Zhuosheng Zhang

Tenure-Track Assistant Professor
School of Electronic Information and Electrical Engineering
Shanghai Jiao Tong University
Email: zhangzs@sjtu.edu.cn
Office: School of Software 5213
800 Dongchuan Road, Shanghai


I am a tenure-track assistant professor at Shanghai Jiao Tong University. I received my Ph.D. degree and my M.S. degree from Shanghai Jiao Tong University in 2023 and 2020. I was an intern at Amazon Web Services, Microsoft Research Redmond, Langboat Tech, NICT (Japan), and IBM. I have served as a PC member for ARR, ICML, NeurIPS, ICLR, ACL, AAAI, etc. I also served as an action editor or area chair for ACL Rolling Review, LREC-COLING 2024, and ICLR 2023 TinyPapers.

My primary research interests include natural language processing, large language models, and autonomous agents. I have published over 60 papers in top-tier conferences and journals, including TPAMI, ICLR, ACL, AAAI, EMNLP, TNNLS, TASLP, and COLING. I have won 1st place in various language understanding and reasoning leaderboards, such as SQuAD2.0, MuTual, RACE, ShARC, and CMRC. I was awarded as an Academic Star at Shanghai Jiao Tong University and was selected as one of the Global Top 100 Chinese Rising Stars in Artificial Intelligence. I won the Excellent Doctoral Thesis of Chinese Information Processing Society (CIPS), WAIC 2024 Youth Outstanding Paper Award, WAIC 2024 YunFan Award: Bright Star, and Baidu Scholarship.

Prospective Students: If you're a Ph.D/master/bachelor student and interested in working with me, feel free to send me an email -- including your CV, transcript and/or samples of your work.


  • CVPR 2024: From Multimodal LLM to Human-level AI: Modality, Instruction, Reasoning and Beyond
    Hao Fei, Yuan Yao, Ao Zhang, Haotian Liu, Fuxiao Liu, Zhuosheng Zhang, Shuicheng Yan.
    Seattle WA, USA
  • LREC-COLING 2024: From Multimodal LLM to Human-level AI: Modality, Instruction, Reasoning, Efficiency and Beyond
    Hao Fei, Yuan Yao, Zhuosheng Zhang, Fuxiao Liu, Ao Zhang, Tat-Seng Chua.
    Torino, Italia
  • IJCNLP-AACL 2023: Learning WHO Saying WHAT to WHOM in Multi-Party Conversations
    Jia-Chen Gu, Zhuosheng Zhang, and Zhen-Hua Ling.
    Bali, Indonesia.
  • IJCAI 2021: Machine Reading Comprehension: The Role of Contextualized Language Models and Beyond
    Zhuosheng Zhang and Hai Zhao.
    Montreal, Canada (Virtual)
  • For Beginners: Dive into LLMs《动手学大模型》系列编程实践教程


  • 2024/06: Talk "LLM Agents Safety" at YSSNLP 2024. [slides]
  • 2023/11: Keynote "Autonomous Language Agents" at CJNLP 2023.
  • 2023/09: Talk "Autonomous Language Agents" at MNNLP 2023. [slides]
  • 2023/03: Talk "Chain-of-Thought Reasoning In Language Models" at WestlakeNLP, FudanNLP, and Bytedance. [slides]
  • 2022/12: Talk "Automatic Chain of Thought Prompting in Large Language Models" at Amazon AWS. [slides]
  • 2022/07: Talk "Large-scale Multi-task Pre-training" at Tencent AI Lab. [slides]
  • 2022/06: Talk "Large-scale Multi-task Pre-training" at Microsoft Research. [slides]
  • 2021/11: Talk "Mengzi Lightweight Pre-trained Models" at Big Model Meetup, with Dr. Ming Zhou. [slides]
  • 2021/11: Talk "Machine Reading Comprehension: The Paradigm of Pre-trained Models" at MLNLP 2021. [slides]
  • 2021/07: Talk "Machine Reading Comprehension and Dialogue Systems" at Huawei Shanghai Institute. [slides]
  • 2020/10: Talk "My Way to Reading Comprehension: Self-cognition and Persistence" at CCL 2020 Student Workshop. [slides]
  • 2020/05: Talk "Machine Reading Comprehension: The Role of Contextualized Language Models and Beyond" at UofA NLP seminar on MRC. [slides]
  • 2017/10: Talk "Fine-grained Embedding for Reading Comprehension" at CMRC 2017 workshop in CCL 2017. [slides]

Recent Publications [Show All]

