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cs.CV2025
BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language Models
Bryan Chen Zhengyu Tan, Zheng Weihua, Zhengyuan Liu +4
As vision-language models (VLMs) are deployed globally, their ability to understand culturally situated knowledge becomes essential. Yet, existing evaluations largely assess static…
cs.CV2025
Humor in Pixels: Benchmarking Large Multimodal Models Understanding of Online Comics
Yuriel Ryan, Rui Yang Tan, Kenny Tsu Wei Choo +1
Understanding humor is a core aspect of social intelligence, yet it remains a significant challenge for Large Multimodal Models (LMMs). We introduce PixelHumor, a benchmark dataset…