Jianguo Zhang 张建国

Ph.D in Computer Science

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

Email: jianguozhang@salesforce.com (Note: jzhan51@uic.edu is deactivated by UIC)

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 current research mainly forcuses on Conversational AI and AI Agent. Specifically,

AI agents, e.g., AI agent design, advanced data collection and language model training.

Natural language understanding, e.g., few-shot natural language understanding/classification/generation

End-to-end dialogue system, e.g., accurate dialogue state tracking and dialogue systems without complicated pipelines

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!

Open Sources

DialogStudio | MultiWOZ | NaturalCC

Publications

DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendation
Yu Wang, Zhiwei Liu, Jianguo Zhang, Weiran Yao, Shelby Heinecke, Philip S. Yu
[ArXiv Paper]
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit
Yao Wan, Yang He, Zhangqian Bi, Jianguo Zhang, Hongyu Zhang, Yulei Sui, Guandong Xu, Hai Jin, Philip S. Yu.
[ArXiv Paper] / [Sources]
BOLAA: Benchmarking and orchestrating LLM-augmented autonomous agents
Zhiwei Liu, Weiran Yao, Jianguo Zhang, Le Xue, Shelby Heinecke, Rithesh Murthy, Yihao Feng, Zeyuan Chen, Juan Carlos Niebles, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese
[ArXiv Paper] / [GitHub]
DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI
      Jianguo Zhang*, Kun Qian*, Zhiwei Liu, Shelby Heinecke, Rui Meng, Ye Liu, Zhou Yu, Silvio Savarese, Caiming Xiong
      In Proceedings of EACL 2024 Findings
      [Paper] / [GitHub] / [HuggingFace]
Retroformer: Retrospective large language agents with policy gradient optimization
      Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Murthy, Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese
      In Proceedings of ICLR 2024(Spotlight)
      [Paper] / [GitHub]
Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System
      Jianguo Zhang, Stephen Roller, Kun Qian, Zhiwei Liu, Rui Meng, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong
      In Proceedings of SIGDIAL 2023
      [Paper]
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-Oriented Dialogue Systems
      Yihao Feng, Shentao Yang, Shujian Zhang, Jianguo Zhang, Caiming Xiong, Mingyuan Zhou, Huan Wang
      In Proceedings of ICLR 2023
      [Paper]
Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training
      Ziwei Fan, Zhiwei Liu, Shelby Heinecke, Jianguo Zhang, Huan Wang, Caiming Xiong, Philip S Yu
      In Proceedings of CIKM 2023
      [Paper]
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]
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 (Oral)
      [Paper]
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 (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 (Oral)
      [Paper]
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
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 (* indicates equal contribution)
      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: ACL Rolling Review 2021-pres, EMNLP 2021-Pres, NeurIPS 2023, EACL 2023, ACL 2021/2022, NAACL 2021, IEEE/ACM TASLP 2020-Pres, and others.

Session Chair: COLING 2020 (industry track: Dialogue).

Senior Program Committee: CIKM 2023.