Conference Publications |

Does AI Help or Harm? Endogenous Information Acquisition with AI Advice
Kexin Chen, Tao Lin, Jianwei Huang
Conference on Web and Internet Economics (WINE), 2026

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Explainable Information Design
(Alphabet) Yiling Chen, Tao Lin, Wei Tang, Jamie Tucker-Foltz
ACM Conference on Economics and Computation (EC), 2026

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Information Design With Large Language Models
(Alphabet) Paul Duetting, Safwan Hossain, Tao Lin, Renato Paes Leme, Sai Srivatsa Ravindranath, Haifeng Xu, Song Zuo
ACM Conference on Economics and Computation (EC), 2026

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Gradient Dynamics in First-Price Auctions: Iterative Strategy Elimination via Cubic Potentials
Mete Şeref Ahunbay, Weiqiang Zheng, Tao Lin
ACM Conference on Economics and Computation (EC), 2026

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Reward Shaping for (Inference-Time) Alignment: A Stackelberg Game Perspective
Haichuan Wang, Tao Lin, Lingkai Kong, Ce Li, Hezi Jiang, Milind Tambe
International Conference on Machine Learning (ICML), 2026

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On the Coordination of Value-Maximizing Bidders
Yanru Guan, Jiahao Zhang, Zhe Feng, Tao Lin
International Conference on Machine Learning (ICML), 2026

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Learning a Game by Paying the Agents
Brian Hu Zhang*, Tao Lin*, Yiling Chen, Tuomas Sandholm
International Conference on Learning Representations (ICLR), 2026

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Learning to Play Multi-Follower Bayesian Stackelberg Games
Gerson Personnat, Tao Lin, Safwan Hossain, David C. Parkes
International Conference on Learning Representations (ICLR), 2026

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A Unified Approach to Submodular Maximization Under Noise
(Alphabet) Kshipra Bhawalkar, Yang Cai, Zhe Feng, Christopher Liaw, Tao Lin
Neural Information Processing Systems (NeurIPS), 2025

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Generalized Principal-Agent Problem with a Learning Agent
Tao Lin, Yiling Chen
International Conference on Learning Representations (ICLR spotlight), 2025

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