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350 results
2026
N. Lopez, F. J. M. Cossío, J. R. T. Ayala, and D. C. Parkes,
“Dynamic Welfare-Maximizing Pooled Testing”, arXiv preprint arXiv:2601.22419, 2026.
N. Lopez, F. J. M. Cossío, J. R. T. Ayala, and D. C. Parkes,
“Dynamic Welfare-Maximizing Pooled Testing”, arXiv preprint arXiv:2601.22419, 2026.
Y. Jiang, D. C. Parkes, and T. Wang,
“Duality for optimal multi-item, multi-bidder auction design: Revenue certificates through deep learning”, Proc. 27th ACM Conf on Economics and Computation (EC’26), 2026.
Y. Jiang, D. C. Parkes, and T. Wang,
“Duality for optimal multi-item, multi-bidder auction design: Revenue certificates through deep learning”, Proc. 27th ACM Conf on Economics and Computation (EC’26), 2026.
N. Thach, H. Chan, D. C. Parkes, and K. R. Lakhani,
“Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach”, In Proc. ACM Conference on Human-AI Complementarity and Alignment (HCOMP). 2026.
N. Thach, H. Chan, D. C. Parkes, and K. R. Lakhani,
“Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach”, In Proc. ACM Conference on Human-AI Complementarity and Alignment (HCOMP). 2026.
G. Personnat, T. Lin, S. Hossain, and D. C. Parkes,
“Learning to play multi-follower Bayesian Stackelberg games”, In Proc. 14th Int Conf on Learning Representations (ICLR), vol. 105160-105189. 2026.
G. Personnat, T. Lin, S. Hossain, and D. C. Parkes,
“Learning to play multi-follower Bayesian Stackelberg games”, In Proc. 14th Int Conf on Learning Representations (ICLR), vol. 105160-105189. 2026.
G. Seo, X. Wang, and D. C. Parkes,
“Understanding strategic platform entry and seller exploration: A Stackelberg model”, In Proc. 35th ACM Web Conference (WWW), vol. 396-407. 2026.
G. Seo, X. Wang, and D. C. Parkes,
“Understanding strategic platform entry and seller exploration: A Stackelberg model”, In Proc. 35th ACM Web Conference (WWW), vol. 396-407. 2026.
S. Fish et al.,
“Generative social choice”, Journal of the ACM, vol. 73 (2), no. 1-11, 2026.
S. Fish et al.,
“Generative social choice”, Journal of the ACM, vol. 73 (2), no. 1-11, 2026.
T. Wang, Y. Pan, X. Yang, Y. Jiang, M. Tambe, and D. C. Parkes,
“LLM Active Alignment: A Nash Equilibrium Perspective”, arXiv preprint arXiv:2602.06836, 2026.
T. Wang, Y. Pan, X. Yang, Y. Jiang, M. Tambe, and D. C. Parkes,
“LLM Active Alignment: A Nash Equilibrium Perspective”, arXiv preprint arXiv:2602.06836, 2026.
2025
A. Tacchetti et al.,
“Deep mechanism design: Learning social and economic policies for human benefit.”, Proceedings of the National Academy of Sciences of the United States of America, vol. 122, no. 25, p. e2319949121, 2025, doi: 10.1073/pnas.2319949121.
A. Tacchetti et al.,
“Deep mechanism design: Learning social and economic policies for human benefit.”, Proceedings of the National Academy of Sciences of the United States of America, vol. 122, no. 25, p. e2319949121, 2025, doi: 10.1073/pnas.2319949121.
Human society is coordinated by mechanisms that control how prices are agreed, taxes are set, and electoral votes are tallied. The design of robust and effective mechanisms for human benefit is a core problem in the social, economic, and political...
M. Curry, Z. Fan, Y. Jiang, S. S. Ravindranath, T. Wang, and D. C. Parkes,
“Automated Mechanism Design: A Survey”, ACM SIGecom Exchanges, vol. 22, no. 2, pp. 102–120, 2025.
M. Curry, Z. Fan, Y. Jiang, S. S. Ravindranath, T. Wang, and D. C. Parkes,
“Automated Mechanism Design: A Survey”, ACM SIGecom Exchanges, vol. 22, no. 2, pp. 102–120, 2025.
T. Wang, Y. Jiang, and D. Parkes,
“BundleFlow: Deep Menus for Combinatorial Auctions by Diffusion-Based Optimization”, 39th Annual Conference on Neural Information Processing Systems NeurIPS. 2025.
T. Wang, Y. Jiang, and D. Parkes,
“BundleFlow: Deep Menus for Combinatorial Auctions by Diffusion-Based Optimization”, 39th Annual Conference on Neural Information Processing Systems NeurIPS. 2025.
T. Wang, H. Dong, Y. Jiang, D. C. Parkes, and M. Tambe,
“On diffusion models for multi-agent partial observability: Shared attractors, error bounds, and composite flow”, Proc. 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025. pp. 2143–2152, 2025.
T. Wang, H. Dong, Y. Jiang, D. C. Parkes, and M. Tambe,
“On diffusion models for multi-agent partial observability: Shared attractors, error bounds, and composite flow”, Proc. 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025. pp. 2143–2152, 2025.
R. Trivedi, K. Sharma, and D. C. Parkes,
“Inner speech as behavior guides: Steerable imitation of diverse behaviors for Human-AI coordination”, Proc. 39th Annual Conference on Neural Information Processing Systems NeurIPS. 2025.
R. Trivedi, K. Sharma, and D. C. Parkes,
“Inner speech as behavior guides: Steerable imitation of diverse behaviors for Human-AI coordination”, Proc. 39th Annual Conference on Neural Information Processing Systems NeurIPS. 2025.