Discover google scholar | semantic scholar | dblp.
  • R-Judge: Benchmarking Safety Risk Awareness for LLM Agents
    Tongxin Yuan#, Zhiwei He#, Lingzhong Dong, Yiming Wang, Ruijie Zhao, Tian Xia, Lizhen Xu, Binglin Zhou, Fangqi Li, Zhuosheng Zhang*, Rui Wang, Gongshen Liu.
    arXiv, 2024
    "Are LLM agents aware of safety risks in real-world applications? Let's find out with R-Judge!"
    [PDF] [Abstract] [Bib]
  • Trajectory Volatility for Out-of-Distribution Detection in Mathematical Reasoning
    Yiming Wang, Pei Zhang, Baosong Yang, Derek F. Wong, Zhuosheng Zhang, Rui Wang.
    arXiv, 2024
    [PDF] [Abstract] [Bib]
  • Is it Possible to Edit Large Language Models Robustly?
    Xinbei Ma, Tianjie Ju, Jiyang Qiu, Zhuosheng Zhang, Hai Zhao, Lifeng Liu, Yulong Wang.
    arXiv, 2024
    "The robustness of model editing remains an open question."
    [PDF] [Abstract] [Bib]
  • Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science
    Xiangru Tang, Qiao Jin, Kunlun Zhu, Tongxin Yuan, Yichi Zhang, Wangchunshu Zhou, Meng Qu, Yilun Zhao, Jian Tang, Zhuosheng Zhang, Arman Cohan, Zhiyong Lu, Mark Gerstein.
    arXiv, 2024
    [PDF] [Abstract] [Bib]
  • GLaPE: Gold Label-agnostic Prompt Evaluation and Optimization for Large Language Model
    Xuanchang Zhang, Zhuosheng Zhang, Hai Zhao.
    arXiv, 2024
    [PDF] [Abstract] [Bib]
  • Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents
    Zhuosheng Zhang#, Yao Yao#, Aston Zhang, Xiangru Tang, Xinbei Ma, Zhiwei He, Yiming Wang, Mark Gerstein, Rui Wang, Gongshen Liu, Hai Zhao.
    arXiv, 2023
    "Join us on an exciting journey from chain-of-thought reasoning to language agent!"
    [PDF] [Abstract] [Bib]
  • Multimodal Chain-of-Thought Reasoning in Language Models
    Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola.
    TMLR, 2024
    "Imagine learning a textbook with no figures: Multimodal-CoT surpasses humans on ScienceQA."
    Featured in Dive into Deep Learning (Adopted at 500 universities from 70 countries)
    [Top Trending Research on paperswithcode] [Idea Inspiration] [PDF] [Abstract] [Bib]
  • Investigating Multi-Hop Factual Shortcuts in Knowledge Editing of Large Language Models
    Tianjie Ju, Yijin Chen, Xinwei Yuan, Zhuosheng Zhang*, Wei Du, Yubin Zheng, Gongshen Liu*.
    ACL, 2024
    [PDF] [Abstract] [Bib]
  • Acquiring Clean Language Models from Backdoor Poisoned Datasets by Downscaling Frequency Space
    Zongru Wu, Zhuosheng Zhang*, Pengzhou Cheng, Gongshen Liu*.
    ACL, 2024
    [PDF] [Abstract] [Bib]
  • On the Cross-lingual Consistency of Text Watermark for Large Language Models
    Zhiwei He, Binglin Zhou, Hongkun Hao, Aiwei Liu, Xing Wang, Zhaopeng Tu, Zhuosheng Zhang, Rui Wang.
    ACL, 2024
    [PDF] [Abstract] [Bib]
  • You Only Look at Screens: Multimodal Chain-of-Action Agents
    Zhuosheng Zhang, Aston Zhang.
    ACL-Findings, 2024
    "Perform a task on smart phones? Train an agent using screenshots."
    [PDF] [Abstract] [Bib] [slides]
  • Measuring Bargaining Abilities of LLMs: A Benchmark and A Buyer-Enhancement Method
    Tian Xia, Zhiwei He, Tong Ren, Yibo Miao, Zhuosheng Zhang, Yang Yang, Rui Wang.
    ACL-Findings, 2024
    [PDF] [Abstract] [Bib]
  • Comprehensive Cognitive LLM Agent for Smartphone GUI Automation
    Xinbei Ma, Zhuosheng Zhang*, Hai Zhao*.
    ACL-Findings, 2024
    [PDF] [Abstract] [Bib]
  • Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models
    Yiming Wang, Zhuosheng Zhang, Rui Wang.
    ACL-Findings, 2024
    [PDF] [Abstract] [Bib]
  • MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning
