"α-β" indicates alphabetical author order


2024 + Forthcoming


  1. Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?

    Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang and Haifeng Xu

    working paper


  2. A Truth Serum for Eliciting Self-Evaluations in Scientific Reviews

    (Randomized order) Jibang Wu, Haifeng Xu, Yifan Guo, Weijie Su

    working paper


  3. A Reduction from Multi-Parameter to Single-Parameter Bayesian Contract Design

    (α-β) Matteo Castiglioni, Junjie Chen, Minming Li, Haifeng Xu and Song Zuo

    Working paper


  4. Algorithmic Cheap Talk

    (α-β) Yakov Babichenko, Inbal Talgam-Cohen, Haifeng Xu and Konstantin Zabarnyi

    working paper


  5. Multi-Sender Persuasion -- A Computational Perspective

    Safwan Hossain*, Tonghan Wang*, Tao Lin*, Yiling Chen, David Parkes and Haifeng Xu

    working paper


  6. On Information Design with Spillovers

    (α-β) Ozan Candogan, Yifan Guo, and Haifeng Xu

    working paper


  7. A Data-Centric Online Market for Machine Learning: From Discovery to Pricing

    (α-β for first 3 authors) Minbiao Han, Jonathan Light, Steven Xia, Sainyam Galhotra, Raul Castro Fernandez, Haifeng Xu

    working paper


  8. Generalized Principal-Agency: Contracts, Information, Games and Beyond

    (α-β) Jiarui Gan, Minbiao Han, Jibang Wu and Haifeng Xu

    working paper


  9. Information Design in the Principal-Agent Problem

    (α-β) Yakov Babichenko, Inbal Talgam-Cohen, Haifeng Xu and Konstantin Zabarnyi

    working paper


  10. Auctioning with Strategically Reticent Bidders

    Jibang Wu, Ashwinkumar Badanidiyuru and Haifeng Xu

    working paper


  11. Mechanism Design with Large Language Models

    (α-β) Paul Duetting, Vahab Mirrokni, Renato Paes Leme, Haifeng Xu, and Song Zuo

    WWW 2024: Proc. ACM Web Conference, 2024 (oral presentation)


  12. Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation

    Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis and Haifeng Xu

    ICLR 2024: Proc. 12th International Conference on Learning Representations, 2024 (spotlight, 5%)


  13. Incentivized Truthful Communication for Federated Bandits

    Zhepei Wei, Chuanhao Li, Haifeng Xu and Hongning Wang

    ICLR 2024: Proc. 12th International Conference on Learning Representations, 2024.


  14. Learning to Persuade on the Fly: Robustness Against Ignorance

    You Zu, Krishnamurthy Iyer, Haifeng Xu

    Operations Research, to appear

    A shorter version appeared at EC 2021


  15. Learning in Online Principal-Agent Interactions: The Power of Menus

    Minbiao Han, Michael Albert and Haifeng Xu

    AAAI 2024: Proc. 38nd AAAI Conference on Artificial Intelligence, 2024.


  16. Bayesian Calibrated Click-Through Auction

    (α-β) Junjie Chen, Minming Li, Haifeng Xu and Song Zuo

    ICALP 2024: Proc. 51st EATCS International Colloquium on Automata, Languages, and Programming, 2024.


    17. 2023


  17. Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

    Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang and Haifeng Xu

    NeurIPS 2023: Proc. 37th Conference on Neural Information Processing Systems, 2023.


  18. Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts

    Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru and Haifeng Xu

    NeurIPS 2023: Proc. 37th Conference on Neural Information Processing Systems, 2023 (spotlight)


  19. Incentivized Communication for Federated Bandits

    Zhepei Wei, Chuanhao Li, Haifeng Xu and Hongning Wang

    NeurIPS 2023: Proc. 37th Conference on Neural Information Processing Systems, 2023.


  20. Markov Persuasion Processes with Endogenous Agent Beliefs

    (α-β) Krishnamurthy Iyer, Haifeng Xu and You Zu

    WINE 2023: Proc. 19'th Conference On Web And Internet Economics, 2023.


