Multimodal foundation models (MFMs) like GPT-4o, Gemini, and Claude have shown rapid progress recently, especially in public demos. While their language skills are well studied, their true ability to understand visual information remains unclear. Most benchmarks used today focus heavily on text-based tasks, such as VQA or classification, which often reflect language strengths more than…

Contrastive Language-Image Pre-training (CLIP) has become important for modern vision and multimodal models, enabling applications such as zero-shot image classification and serving as vision encoders in MLLMs. However, most CLIP variants, including Meta CLIP, are limited to English-only data curation, ignoring a significant amount of non-English content from the worldwide web. Scaling CLIP to include…