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cs.AI2026
Data-Driven Personas for Survey Simulation: Insights into Simulation Alignment Across Data-Access Regimes
Dongryeol Lee, Weronika Łajewska, Leonardo Perelli +1
Large language models (LLMs) offer new opportunities for public opinion research by enabling early prediction of survey responses, potentially reducing the cost and time of traditi…
cs.AI2026
Data-Driven Persona-Conditioned Agents for A/B Test Simulation
Ziyad Benomar, Weronika Łajewska, Leonardo Perelli +1
A/B testing is the gold standard for evaluating product changes, but each experiment requires real user traffic, engineering effort, and weeks of measurement. We propose a simulati…
cs.AI2026
The Illusion of AI Expertise Under Uncertainty: A Probabilistic Paradigm to Interpret Results Under Ground Truth Variation
Aparna Elangovan, Lei Xu, Mahsa Elyasi +8
Benchmarking the capabilities of AI systems, including Large Language Models (LLMs) and Vision Models, typically ignores the impact of uncertainty in the underlying ground truth an…