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Full publication list can be found in my [CV]

Recent Preprints

• Strategic Planning and Rationalizing on Trees Make LLMs Better Debaters
  Danqing Wang, Zhuorui Ye, Xinran Zhao, Fei Fang, Lei Li (2025)
• Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
  Yixuan Even Xu, Yash Savani, Fei Fang, Zico Kolter (2025)
• Grounded Persuasive Language Generation for Automated Marketing
  Jibang Wu, Chenghao Yang, Simon Mahns, Chaoqi Wang, Hao Zhu, Fei Fang, Haifeng Xu (2025)
• Cooperative Strategic Planning Enhances Reasoning Capabilities in Large Language Models
  Danqing Wang, Zhuorui Ye, Fei Fang, Lei Li (2024)
• Out of the Past: An AI-Enabled Pipeline for Traffic Simulation from Noisy, Multimodal Detector Data and Stakeholder Feedback
  Rex Chen, Karen Wu, John McCartney, Norman Sadeh, Fei Fang (2025)
• Making Teams and Influencing Agents: Efficiently Coordinating Decision Trees for Interpretable Multi-Agent Reinforcement Learning
  Rex Chen, Stephanie Milani, Zhicheng Zhang, Norman Sadeh, Fei Fang (2025)
• Persuasive Prediction via Decision Calibration
  Jingwu Tang, Jiahao Zhang, Fei Fang, Zhiwei Steven Wu (2025)
• Safe Multi-agent Reinforcement Learning with Natural Language Constraints
  Ziyan Wang, Meng Fang, Tristan Tomilin, Fei Fang, Yali Du (2024)
• On the Detection of Reviewer-Author Collusion Rings From Paper Bidding
  Steven Jecmen, Nihar B. Shah, Fei Fang, Leman Akoglu (2024)