  21. The Economics of Machine Learning

    Haifeng Xu

    IJCAI 2023 (Early Career Spotlight Paper): Proc. 32nd International Joint Conference on Artificial Intelligence, 2023.


  22. Robust Stackelberg Equilibria

    (α-β) Jiarui Gan, Minbiao Han, Jibang Wu, and Haifeng Xu

    EC 2023: Proc. 24th ACM Conference on Economics and Computation, 2023.


  23. How Bad is Top-K Recommendation under Competing Content Creators?

    Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang and Haifeng Xu

    ICML 2023: Proc. 40th International Conference on Machine Learning, 2023 (live presentation)


  24. Competitive Information Design for Pandora’s Box [slides]

    (α-β) Bolin Ding, Yiding Feng, Chien-Ju Ho, Wei Tang and Haifeng Xu

    SODA 2023: Proc. 34th ACM-SIAM Symposium on Discrete Algorithms, 2023.


  25. Incentivizing Exploration in Linear Bandits under Information Gap

    Huazheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu and Hongning Wang

    RecSys 2023: Proc. 17th ACM Conference on Recommender Systems， 2023.


    26. 2022


  26. Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards

    (α-β) Ashwinkumar Badanidiyuru, Zhe Feng, Tianxi Li and Haifeng Xu

    NeurIPS 2022: Proc. 36th Conference on Neural Information Processing Systems, 2022.


  27. Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality.

    Jibang Wu, Weiran Shen, Fei Fang and Haifeng Xu

    NeurIPS 2022: Proc. 36th Conference on Neural Information Processing Systems, 2022.


  28. CS-Shapley: Class-wise Shapley Values for Data Valuation in Classification.

    Stephanie Schoch, Haifeng Xu and Yangfeng Ji.

    NeurIPS 2022: Proc. 36th Conference on Neural Information Processing Systems, 2022.


  29. Regret-Minimizing Bayesian Persuasion

    (α-β) Yakov Babichenko, Inbal Talgam-Cohen, Haifeng Xu and Konstantin Zabarnyi

    Games and Economic Behavior (GEB), 2022 (an extended abstract appeared at EC 2021)


  30. Multi-Agent Learning for Iterative Dominance Elimination: Formal Barriers and New Algorithms

    (α-β) Jibang Wu, Haifeng Xu and Fan Yao

    COLT 2022: Proc. 35th Annual Conference on Learning Theory, 2022.


  31. Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning

    Jibang Wu, Zixuan Zhang, Zhe Feng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan and Haifeng Xu

    EC 2022: Proc. 23th ACM Conference on Economics and Computation, 2022.


  32. Algorithmic Information Design in Multi-Player Games: Possibility and Limits in Singleton Congestion

    Chenghan Zhou, Thanh H. Nguyen and Haifeng Xu

    EC 2022: Proc. 23th ACM Conference on Economics and Computation, 2022.


  33. Online Bayesian Recommendation with No Regret

    (α-β) Yiding Feng, Wei Tang, Haifeng Xu

    EC 2022: Proc. 23th ACM Conference on Economics and Computation, 2022.


  34. Learning from a Learning User for Optimal Recommendations

    Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang and Haifeng Xu

    ICML 2022: Proc. 39th International Conference on Machine Learning, 2022.


  35. When Are Linear Stochastic Bandits Attackable?

    Huazheng Wang, Haifeng Xu and Hongning Wang

    ICML 2022: Proc. 39th International Conference on Machine Learning, 2022.


  36. Selling Data To a Machine Learner: Pricing via Costly Signaling

    (α-β) Junjie Chen, Minming Li and Haifeng Xu

    ICML 2022: Proc. 39th International Conference on Machine Learning, 2022.


