Large Language Models

Foundation Models and LLMs

[Mechanism Design for LLMs, Uncertainty Quantification with ML Models]

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

Mechanism Design for LLMs

(Review)

Mechanism design meets large language models: Foundations and frontiers. [journal][preprint][code]

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

Statistical Learning and Data Science (SLADS), special issue on “Statistics and AI", 2026.

(Hallucination)

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.

Ali Kaazempur-Mofrad, Xiaowu Dai*, and Xuming He.

Preprint, 2026.

(Reasoning)

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.

(Alignment)

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

Preprint, 2026.

Uncertainty Quantification with ML Models

(ML-Powered Inference)

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

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

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

Under Major Revisions at Journal of the Royal Statistical Society Series B: Statistical Methodology (JRSSB), 2026.

(LLM Evaluation)

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

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

Preprint, 2026.

Statistical inference for LLM evaluations: From multiple auxiliary predictors to valid uncertainty quantification. [pdf][code]

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

Preprint, 2026.