Chen Xu

Chen Xu (徐晨)

Postdoctoral Researcher

Language Technologies Institute (LTI)
School of Computer Science
Carnegie Mellon University
Pittsburgh, PA, USA

Email: /

I am a Postdoctoral Researcher at the Language Technologies Institute (LTI), Carnegie Mellon University, working with Prof. Chenyan Xiong. I received my Ph.D. from Renmin University of China, where I was advised by Prof. Jun Xu, and earned a double Bachelor's degree in engineering and economics. My research interests center on information retrieval, fairness, recommender systems, and large language models.

I am looking for highly-motivated students interested in the intersection of Economics and AI. Feel free to reach out if you are interested!

Education

Carnegie Mellon University
Postdoctoral Researcher, Jun 2026 - present, USA
Advisor: Prof. Chenyan Xiong
Renmin University of China
Ph.D. in Computer Science, 2021 - 2025, China
Advisor: Prof. Jun Xu
Renmin University of China
Bachelor in Computer Science and Economics, 2017 - 2021, China

Experiences

Visiting Ph.D. Student, IRLab, University of Amsterdam
Oct 2024 - Oct 2025 · Advisor: Prof. Maarten de Rijke
Visiting Ph.D. Student, NExT++ Lab, National University of Singapore
Sep 2023 - July 2024 · Advisor: Prof. Tat-Seng Chua, Mentor: Prof. Wenjie Wang

Research Interests

🛡️

Trustworthy AI

Fairness, diversity, and other principles for building reliable and responsible AI systems.

📈

AI × Economics

Token economics and AI-driven social simulation at the intersection of economic theory and AI.

🧠

Foundation AI Models

World models and generative AI models as the foundation of next-generation intelligent systems.

Toolkits, Surveys & Tutorials

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FairDiverse: A Comprehensive Toolkit for Fair and Diverse Information Retrieval Algorithms
Chen Xu, Zhirui Deng, Clara Rus, Xiaopeng Ye, Yuanna Liu, Jun Xu*, Zhicheng Dou*, Ji-Rong Wen, Maarten de Rijke
GitHub · Docs
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Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era
Sunhao Dai, Chen Xu, Shicheng Xu, Liang Pang, Jun Xu, Zhenhua Dong
KDD 2024 (Survey & Tutorial)
Survey Link
pdfpdf
Economic Perspectives on Fairness in Information Retrieval
Chen Xu, Clara Rus, Yuanna Liu, Marleen de Jonge, Jun Xu, Maarten de Rijke
SIGIR 2025, ECIR 2026, WWW 2026 (Tutorial)

Publications

Full list on Google Scholar.   * Corresponding author

2026
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Unveiling and Simulating Short-Video Addiction Behaviors via Economic Addiction Theory
Chen Xu, Zhipeng Yi, Ruizi Wang, Wenjie Wang, Jun Xu, Maarten de Rijke
WWW 2026
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The Attention Market: Interpreting Online Fair Re-ranking as Manifold Optimization under Walrasian Equilibrium
Chen Xu, Wei Chu, Wenyu Hu, Fengran Mo, Jun Xu, Maarten de Rijke
arXiv preprint 2026
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TacoMAS: Test-Time Co-Evolution of Topology and Capability in LLM-based Multi-Agent Systems
Chen Xu, Yicheng Hu, Ruizi Wang, Xinyu Lin, Wenjie Wang, Dongrui Liu, Fuli Feng
arXiv preprint 2026
pdfpdf
Unifying Diversity and Fairness in Re-ranking via Economic Growth Theory
Zhaofeng Li, Chen Xu*, Xinyu Lin, Wenjie Wang, Xiangnan Xiao
WWW 2026
2025
pdfpdf
FairDiverse: A Comprehensive Toolkit for Fair and Diverse Information Retrieval Algorithms
Chen Xu, Zhirui Deng, Clara Rus, Xiaopeng Ye, Yuanna Liu, Jun Xu*, Zhicheng Dou*, Ji-Rong Wen, Maarten de Rijke
SIGIR 2025 (Resource Paper)
pdfpdf
Understanding Accuracy-Fairness Trade-offs in Re-ranking through Elasticity in Economics
Chen Xu, Jujia Zhao, Wenjie Wang, Liang Pang, Jun Xu*, Tat-Seng Chua, Maarten de Rijke
SIGIR 2025
pdfpdf
CreAgent: Towards Long-Term Evaluation of Recommender System under Platform-Creator Information Asymmetry
Xiaopeng Ye, Chen Xu, Zhongxiang Sun, Jun Xu, Gang Wang, Zhenhua Dong, Ji-Rong Wen
SIGIR 2025
pdfpdf
Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation
Chen Xu, Yuxin Li, Wenjie Wang, Liang Pang, Jun Xu*, Tat-Seng Chua
ICLR 2025
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LLM-based Federated Recommendation
Jujia Zhao, Wenjie Wang*, Chen Xu*, See-Kiong Ng, Tat-Seng Chua
NAACL 2025 Findings
2024
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A Study of Implicit Ranking Unfairness in Large Language Models
Chen Xu, Wenjie Wang, Yuxin Li, Liang Pang, Jun Xu*, Tat-Seng Chua
EMNLP 2024 Findings
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A Taxation Perspective for Fair Re-ranking
Chen Xu, Xiaopeng Ye, Wenjie Wang*, Liang Pang, Jun Xu*, Tat-Seng Chua
SIGIR 2024 Best Paper Honorable Mention
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BankFair: Balancing Accuracy and Fairness under Varying User Traffic in Recommender System
Xiaopeng Ye, Chen Xu, Jun Xu*, Xuyang Xie, Gang Wang, Zhenhua Dong
CIKM 2024
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FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval
Chen Xu, Jun Xu*, Yiming Ding, Xiao Zhang, Qi Qi
WWW 2024
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LTP-MMF: Towards Long-term Provider Max-min Fairness Under Recommendation Feedback Loops
Chen Xu, Xiaopeng Ye, Jun Xu*, Xiao Zhang, Weiran Shen, Ji-Rong Wen
TOIS 2024
2023
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P-MMF: Provider Max-min Fairness Re-ranking in Recommender System
Chen Xu, Sirui Chen, Jun Xu*, Weiran Shen, Xiao Zhang, Gang Wang, Zhenhua Dong
WWW 2023 Spotlight — Best Paper Candidate
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Syntactic-Informed Graph Networks for Sentence Matching
Chen Xu, Jun Xu*, Zhenhua Dong, Ji-Rong Wen
TOIS 2023
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Uncovering ChatGPT's Capabilities in Recommender Systems
Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, Jun Xu
RecSys 2023 (FAST track)
2022
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Dually Enhanced Propensity Score Estimation in Sequential Recommendation
Chen Xu, Jun Xu*, Xu Chen, Zhenhua Dong, Ji-Rong Wen
CIKM 2022
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Semantic Sentence Matching via Interacting Syntax Graphs
Chen Xu, Jun Xu*, Zhenhua Dong, Ji-Rong Wen
COLING 2022

Professional Services

Invited Reviewer for TOIS, TIST, TKDE, JISIST, JIR
Program Committee Member of CIKM, EMNLP, KDD, WWW

Honors

Best Paper Honorable Mention, SIGIR 2024
Spotlight — Best Paper Candidate, WWW 2023
Best Oral and Poster Presentation, NCTIR 2025

© 2026 Chen Xu · Last update: June 2026
Template inspired by Prof. Xiangnan He.