  37. Information Design for Multiple Independent and Self-Interested Defenders: Work Less, Pay Off More

    Chenghan Zhou, Andrew Spivey, Haifeng Xu and Thanh Hong Nguyen

    UAI 2022: Proc. 38th Conference on Uncertainty in Artificial Intelligence, 2022 (also accepted to Games Journal)


  38. Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning

    (α-β for first two authors) Anshuka Rangi, Haifeng Xu, Long Tran-Thanh and Massimo Franceschetti

    IJCAI 2022: Proc. 31st International Joint Conference on Artificial Intelligence, 2022 (long oral, 3.75%).


  39. Learning the Optimal Recommendation from Explorative Users

    Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang and Haifeng Xu

    AAAI 2022: Proc. 36nd AAAI Conference on Artificial Intelligence, 2022.


  40. The Strange Role of Information Asymmetry in Auctions -- Does More Accurate Value Estimation Benefit A Bidder?

    Haifeng Xu and Ruggiero Cavallo

    AAAI 2022: Proc. 36nd AAAI Conference on Artificial Intelligence, 2022 (oral presentation).


  41. First-order Convex Fitting and Its Application to Economics and Optimization

    (α-β) Quinlan Dawkins, Minbiao Han and Haifeng Xu

    AAAI 2022: Proc. 36nd AAAI Conference on Artificial Intelligence, 2022 (oral presentation).


  42. Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification

    (α-β) Anshuka Rangi, Long Tran-Thanh, Haifeng Xu and Massimo Franceschetti

    AAAI 2022: Proc. 36nd AAAI Conference on Artificial Intelligence, 2022 (oral presentation).


  43. When Can the Defender Effectively Deceive Attackers in Security Games?

    Thanh Nguyen and Haifeng Xu

    AAAI 2022: Proc. 36nd AAAI Conference on Artificial Intelligence, 2022.


  44. Multi-Channel Bayesian Persuasion

    (α-β) Yakov Babichenko, Inbal Talgam-Cohen, Haifeng Xu and Konstantin Zabarnyi

    ITCS 2022: Proc. 13th Innovations in Theoretical Computer Science conference, 2022.


    45. 2021


  45. The Limits of Optimal Pricing in the Dark

    (α-β) Quinlan Dawkins, Minbiao Han and Haifeng Xu

    NeurIPS 2021: Proc. 35th Conference on Neural Information Processing Systems, 2021.


  46. Least Square Calibration for Peer Reviews

    Sijun Tan, Jibang Wu, Xiaohui Bei and Haifeng Xu

    NeurIPS 2021: Proc. 35th Conference on Neural Information Processing Systems, 2021.


  47. (Almost) Free Incentivized Exploration from Decentralized Learning Agents

    Chengshuai Shi, Haifeng Xu, Wei Xiong and Cong Shen

    NeurIPS 2021: Proc. 35th Conference on Neural Information Processing Systems, 2021.


  48. Efficient Algebraic Multigrid Methods for Multilevel Overlapping Co-Clustering of User-Item Relationships

    Haifeng Xu, Rasha F. Kashef, Hans De Sterck, and Geoffrey Sanders

    Informs Journal on Computing, 2021.


  49. PAC-Learning for Strategic Classification

    (α-β) Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao

    The Journal of Machine Learning Research (JMLR)

    A shorter version appeared at ICML 2021 (long oral, 3%)


  50. Diffusion Source Identification on Networks with Statistical Confidence

    (α-β) Quinlan Dawkins, Tianxi Li, Haifeng Xu

    ICML 2021: Proc. 38th International Conference on Machine Learning, 2021.


  51. Optimal Pricing of Information

    (α-β) Shuze Liu, Weiran Shen and Haifeng Xu

    EC 2021: Proc. 22th ACM Conference on Economics and Computation, 2021.


  52. The Power of Signaling and its Intrinsic Connection to the Price of Anarchy

    James Nachbar, Haifeng Xu

    DAI 2021: Proc. 3rd International Conference on Distributed Artificial Intelligence, 2021.


    53. 2020


  53. Collapsing Bandits and Their Application to Public Health Interventions

    Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

    NeurIPS 2020: Proc. 34th Conference on Neural Information Processing Systems, 2020.


