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Foundation Models and LLMs

[Mechanism Design for LLMs, Uncertainty with ML Models]

(Note:     students under my supervision;  † equal contribution;  * corresponding author)​​​​​

 

Mechanism Design for LLMs

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• Incentivizing truthful language models via peer elicitation games. [proceedings​][preprint][code]

Baiting Chen†, Tong Zhu†, Jiale Han, Lexin Li, Gang Li, and Xiaowu Dai*.

Advances in Neural Information Processing Systems (NeurIPS), 2025.

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• A survey on mechanism design meets large language models. [pdf][code​]

Baiting Chen, Tong Zhu, Xuanang Li, Yichi Zhang, and Xiaowu Dai*.

Preprint, 2026.​

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• ALIGN: Aligned delegation with performance guarantees for multi-agent LLM reasoning. [pdf​][code​]

Tong Zhu†, Baiting Chen†, Jin Zhou, Hua Zhou, Sriram Sankararaman, and Xiaowu Dai*.

Preprint, 2026.

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• Common-agency games for multi-objective test-time alignment. [pdf][code]

Baiting Chen†, Tong Zhu†, Rui Yu†, and Xiaowu Dai*.

Preprint, 2026.

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Uncertainty with ML Models​​​

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• Surrogate-powered inference: Regularization and adaptivity. [pdf​]

Jianmin Chen, Huiyuan Wang, Thomas Lumley, Xiaowu Dai, and Yong Chen.

Under Major Revisions at Journal of the American Statistical Association (JASA), 2025.

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• Prediction-powered conditional inference. [pdf​][code]

Yang Sui, Jin Zhou, Hua Zhou, and Xiaowu Dai*.

Preprint, 2026.

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• Prompt-dependent ranking of large language models with uncertainty quantification. [pdf​][code​]

Angel Rodrigo Avelar Menendez, Yufeng Liu, and Xiaowu Dai*.

Preprint, 2026.

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