2 citations · 9 across the 34 of their papers we have counts for
4 papers · 2 filters
World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models
Eunsu Kim, Junyeong Park, Na Min An +9
In a globalized world, cultural elements from diverse origins frequently appear together within a single visual scene. We refer to these as culture mixing scenarios, yet how Large…
PCRI: Measuring Context Robustness in Multimodal Models for Enterprise Applications
Hitesh Laxmichand Patel, Amit Agarwal, Srikant Panda +6
The reliability of Multimodal Large Language Models (MLLMs) in real-world settings is often undermined by sensitivity to irrelevant or distracting visual context, an aspect not cap…
RCI: A Score for Evaluating Global and Local Reasoning in Multimodal Benchmarks
Amit Agarwal, Hitesh Laxmichand Patel, Srikant Panda +7
Multimodal Large Language Models (MLLMs) have achieved impressive results on vision-language benchmarks, yet it remains unclear whether these benchmarks assess genuine global reaso…
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…