website is under construction