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Author

Ziyad Benomar

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#artificial intelligence Preprint Sep 2026

Augmented Hypothesis Testing with Persona-Based LLM Simulations

A/B testing requires large sample sizes, long timelines, and significant costs. When auxiliary predictions of experimental outcomes are available from machine learning models, uncertain prediction quality precludes replacing human experiments entirely, yet these predictions may still contain useful signal. We propose a...

Ziyad Benomar, Aymen Al Marjani, Paul Missault et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Data-Driven Persona-Conditioned Agents for A/B Test Simulation

A simulation framework that predicts A/B test outcomes using LLM-powered agents conditioned on data-driven personas grounded in real user behavioral signals is proposed, demonstrating that data-driven personas are a viable path toward fast, low-cost experiment pre-screening.

Ziyad Benomar, Weronika Lajewska, Leonardo Perelli et al. · 1 citation

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