AI RESEARCH
AgentA/B: Automated and Scalable Web A/BTesting with Interactive LLM Agents
arXiv CS.CL
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ArXi:2504.09723v4 Announce Type: replace-cross A/B testing experiment is a widely adopted method for evaluating UI/UX design decisions in modern web applications. Yet, traditional A/B testing remains constrained by its dependence on the large-scale and live traffic of human participants, and the long time of waiting for the testing result. Through formative interviews with six experienced industry practitioners, we identified critical bottlenecks in current A/B testing workflows.