  54. The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation

    (α-β) Zhe Feng, David C. Parkes, Haifeng Xu

    ICML 2020: Proc. 37th International Conference on Machine Learning, 2020.


  55. To Warn or Not to Warn: Online Signaling in Audit Games

    Chao Yan, Haifeng Xu, Yevgeniy Vorobeychik, Bo Li, Daniel Fabbri, Bradley Malin

    ICDE 2020: Proc. 36th IEEE International Conference on Data Engineering, 2020. (oral presentation)


  56. To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and Sustainability

    Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, and Milind Tambe

    AAAI 2020: Proc. 34nd AAAI Conference on Artificial Intelligence, 2020. (oral presentation)


  57. Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents

    Sarah Keren, Haifeng Xu, Kofi Kwapong, David Parkes, and Barbara Grosz

    AAAI 2020: Proc. 34nd AAAI Conference on Artificial Intelligence, 2020. (oral presentation)


  58. On the Tractability of Public Persuasion with No Externalities

    Haifeng Xu

    SODA 2020: Proc. 31st ACM-SIAM Symposium on Discrete Algorithms, 2020.


  59. Selling Information through Consulting

    (α-β) Yiling Chen, Haifeng Xu, Shuran Zheng

    SODA 2020: Proc. 31st ACM-SIAM Symposium on Discrete Algorithms, 2020.


  60. Tackling Imitative Attacker Deception in Repeated Bayesian Stackelberg Security Games

    Thanh Nguyen, Andrew Butler and Haifeng Xu

    ECAI 2020: Proc. the 24th European Conference on Artificial Intelligence, 2020.



    61. 2019


  61. Computing Equilibria of Prediction Markets via Persuasion.

    (α-β) Jerry Anunrojwong, Yiling Chen, Bo Waggoner and Haifeng Xu

    WINE 2019: Proc. 15th Conference on Web and Internet Economics, 2019.


  62. Imitative Follower Deception in Stackelberg Games

    Jiarui Gan, Haifeng Xu, Qingyu Guo, Long Tran-Thanh, Zinovi Rabinovich and Michael Wooldridge

    EC 2019: Proc. 20th ACM Conference on Economics and Computation, 2019.


  63. Imitative Attacker Deception in Stackelberg Security Games.

    (α-β) Thanh H. Nguyen and Haifeng Xu

    IJCAI 2019: Proc. 28th International Joint Conference on Artificial Intelligence, 2019.


  64. Cyber Camouflage Games for Strategic Deception

    Omkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld, and Fei Fang

    GameSec 2019: Proc. 10th Conference on Decision and Game Theory for Security, 2019.



    65. 2018 + Before


  65. Targeting and Signaling in Ad Auctions

    (α-β) Ashwinkumar Badanidiyuru, Kshipra Bhawalkar and Haifeng Xu

    SODA 2018: Proc. 29th ACM-SIAM Symposium on Discrete Algorithms, 2018.


  66. Strategic Coordination of Human Patrollers and Mobile Sensors with Signaling for Security Games

    Haifeng Xu, Kai Wang, Phebe Vayanos and Milind Tambe

    AAAI 2018: Proc. 32nd AAAI Conference on Artificial Intelligence. (oral presentation)


  67. Deceiving Cyber Adversaries: A Game Theoretic Approach

    Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Long Tran-Thanh, Phebe Vayanos, Yevgeniy Vorobeychik

    AAMAS 2018: Proc. 17th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, 2018.


  68. Mitigating the Curse of Correlation in Security Games by Entropy Maximization

    Haifeng Xu, Shaddin Dughmi, Milind Tambe and Venil Loyd Noronha

    AAMAS 2018: Proc. 17th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, 2018.


  69. Algorithmic Persuasion with No Externalities

    (α-β) Shaddin Dughmi and Haifeng Xu

    EC 2017: Proc. 18th ACM Conference on Economics and Computation, 2017.


