SimulacraBench

A NeurIPS 2026 competition centered on probabilistic matrix completion of respondent $$\times$$ question grids drawn from UN humanitarian survey microdata that has never been publicly released. The organizing team at Stanford holds data under a data-use agreement with UNICEF, UNHCR, and the world bank; participants submit code that the organizers run against the data and report back per-track scores resulting from a proper scoring rule. This design yields (i) a clean, uncontaminated benchmark for evaluating AI systems as simulacra of human populations, (ii) a rigorous empirical probe of the intersection between private disclosure mechanisms and behavioural simulation and (iii) directly actionable results for UNICEF, UNHCR, and the World Bank in their survey-design and policy-modeling workflows. The underlying data---UNICEF's Faith \& Immunisation Survey, the UNHCR ERPIS instrument, and a World Bank job assessment---cover more than 40,000 respondents across 15 countries on socio-demographic, attitudinal, and behavioural items relevant to global health, climate, and forced-displacement policy.