1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89
Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…
Can Multimodal LLMs do Visual Temporal Understanding and Reasoning? The answer is No!
Mohamed Fazli Imam, Chenyang Lyu, Alham Fikri Aji
Multimodal Large Language Models (MLLMs) have achieved significant advancements in tasks like Visual Question Answering (VQA) by leveraging foundational Large Language Models (LLMs…
CLIP meets DINO for Tuning Zero-Shot Classifier using Unlabeled Image Collections
Mohamed Fazli Imam, Rufael Fedaku Marew, Jameel Hassan +3
In the era of foundation models, CLIP has emerged as a powerful tool for aligning text & visual modalities into a common embedding space. However, the alignment objective used to t…
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…