  70. Optimal Patrol Planning for Green Security Games with Black-Box Attackers

    Haifeng Xu, Benjamin Ford, Fei Fang, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga

    GameSec 2017: Proc. 8th Conference on Decision and Game Theory for Security, 2017.


  71. Don’t Bury your Head in Warnings: A Game-Theoretic Approach for Intelligent Allocation of Cyber-security Alerts

    Aaron Schlenker, Haifeng Xu, Mina Guirguis, Chris Kiekintveld, Arunesh Sinha, Milind Tambe, Solomon Sonya, Darryl Balderas, Noah Dunstatter

    IJCAI 2017: Proc. 26th International Joint Conference on Artificial Intelligence, 2017.


  72. The Mysteries of Security Games: Equilibrium Computation Becomes Combinatorial Algorithm Design

    Haifeng Xu

    EC 2016: Proc. 17th ACM Conference on Economics and Computation, 2016.


  73. Algorithmic Bayesian Persuasion

    (α-β) Shaddin Dughmi, Haifeng Xu

    STOC 2016: Proc. 48th ACM Symposium on Theory of Computing, 2016. (Invited to SICOMP Special Issue for STOC 2016)


  74. Signaling in Bayesian Stackelberg Games

    Haifeng Xu, Rupert Freeman, Vincent Conitzer, Shaddin Dughmi, Milind Tambe

    AAMAS 2016: Proc. 15th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, 2016.


  75. Playing Repeated Security Games with No Prior Knowledge

    Haifeng Xu, Long Tran Thanh, Nick Jennings

    AAMAS 2016: Proc. 15th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, 2016.


  76. Using Social Networks to Aid Homeless Shelters: Dynamic Influence Maximization under Uncertainty

    Amulya Yadav, Hau Chan, Albert Jiang, Haifeng Xu, Eric Rice, Milind Tambe

    AAMAS 2016: Proc. 15th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, 2016.


  77. Security Games with Information Leakage: Modeling and Computation [arXiv version]

    Haifeng Xu, Albert X. Jiang, Arunesh Sinha, Zinovi Rabinovich, Shaddin Dughmi, Milind Tambe

    IJCAI 2015: Proc. 24th International Joint Conference on Artificial Intelligence, 2015.


  78. Computing Optimal Mixed Strategies for Security Games with Dynamic Payoffs [appendix]

    Yue Yin, Haifeng Xu, Jiarui Gan, Bo An, Albert X. Jiang

    IJCAI 2015: Proc. 24th International Joint Conference on Artificial Intelligence, 2015.


  79. Information Disclosure as a Means to Security

    Zinovi Rabinovich, Albert X. Jiang, Manish Jain, Haifeng Xu

    AAMAS 2015: Proc. 14th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, 2015.


  80. Exploring Information Asymmetry in Two-Stage Security Games

    Haifeng Xu, Zinovi Rabinovich, Shaddin Dughmi, Milind Tambe

    AAAI 2015: Proc. 29nd AAAI Conference on Artificial Intelligence.


  81. Solving Zero-Sum Security Games in Discretized Spatio-Temporal Domains [appendix]

    Haifeng Xu, Fei Fang, Albert Jiang, Vincent Conitzer, Shaddin Dughmi, Milind Tambe

    AAAI 2014: Proc. 28nd AAAI Conference on Artificial Intelligence.


  82. Give a Hard Problem to a Diverse Team: Exploring Large Action Spaces [appendix]

    Leandro Marcolino, Haifeng Xu, Albert Jiang, Milind Tambe, Emma Bowring

    AAAI 2014: Proc. 28nd AAAI Conference on Artificial Intelligence.


  83. Improving the Efficiency of Crowdsourcing Contests

    Haifeng Xu, Kate Larson

    AAMAS 2014: Proc. 13th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, 2014.


  84. Predicting Advertiser Bidding Behaviors in Sponsored Search by Rationality Modeling

    Haifeng Xu, Bin Gao, Diyi Yang, Tieyan Liu

    WWW 2013: Proc. 22th Intl. World Wide Web Conference, 2013.