Canyu Chen

Hi, this is Canyu Chen (陈灿宇). I am a Computer Science Ph.D. student at Northwestern University and a member of the Northwestern MLL Lab, fortunately advised by Prof. Manling Li. I was a graduate visiting researcher at University of California, Berkeley, hosted by Prof. Dawn Song. I received my B.S. from the University of Chinese Academy of Sciences. I have the privilege of collaborating closely with Prof. Dawn Song, Prof. James Evans, and Prof. Philip Torr. I am grateful for the previous mentorship from Prof. Kai Shu. I am a recipient of the prestigious Bloomberg Data Science Ph.D. Fellowship.

My research interest covers Foundation Agent, Trustworthiness, and Multimodality. FedAgent enables agent learning without sacrifacing user data privacy (first author, Best Paper Award at the AAAI'26 TrustAgent Workshop, Outstanding Paper Award in the AAAI'26 PerFM Workshop). AgentTrust demonstrates the feasbility to simulate human trust behavior with LLM agents (co-first author, Outstanding Paper Award in the CIKM'25 LASS Workshop). LLMFake shows that LLM-generated misinformation can be more deceptive than human-written misinformation (first author, Didactic Paper Award in NeurIPS'23 ICBINB Workshop). I aim to pursue Safe and Aligned Artificial General Intelligence in the long run. I am one organizer of the ResponsibleFM community (Join ResponsibleFM Community on Slack!), dedicated to advancing socially responsible and trustworthy foundation models (language and multimodal). I have started and led the LLMs Meet Misinformation initiative, aiming to combat misinformation in the age of LLMs. I am always happy to chat and discuss potential collaborations, or give talks about my research in related seminars. Feel free to contact me via wechat ID : alexccychen or email canyuchen AT u.northwestern.edu

Incoming Workshops & Tutorials

News

Publications (show selected / show by date)

(* indicates equal contributions)

2026

• 

  Federated Agent Reinforcement Learning
  Canyu Chen*, Kangyu Zhu*, Zhaorun Chen, Zhanhui Zhou, Shizhe Diao, Yiping Lu, Tian Li, Manling Li, Dawn Song
  TrustAgent@AAAI 2026, Oral · PerFM@AAAI 2026, Oral
  [PDF]
  Award: Best Paper Award in the AAAI 2026 Workshop on Trust and Control in Agentic AI
  Award: Outstanding Paper Award in the AAAI 2026 Workshop on Personalization in the Era of Large Foundation Models

• 

  Can Editing LLMs Inject Harm?
  Canyu Chen*, Baixiang Huang*, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu
  AAAI 2026 · TiFA@ICML 2024, Lightning Talk
  [arXiv] [project website] [poster] [Code, Results, and Dataset] [YouTube]
  Included in Tutorial : [Knowledge Editing for Large Language Models@IJCAI 2024]

• 

  Artificial Entanglement in the Fine-Tuning of Large Language Models
  Min Chen, Zihan Wang, Canyu Chen, Zeguan Wu, Manling Li, Junyu Liu
  [arxiv]

2025

• Reflection on Knowledge Editing: Charting the Next Steps
  Yunzhi Yao, Canyu Chen, Jia-Chen Gu, Shumin Deng, Manling Li, Nanyun Peng
  [blog]

• 

  Can Knowledge Editing Really Correct Hallucinations?
  Baixiang Huang*, Canyu Chen*, Xiongxiao Xu, Ali Payani, Kai Shu
  ICLR 2025 · Safe Generative AI@NeurIPS 2024
  [arXiv] [project website] [Code and results on GitHub]
  Award: Top #2 Paper of the day at HuggingFace AK Daily Papers (Oct.25, 2024).

• MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
  Zhaorun Chen, Yichao Du, Zichen Wen, Yiyang Zhou, Chenhang Cui, Zhenzhen Weng, Haoqin Tu, Chaoqi Wang, Zhengwei Tong, Qinglan Huang, Canyu Chen, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, Huaxiu Yao
  NeurIPS 2025, Datasets and Benchmarks Track · FM-Wild@ICML 2024
  [arXiv] [project website] [Code] [Models, Datasets, and Leaderboard on huggingface]
  Award: Top #1 Paper of the day at HuggingFace AK Daily Papers (Jul.9, 2024).