    Xiangru Tang#, Anni Zou#, Zhuosheng Zhang, Yilun Zhao, Xingyao Zhang, Arman Cohan, Mark Gerstein.
    ACL-Findings, 2024
    [PDF] [Abstract] [Bib]
  • Structured Chemistry Reasoning with Large Language Models
    Siru Ouyang, Zhuosheng Zhang, Bing Yan, Xuan Liu, Jiawei Han, Lianhui Qin.
    ICML, 2024
    [PDF] [Abstract] [Bib]
  • Self-Prompting Large Language Models for Open-Domain QA
    Junlong Li, Jinyuan Wang, Zhuosheng Zhang*, Hai Zhao*.
    NAACL, 2024
    "Free from training data and external knowledge corpus for ODQA."
    [PDF] [Abstract] [Bib]
  • Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model
    Zhiwei He, Xing Wang, Wenxiang Jiao, Zhuosheng Zhang, Rui Wang, Shuming Shi, Zhaopeng Tu.
    NAACL, 2024
    [PDF] [Abstract] [Bib]
  • Mitigating Harmful Chain-of-Thought Reasoning with Selective Filtering
    Yexin Wu, Zhuosheng Zhang*, Hai Zhao*.
    LREC-COLING, 2024
    [PDF] [Abstract] [Bib]
  • AuRoRA: A One-for-all Platform for Augmented Reasoning and Refining with Task-Adaptive Chain-of-Thought Prompting
    Anni Zou, Zhuosheng Zhang*, Hai Zhao*.
    LREC-COLING, 2024
    [PDF] [Abstract] [Bib] [Demo]
  • Multi-turn Dialogue Comprehension from a Topic-aware Perspective
    Xinbei Ma, Yi Xu, Hai Zhao, Zhuosheng Zhang.
    Neurocomputing, 2024
    [PDF] [Abstract] [Bib]
  • Fact-driven Logical Reasoning for Machine Reading Comprehension
    Siru Ouyang, Zhuosheng Zhang*, Hai Zhao*.
    AAAI, 2024
    [PDF] [Abstract] [Bib]
  • Exploring Human-Like Translation Strategy with Large Language Models
    Zhiwei He, Tian Liang, Wenxiang Jiao, Zhuosheng Zhang, Yujiu Yang, Rui Wang, Zhaopeng Tu, Shuming Shi, Xing Wang.
    TACL, 2023
    Delves into LLMs' potential for mimicking human translation strategies.
    [PDF] [Abstract] [Bib]
  • Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
    Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, Diyi Yang
    EMNLP, 2023
    "Benchmarking ChatGPT on 20 popular NLP datasets covering 7 representative task categories."
    [PDF] [Abstract] [Bib]
  • Learning Better Masking for Better Language Model Pre-training
    Dongjie Yang, Zhuosheng Zhang*, Hai Zhao*.
    ACL, 2023
    [PDF] [Abstract] [Bib]
  • On Element-aware Automatic Summarization: Expert-writing Test Set and Chain-of-Thought Method
    Yiming Wang, Zhuosheng Zhang, Rui Wang.
    ACL, 2023
    "You really need higher-quality reference summaries to evaluate LLMs!"
    [PDF] [Abstract] [Bib]
  • Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification
    Anni Zou, Zhuosheng Zhang, Hai Zhao.
    ACL-Findings, 2023
    [PDF] [Abstract] [Bib]
  • Automatic Chain of Thought Prompting in Large Language Models
    Zhuosheng Zhang, Aston Zhang, Mu Li, Alex Smola.
    ICLR, 2023
    "Let's think not just step by step, but also one by one."
    Featured in Dive into Deep Learning (Adopted at 400 universities from 60 countries)
    [PDF] [Abstract] [Bib] [bilibili] [slides]
  • Enhanced Speaker-aware Multi-party Multi-turn Dialogue Comprehension
    Xinbei Ma, Zhuosheng Zhang*, Hai Zhao*.
    TASLP, 2023
    [PDF] [Abstract] [Bib]
  • Universal Multimodal Representation for Language Understanding
    Zhuosheng Zhang#, Kehai Chen, Rui Wang#, Masao Utiyama, Eiichiro Sumita, Zuchao Li, Hai Zhao
    TPAMI, 2023
    "Let's retrieve images to overcome the lack of large-scale bilingual pairs."
    [PDF] [Abstract] [Bib]
  • Language Model Pre-training on True Negatives
    Zhuosheng Zhang, Hai Zhao, Masao Utiyama, Eiichiro Sumita
    AAAI, 2023
    [PDF] [Abstract] [Bib]

