Brief

Researchers have introduced Diversity-driven Offline Multi-Objective Optimization (DOMOO), a novel approach to tackle complex problems with multiple objectives when only a fixed dataset is available. DOMOO addresses the out-of-distribution issue common in offline optimization by incorporating a risk control module to estimate and mitigate potential errors in candidate solutions. Additionally, a nested Pareto set learning strategy is employed to adapt to various Pareto front geometries, enhancing solution quality and diversity. AI

A new paper evaluates the performance of commercial and open-source large language models on Arabic Islamic inheritance reasoning tasks. The study found that commercial models generally outperform open-source models, showing greater reliability in identifying heirs, applying exclusion rules, and maintaining consistency. Gemini 2.5 Flash achieved the best performance among the evaluated models, with a Mean Reciprocal Error (MRE) of 0.989. AI