• From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge
  Dawei Li, Bohan Jiang, Liangjie Huang, Alimohammad Beigi, Chengshuai Zhao, Zhen Tan, Amrita Bhattacharjee, Yuxuan Jiang, Canyu Chen, Tianhao Wu, Kai Shu, Lu Cheng, Huan Liu
  EMNLP 2025
  [arXiv] [project website] [Paper List on GitHub]
  Award: Top #3 Paper of the day at HuggingFace AK Daily Papers (Nov.26, 2024).
  Media Coverage : [机器之心]

• Explainable differential diagnosis with dual-inference large language models
  Shuang Zhou, Mingquan Lin, Sirui Ding, Jiashuo Wang, Canyu Chen, Genevieve B Melton, James Zou, Rui Zhang
  npj Health Systems, 2025
  [publication]

• SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?
  Yucheng Shi, Tianze Yang, Canyu Chen, Quanzheng Li, Tianming Liu, Xiang Li, Ninghao Liu
  BIBM 2025
  [arXiv]

• Evaluating the Social Impact of Generative AI Systems
  Irene Solaiman, Zeerak Talat, William Agnew, Lama Ahmad, Dylan Baker, Su Lin Blodgett, Canyu Chen, Hal Daumé III, Jesse Dodge, Isabella Duan, Ellie Evans, Felix Friedrich, Avijit Ghosh, Usman Gohar, Sara Hooker, Yacine Jernite, Ria Kalluri, Alberto Lusoli, Alina Leidinger, Michelle Lin, Xiuzhu Lin, Sasha Luccioni, Jennifer Mickel, Margaret Mitchell, Jessica Newman, Anaelia Ovalle, Marie-Therese Png, Shubham Singh, Andrew Strait, Lukas Struppek, Arjun Subramonian
  Oxford Handbook on the Foundations and Regulation of Generative AI, 2025
  [Publication] [researchgate]

• AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
  MLCommons AI Safety Working Group
  arXiv preprint. Feb. 2025.
  [arXiv] [official blog]
  Media Coverage : [IEEE Spectrum] [The Register] [Yahoo Finance] [Business Wire] [SiliconANGLE] [SDxCentral] [Hackster.io] [HPCwire] [AIwire] [KMWorld]

• SST: Multi-Scale Hybrid Mamba-Transformer Experts for Long-Short Range Time Series Forecasting
  Xiongxiao Xu, Canyu Chen, Yueqing Liang, Baixiang Huang, Guangji Bai, Liang Zhao, Kai Shu.
  CIKM 2025
  [arXiv]

2024

• 

  ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?
  Canyu Chen*, Jian Yu*, Shan Chen, Che Liu, Zhongwei Wan, Danielle S. Bitterman, Fei Wang, Kai Shu
  AMIA NLP 2024, Oral · GenAI4Health@NeurIPS 2024
  [arxiv] [project website] [Code and results on GitHub]

• 

  Can Large Language Model Agents Simulate Human Trust Behavior?
  Chengxing Xie*, Canyu Chen*, Feiran Jia, Ziyu Ye, Shiyang Lai, Kai Shu, Jindong Gu, Adel Bibi, Ziniu Hu, David Jurgens, James Evans, Philip Torr, Bernard Ghanem, Guohao Li.
  NeurIPS 2024 · LASS@CIKM 2025, Oral · MSLD 2024, Oral · AIBS@KDD 2024, Oral
  [arXiv] [project website] [slides] [code and results]
  Demos on HuggingFace: [Trust Game Demo] [Repeated Trust Game Demo]
  Award: Outstanding Paper Award in the 1st Workshop on LLM Agents for Social Simulation at CIKM 2025
  Award: Featured Research at The Agentic AI Summit 2025, hosted by The Berkeley Center for Responsible, Decentralized Intelligence (Berkeley RDI)
  Media Coverage : [机器之心]
  Invited Talks : [Swarma Club] [Knowledge Lab in the University of Chicago] [Guest Lecture for ARTG 6460: Human-Centered AI@Northeastern University] [The Agentic AI Summit 2025 Lightning Talk] [Patronus AI]