Shared Tasks

[May 2022] HellaSwag Leaderboard on Commonsense Reasoning
[January 2021] ShARC Leaderboard on Conversational Question Answering
[September 2020] MuTual Leaderboard on Dialogue Reasoning Challenge
[July 2019] SQuAD2.0 Leaderboard on Machine Reading Comprehension
  • The best models for both single and ensemble settings among all submissions (2020.01).
  • The first to surpass human benchmark on both EM and F1 scores with a single model (from 2019.07-09).
  • The first time to exceed 90% F1 score with ensemble models.
    [Leaderboard] [Paper] [Report]
[March 2019] RACE Leaderboard on Machine Reading Comprehension
[April 2019] SNLI Leaderboard on Language Inference [March 2019] GLUE Leaderboard on Language Understanding
  • The 3rd best among all submissions.
  • The best among all academic submissions.
    [Leaderboard] [Paper]
[August 2017] Chinese Machine Reading Comprehension (CCL-CMRC 2017)

Awards & Honors

  • 2024: WAIC Youth Outstanding Paper Award, World Artificial Intelligence Conference.

  • 2024: WAIC YunFan Award: Bright Star, World Artificial Intelligence Conference.

  • 2023: Excellent Doctoral Thesis of Chinese Information Processing Society (CIPS).

  • 2023: Shanghai Outstanding Doctoral Graduate.

  • 2022: Academic Stars of Graduate Students (10 recipients), Shanghai Jiao Tong University.

  • 2021: Global Top 100 Chinese Rising Stars in Artificial Intelligence (Top 10 recommended), Baidu Research.

  • 2021: Baidu Scholarship (10 recipients, worldwide), Baidu.

  • 2020: National Scholarship of China, Ministry of Education of the P.R. China.

  • 2019: Yang Yuanqing Education Fund, The foundation of Class 1988 in CS @ Shanghai Jiao Tong University.

  • 2018: Academic Stars of Graduate Students (The only master student awardee), Shanghai Jiao Tong University.

  • 2016: National Figures Nomination of College Students (20 total recipients), Ministry of Education of the P.R. China.

  • 2015: CCF Elite Collegiate Award, China Computer Federation.


  • NIS8021: Frontier Technology in Natural Language Processing
    Graduate, Shanghai Jiao Tong University, Fall 2024.
  • NIS3353: Artificial Intelligence Security
    Undergraduate, Shanghai Jiao Tong University, Spring 2024.

Academic Service

  • Organization:
    • Session Chair at IJCNLP-AACL 2023.
    • Co-chair of CCL Student Seminar, 2022
    • President of IBM Tech Club at Wuhan University, 2014-2015.
  • Area Chair / Action Editor/ SPC:
    • ACL Rolling Review
    • LREC-COLING 2024
    • IJCAI 2024
    • ICLR 2023 TinyPapers
  • Program Committee Member:
    • ML/AI conferences: ICLR, ICML, NeurIPS, AAAI, IJCAI, etc.
    • CL/NLP conferences: ARR, ACL, EMNLP, COLING, NAACL, AACL, NLPCC, CCL, etc.

  • Journal Reviewer: Artificial Intelligence, IEEE/ACM TASLP, IEEE TNNLS, IEEE TETCI, IEEE Communications Magazine, ACM TALLIP, ACM TOIS, TMLR, Neurocomputing, Multimedia Systems, Neural Computing and Applications, Expert Systems With Applications.


  • Jul. 2022 - Aug. 2023, Amazon Web Services AI, CA, USA.
    Applied Scientist Intern (remote), advised by Dr. Aston Zhang, Mu Li, Alex Smola.
  • Feb. 2022 - June. 2022, Microsoft Cognitive Services Research Group, WA, USA.
    Research Intern (remote), advised by Dr. Shuohang Wang.
  • Mar. 2021 - Dec. 2021, Langboat Tech, Beijing, China.
    Research Intern (remote), advised by Prof. Ming Zhou.
  • Jun. 2019 - Jul. 2020, NICT, Kyoto, Japan.
    Internship Research Fellow, advised by Prof. Rui Wang, Kehai Chen, Masao Utiyama, and Eiichiro Sumita.


  • Sept. 2020 - Sept. 2023
    Ph.D., Dept. of Computer Science and Engineering, Shanghai Jiao Tong University, advised by Prof. Hai Zhao.
  • Sept. 2016 - Mar. 2020
    M.S., Dept. of Computer Science and Engineering, Shanghai Jiao Tong University, advised by Prof. Hai Zhao.
  • Sept. 2012 - Jun. 2016
    B.S., Dept. of Computer Science and Engineering, Wuhan University, advised by Prof. Haojun Ai.

Lab Members

I am always fortunate to work with these brilliant young researchers. Those are the students I am (was) collaborating with.