Robust Sequential Experimental Design for A/B Testing

Qianglin Wen; Xiangkun Wu; Chengchun Shi; Ting Li; Niansheng Tang; Yingying Zhang; Hongtu Zhu

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arXiv · 2605.12899

Robust Sequential Experimental Design for A/B Testing

Qianglin Wen·Xiangkun Wu·Chengchun Shi·Ting Li·Niansheng Tang·Yingying Zhang·Hongtu Zhu

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Abstract

Experimental design has emerged as a powerful approach for improving the sample efficiency of A/B testing, yet existing designs rely critically on correctly specified models. We study robust sequential experimental design under model misspecification and develop a unified framework that covers both contextual bandit and dynamic settings. Theoretically, we prove that our design bounds the worst-case mean squared error of the estimated treatment effect. Empirically, we demonstrate the effectiveness of the proposed approach using synthetic and real-world datasets from a leading technology company.

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Qianglin Wen, Xiangkun Wu, Chengchun Shi, Ting Li, Niansheng Tang, Yingying Zhang, Hongtu Zhu. 2026-05-13. Robust Sequential Experimental Design for A/B Testing. https://arxiv.org/abs/2605.12899

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