• 

  Combating Misinformation in the Age of LLMs: Opportunities and Challenges
  Canyu Chen, Kai Shu.
  AI Magazine 2024, Highlight Article
  [publication] [arXiv] [project website] [Slides] [paper list] [YouTube]
  Award: Research Spotlight in The 2024 Summit on Responsible Decentralized Intelligence —— Future of Decentralization and AI, hosted by The Berkeley Center for Responsible, Decentralized Intelligence (Berkeley RDI)
  Media Coverage : [Marktechpost AI Research News] [Reddit r/machinelearningnews] [Analytics Vidhya Blog].
  Invited Talks : [Berkeley Decentralization & AI Summit Research Spotlight Talk] [Psych Methods] [KAIST/IBS Data Science Group] [Guest Lecture for CSCI 8265: Trustworthy Machine Learning@UGA] [Zhejiang University] [TechBeat] [Guest Lecture for CSCI 8000 Advanced Special Topics in Computer Science@UGA] [Guest Lecture for CSDS 600 Introduction to Artificial Intelligence@CWRU] [Guest Lecture for CS 585 Natural Language Processing@Illinois Tech] [University of Massachusetts Amherst BioNLP Lab] [Guest Lecture for CS 517 Socially Responsible AI@UIC].
  

• 

  Can LLM-Generated Misinformation Be Detected?
  Canyu Chen, Kai Shu.
  ICLR 2024 · RegML@NeurIPS 2023, Oral · ICBINB@NeurIPS 2023, Spotlight · AGI Leap Summit 2024, Spotlight Talk
  [publication] [arXiv] [project website] [dataset and code] [Slides] [YouTube] [zhihu] [twitter/x.com] [LinkedIn]
  Award: Didactic Paper Award in the workshop ICBINB@NeurIPS 2023 (1/35 of all accepted papers).
  Award: Spotlight Research in AGI Leap Summit 2024.
  Award: Third Place Award in the Illinois Tech College of Computing Poster Session 2024 (Ph.D. Group).
  Included in the curriculum: [CS120: Introduction to AI Safety@Stanford] [DATA 78000: Large Language Models and Chat GPT@The City University of New York].
  Included in Tutorial: [Defending Against Generative AI Threats in NLP@SBP-BRiMS 2024]. [Preventing and Detecting Misinformation Generated by Large Language Models@SIGIR 2024].
  Media Coverage : [The Register] [LLM Security] [Blog 1] [Blog 2].
  Invited Talks : [AGI Leap Summit Spotlight Research Talk] [Tsinghua AI Time].

• Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges
  Baixiang Huang, Canyu Chen, Kai Shu.
  SIGKDD Explorations 2024
  [arXiv] [project website] [Paper list on GitHub]

• Can Large Language Models Identify Authorship?
  Baixiang Huang, Canyu Chen, Kai Shu.
  EMNLP 2024, Findings
  [arXiv] [project website] [code]

• MetaGAD: Learning to Meta Transfer for Few-shot Graph Anomaly Detection.
  Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu.
  DSAA 2024
  [arXiv]

• Model Attribution in Machine-Generated Disinformation: A Domain Generalization Approach with Supervised Contrastive Learning
  Alimohammad Beigi, Zhen Tan, Nivedh Mudiam, Canyu Chen, Kai Shu, Huan Liu.
  DSAA 2024
  [arXiv]

• FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks
  Peiran Wu, Che Liu, Canyu Chen, Jun Li, Cosmin I. Bercea, Rossella Arcucci
  arXiv preprint. Oct. 2024.
  [arXiv]

• FairMindSim: Alignment of Behavior, Emotion, and Belief in Humans and LLM Agents Amid Ethical Dilemmas
  Yu Lei, Hao Liu, Chengxing Xie, Songjia Liu, Zhiyu Yin, Canyu Chen, Guohao Li, Philip Torr, Zhen Wu
  arXiv preprint. Oct. 2024.
  [arXiv] [code]

• Introducing v0.5 of the AI Safety Benchmark from MLCommons
  MLCommons AI Safety Working Group
  arXiv preprint. Apr. 2024.
  [arXiv] [official blog]
  Media Coverage : [IEEE Spectrum] [AK Daily Papers] [Marktechpost] [AI Business] [EnterpriseAI News] [HPCwire] [Hackster.io] [ELBLOG.PL] [SiliconANGLE] [GoatStack.ai].

