Christopher Rodriguez

Patricia Paskov, Christopher Rodriguez, Sunishchal Dev et al.

Open-weight AI models (OWMs), or models released with publicly-available weights, are distributing rapidly and approaching the performance levels of leading closed-weight AI models (CWMs). While OWMs offer substantial scientific and economic benefits, their release introduces distinct risk factors for which existing evaluation practices, largely designed for CWM deployment, fail to account. In this paper, we argue that these risk factors demand distinct proportional evaluation (PE) approaches: evaluating without system-level safeguards (PE1), assessing robustness to modifications that undo model-level safeguards (PE2), testing selective capability amplification (PE3), and proxying worst-case misuse (PE4). We systematically review current evaluation practices of OWMs released in 2025 through April 2026, finding that only one of the 37 families of models reviewed fulfills PE1-4 and most do not fulfill any. This paper targets policymakers, funders, and researchers involved in AI evaluation. As OWMs grow increasingly capable, their evaluation warrants close attention from developers, funders, and governance bodies alike.

Martin Capdevila, Esteban Villa Turek, Ellen Karina Chumbe Fernandez et al.

Large language models are, by definition, based on language. In an effort to underscore the critical need for regional localized models, this paper examines primary differences between variants of written Spanish across Latin America and Spain, with an in-depth sociocultural and linguistic contextualization therein. We argue that these differences effectively constitute significant gaps in the quotidian use of Spanish among dialectal groups by creating sociolinguistic dissonances, to the extent that locale-sensitive AI models would play a pivotal role in bridging these divides. In doing so, this approach informs better and more efficient localization strategies that also serve to more adequately meet inclusivity goals, while securing sustainable active daily user growth in a major low-risk investment geographic area. Therefore, implementing at least the proposed five sub variants of Spanish addresses two lines of action: to foment user trust and reliance on AI language models while also demonstrating a level of cultural, historical, and sociolinguistic awareness that reflects positively on any internationalization strategy.