Topic: benchmarks

Supports multilingual and culturally contextual evaluation of AI systems, including benchmarks and datasets for underrepresented languages and contexts, with attention to the Global South. Proposals may develop responsible evaluation infrastructure, human judgment in evaluation, and methods for assessing AI deployment in emerging markets. Use the ARA proposal template; four pages excluding appendices are encouraged. Decisions are expected in February 2027. Applications close on 4 November 2026 at 11:59pm Pacific Time.

This half-day workshop debates when explicit predictive models improve robot learning and when end-to-end policies or hybrid systems are preferable. Six debate motions examine generalization, counterfactual reasoning, data efficiency, evaluation, deployment costs and the limits of current benchmarks. Invited talks, contributed spotlights and posters connect theory to empirical comparisons, including negative results. Confirmed speakers include Chelsea Finn, Yunzhu Li, Georgia Chalvatzaki and Vincent Sitzmann. Paper submissions closed on 12 October; camera-ready papers are due on 6 November and