2023

• Learners. teaser">

  PromptDA: Label-guided Data Augmentation for Prompt-based Few-shot Learners.
  Canyu Chen, Kai Shu.
  EACL 2023 · ENLSP@NeurIPS 2022, Oral (Spotlight)
  [arXiv] [code] [youtube] [bilibili] [slides] [poster]

• Approach. teaser">

  Fair Classification via Domain Adaptation: A Dual Adversarial Learning Approach.
  Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu.
  Frontiers in Big Data, 2023
  [publication] [arXiv]

• Attacking Fake News Detectors via Manipulating News Social Engagement.
  Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu.
  WWW 2023
  [arXiv] [code]
  Media Coverage : [Montreal AI Ethics Institute].

2022

• Intervention, and Open Issues. teaser">

  Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issues.
  Canyu Chen*, Haoran Wang*, Matthew Shapiro, Yunyu Xiao, Fei Wang, Kai Shu.
  arXiv preprint. Nov. 2022.
  [arXiv]

• Attributes. teaser">

  When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes.
  Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Ashish Kundu, Ali Payani, Yuan Hong, Kai Shu.
  TSRML@NeurIPS 2022 · AFCP@NeurIPS 2022
  [arXiv] [Video] [Slides] [Poster]
  Media Coverage : [Illinois Tech News].
  

• Artificial Intelligence Algorithms for Treatment of Diabetes.
  Mudassir M. Rashid, Mohammad Reza Askari, Canyu Chen, Yueqing Liang, Kai Shu, Ali Cinar.
  Algorithms 2022
  [Paper]

• Graphs. teaser">

  BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
  Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu.
  NeurIPS 2022, Datasets and Benchmarks Track
  [arXiv] [code]

Invited Talks

• "Can AI Agents Simulate Human Behavior?" [Slides]
  • Patronus AI: invited talk, 08/2025.
  • The Agentic AI Summit 2025, hosted by The Berkeley Center for Responsible, Decentralized Intelligence (Berkeley RDI): Lightning Talk, 08/2025.
  • Northeastern University: Guest lecture for the course ARTG 6460: Human-Centered AI invited by Prof. Dakuo Wang, 03/2025.
  • The University of Chicago, Knowledge Lab: Invited talk by Prof. James Evans, 11/2024.
  • Swarma Club: invited talk by Prof. Yuxuan Liang, 06/2024.
• "Combating Misinformation in the Age of LLMs" [Slides]
  • University of Illinois Chicago (UIC): Guest lecture for the course "CS 517 Socially Responsible AI" invited by Prof. Lu Cheng, 05/2025.
  • University of Massachusetts Amherst BioNLP Lab: invited talk by Prof. Hong Yu, 01/2025.
  • Illinois Institute of Technology: Guest lecture for the course "CS 585 Natural Language Processing" instructed by Prof. Jacek Dzikowski, 11/2024.
  • Case Western Reserve University: Guest lecture for the course "CSDS 600 Introduction to Artificial Intelligence" invited by Prof. Xiaotian (Max) Han, 11/2024.
  • University of Georgia: Guest lecture for the course "CSCI 8000 Advanced Special Topics in Computer Science" invited by Prof. Zhen Xiang, 11/2024.
  • Zhejiang University: invited talk by Prof. Tianhang Zheng, [Poster], 10/2024.
  • University of Georgia: Guest lecture invited by Prof. Ninghao Liu for the course CSCI 8265: Trustworthy Machine Learning (2024 fall), 10/2024.
  • The 2024 Summit on Responsible Decentralized Intelligence — Future of Decentralization and AI, hosted by The Berkeley Center for Responsible, Decentralized Intelligence (Berkeley RDI): Research Spotlight talk, [YouTube], 08/2024.
  • KAIST/IBS Data Science Group: invited talk by Wenchao Dong.
• "Towards Trustworthy Large Language Models" [Slides]
  • Illinois Institute of Technology: Guest lecture for the course "CS 585 Natural Language Processing" instructed by Prof. Jacek Dzikowski, 04/2025.
• "Can LLM-Generated Misinformation Be Detected?" [Slides] [YouTube]
  • AGI Leap Summit 2024: Spotlight Research talk, 02/2024.
  • Tsinghua University AI Time: invited talk, [Gongzhonghao], 02/2024.
• "Fairness in AI: An Introduction" [Slides]
  • University of Illinois Chicago (UIC):Guest lecture invited by Prof. Lu Cheng for CS 483 Big Data Mining (2023 Spring), 04/2023. [04/18/2023] at UIC