Recent Publications

• REALM: A Dataset of Real-World LLM Use Cases
  Jingwen Cheng, Kshitish Ghate, Wenyue Hua, William Yang Wang, Hong Shen, Fei Fang. In ACL 2025 Findings.
• M3HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
  Ziyan Wang, Zhicheng Zhang, Fei Fang, Yali Du. In ICML 2025.
• Missing Pieces: How Framing Uncertainty Impacts Longitudinal Trust in AI Decision Aids — A Gig Driver Case Study
  Rex Chen, Ruiyi Wang, Fei Fang, Norman Sadeh. In FAccT 2025.
• Teamwork Makes the Defense Work: Defense Resource Allocation with Composable Targets
  Siyu Liu, Rida Bazzi, Fei Fang, Tiffany Bao. In AAMAS 2025.
• CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy
  Mian Zhang, Xianjun Yang, Xinlu Zhang, Travis Labrum, Jamie C. Chiu, Shaun M. Eack, Fei Fang, William Yang Wang, Zhiyu Zoey Chen. In NAACL 2025.
• TypedThinker: Typed Thinking Improves Large Language Model Reasoning
  Danqing Wang, Jianxin Ma, Fei Fang, Lei Li. In ICLR 2025.
• LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning
  Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon, Fei Fang. In ICLR 2025.
• Training Users Against Human and GPT-4 Generated Social Engineering Attacks
  Tyler Malloy, Maria Jose Ferreira, Fei Fang, Cleotilde Gonzalez. In HCII 2025.
• Improving Community-Participated Patrol for Anti-Poaching
  Yufei Wu, Yixuan Even Xu, Xuming Zhang, Duo Liu, Shibing Zhu, Fei Fang. In AAAI 2025.
• Deviate or Not: Learning Coalition Structures with Multiple-bit Observations in Games
  Yixuan Even Xu, Zhe Feng, Fei Fang. In AAAI 2025.
• Leveraging a Cognitive Model to Measure Subjective Similarity of Human and GPT-4 Written Content
  Tyler Malloy, Maria José Ferreira, Fei Fang, Cleotilde Gonzalez. In CONLL 2024.
• Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
  Jingwu Tang, Gokul Swamy, Fei Fang, Zhiwei Steven Wu. In NeurIPS 2024.
• Global Rewards in Restless Multi-Armed Bandits
  Naveen Raman, Zheyuan Ryan Shi, Fei Fang. In NeurIPS 2024.
• PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals
  Ruiyi Wang, Stephanie Milani, Jamie C. Chiu, Jiayin Zhi, Shaun M. Eack, Travis Labrum, Samuel M. Murphy, Nev Jones, Kate Hardy, Hong Shen, Fei Fang, Zhiyu Zoey Chen. In EMNLP 2024.
• MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure
  Zhicheng Zhang, Yancheng Liang, Yi Wu, Fei Fang. In AAMAS 2024.
• RELand: Risk Estimation of Landmines via Interpretable Invariant Risk Minimization
  Mateo Dulce Rubio, Siqi Zeng, Qi Wang, Didier Alvarado, Francisco Moreno, Hoda Heidari, Fei Fang. In ACM Journal on Computing and Sustainable Societies (JCSS). 2024
• Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning
  Jiayu Chen, Zelai Xu, Yunfei Li, Chao Yu, Jiaming Song, Huazhong Yang, Fei Fang, Yu Wang, Yi Wu. In AAAI 2024.
• Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages
  Sameer Jain, Sedrick Scott Keh, Shova Chettri, Karun Dewan, Pablo Izquierdo, Johanna Prussman, Pooja Shreshtha, Cesar Suarez, Zheyuan Ryan Shi, Lei Li, Fei Fang. In AAAI 2024 AI for Social Impact Track.
• Learning Coalition Structures with Games
  Yixuan Even Xu, Chun Kai Ling, Fei Fang. In AAAI 2024.
• Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
  Zelai Xu, Chao Yu, Fei Fang, Yu Wang, Yi Wu. In ICML 2024.
• Testing for Reviewer Anchoring in Peer Review: A Randomized Controlled Trial
  Ryan Liu, Steven Jecmen, Vincent Conitzer, Fei Fang, Nihar B. Shah. In PloS one 19 (11), e0301111. 2024.
• NewsPanda: Media Monitoring for Timely Conservation Action
  Sedrick Scott Keh, Zheyuan Ryan Shi, David J. Patterson, Nirmal Bhagabati, Karun Dewan, Areendran Gopala, Pablo Izquierdo, Debojyoti Mallick, Ambika Sharma, Pooja Shrestha, Fei Fang. In AAAI 2024.
• MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning
  Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran. In AAMAS 2024.
• A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment
  Yixuan Even Xu, Steven Jecmen, Zimeng Song, Fei Fang. In NeurIPS 2023.
• Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
  Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzpecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann. In CHI 2023.
• Multi-defender Security Games with Schedules
  Zimeng Song, Chun Kai Ling, Fei Fang. In GameSec 2023.
• Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?
  Rex Chen, Kathleen M. Carley, Fei Fang, Norman Sadeh. In WSC 2023.
• Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games
  Chun Kai Ling, J. Zico Kolter, Fei Fang. In AAAI 2023.
• A Survey of Explainable Reinforcement Learning
  Explainable Reinforcement Learning: A Survey and Comparative Review. In ACM Computing Surveys, doi:10.1145/3616864 2023.
• Explainable Action Advising for Multi-Agent Reinforcement Learning
  Yue Guo, Joseph Campbell, Simon Stepputtis, Ruiyu Li, Dana Hughes, Fei Fang, Katia Sycara. In ICRA 2023.
• A Dataset on Malicious Paper Bidding in Peer Review
  Steven Jecmen, Minji Yoon, Vincent Conitzer, Nihar B. Shah, Fei Fang. In the Web Conference 2023.
• Safe Subgame Resolving for Extensive Form Correlated Equilibrium
  Chun Kai Ling, Fei Fang. In AAAI 2022.
• Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation
  Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao. In NeurIPS 2022.
• Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality
  Jibang Wu, Weiran Shen, Fei Fang, Haifeng Xu. In NeurIPS 2022.
• MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
  Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles Kamhoua, Evangelos E. Papalexakis, Fei Fang. In ECML-PKDD 2022.
• Ranked Prioritization of Groups in Combinatorial Bandit Allocation
  Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe. In IJCAI 2022 Special Track on AI for Good.
• PerfectDou: Dominating DouDizhu with Perfect Information Distillation
  Guan Yang, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang, Guangjun Zeng, Yue Lin. In NeurIPS 2022.
• Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training
  Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao. In IJCAI 2022.
• Fighting the Fog: Evaluating the Clarity of Privacy Disclosures in the Age of CCPA
  Rex Chen, Fei Fang, Thomas Norton, Aleecia M. McDonald, Norman Sadeh. In WPES 2021.
• Temporal Induced Self-Play for Stochastic Bayesian Games
  Weizhe Chen, Zihan Zhou, Yi Wu, Fei Fang. In IJCAI 2021.
• Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design
  Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah. In HCOMP 2022.
• Robust Reinforcement Learning Under Minimax Regret for Green Security
  Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe. In UAI 2021.
• Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization
  Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Du, Yu Wang, Yi Wu. In ICLR 2021.
• Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods
  Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso. In AAAI 2021.
• Spatio-Temporal Pricing for Ridesharing Platforms
  Hongyao Ma, Fei Fang, David C. Parkes. In Operations Research, 2021
• Dual-Mandate Patrols: Multi-Armed Bandits for Green Security
  Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe. In AAAI 2021 AI for Social Impact Track.
• Deep Archimedean Copulas
  Chun Kai Ling, Fei Fang, J. Zico Kolter. In NeurIPS 2020.
• Bandit Data-Driven Optimization
  Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani, Fei Fang. In AAAI 2022 AI for Social Impact Track
• Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments
  Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang. In NeurIPS 2020.
• Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
  Qian Long, Zihan Zhou, Abhibav Gupta, Fei Fang, Yi Wu, Xiaolong Wang. In ICLR 2020.
• Green Security Game with Community Engagement
  Taoan Huang, Weiran Shen, David Zeng, Tianyu Gu, Rohit Singh, Fei Fang. In AAMAS 2020.
• Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK
  Zheyuan Ryan Shi, Aaron Schlenker, Brian Hay, Daniel Bittleston, Siyu Gao, Emily Peterson, John Trezza, Fei Fang. In AAAI 2020.

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