Awards and Fellowship

• Bloomberg Data Science Ph.D. Fellowship, 2026-2027
• Outstanding Paper Award in the AAAI 2026 Workshop on Personalization in the Era of Large Foundation Models for the first-authored paper Federated Agent Reinforcement Learning [PDF].
• Best Paper Award in the AAAI 2026 Workshop on Trust and Control in Agentic AI for the first-authored paper Federated Agent Reinforcement Learning [PDF].
• Tinker Research Grant ($5000) from Thinking Machines Lab, 2026.
• Outstanding Paper Award in the 1st Workshop on LLM Agents for Social Simulation at CIKM 2025 for the co-first-authored paper Can Large Language Model Agents Simulate Human Trust Behavior? [arXiv] [project website].
• Northwestern Conference Travel Grant ($600)
• McCormick School of Engineering Fellowship by Northwestern University, 2025.
• Patronus AI Ph.D. Research Fellowship by Patronus AI, 2025.
• Featured Research at The Agentic AI Summit 2025, hosted by The Berkeley Center for Responsible, Decentralized Intelligence (Berkeley RDI).
• Outstanding reviewer at KDD 2025 (Aug Cycle & Feb Cycle, a recognition for the top 10% of reviewers).
• Outstanding reviewer at EMNLP 2024.
• Highlight Article in AI Magazine (Volume 45, Issue 3, Fall 2024) .
• Research Spotlight in The 2024 Summit on Responsible Decentralized Intelligence —— Future of Decentralization and AI, hosted by The Berkeley Center for Responsible, Decentralized Intelligence (Berkeley RDI)
• Great Review at ACL Rolling Review 2024 April
• Travel Award for Seventeenth Midwest Speech and Language Days (MSLD 2024)
• Sigma Xi Student Research Award 2024 from Illinois Tech and the local Sigma Xi chapter. ( An award of $500 is given each year to up to two graduate students at Illinois Tech who have demonstrated significant promise in research and scholarship through their accomplishments. There is only one awardee across the whole university in 2024. )
• Harvard Technical AI Safety Fellowship 2024 Spring.
• Third Place Award in the Illinois Tech College of Computing Poster Session 2024 (Ph.D. Group).
• Spotlight Research in the symposium AGI Leap Summit 2024.
• Didactic Paper Award (1/35 of all accepted papers) in the workshop in workshop ICBINB@NeurIPS 2023 for the first-authored paper Can LLM-Generated Misinformation Be Detected? [arXiv] [project website]. The Didactic Award is awarded to the most well-explained and pedagogical paper in ICBINB workshop at NeurIPS 2023.
• NeurIPS 2023 Volunteer Award.

Media Coverage

• Northwestern Computer Science Department News: "Multi-Institution Team Wins Two Awards at AAAI-26 Workshops".
• Illinois Tech Today: "Recognizing the Outstanding Work of Our Illinois Tech Faculty"
• Marktechpost AI Research News: "This AI Report from the Illinois Institute of Technology Presents Opportunities and Challenges of Combating Misinformation with LLMs"
• The Register: "It's true, LLMs are better than people – at creating convincing misinformation"
• Illinois Tech News: "Breaking Biases"
• Montreal AI Ethics Institute: "Attacking Fake News Detectors via Manipulating News Social Engagement"
• IEEE Spectrum: "Announcing a Benchmark to Improve AI Safety: MLCommons has made benchmarks for AI performance—now it's time to measure safety"
• 机器之心: "NeurIPS 2024 | LLM智能体真能模拟人类行为吗？答案有了"
• 机器之心: "关于LLM-as-a-judge范式，终于有综述讲明白了"
• TechBeat: "大模型时代的虚假信息危机：挑战和机遇"

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