Excited to share that we have committed our paper “Vision-Language Models are Confused Tourists” to #CVPR2026 (Findings)! 🇺🇸🏔 Arxiv: arxiv.org/abs/2511.17004 We question whether current SOTA VLMs remain robust in simple cultural grounding QA when distracting contextual objects are present For example, if you eat chicken schnitzel with Mt. Fuji in the background, will the model fail to recognize it as Japanese katsu? ConfusedTourists introduces: 👉 5k+ evaluation samples across 3 cultural item categories, comprising 243 unique cultural items from 57 countries and 11 sub-regions 🌍 👉 Evaluation of 14 VLMs across 12 data features 🤖 👉 Findings showing that simple concept mixing can cause up to a -40% drop in perform 📉 Special thanks to my co-authors @IkhlasulHanif0 , @emthehunt, @gentaiscool, @FajriKoto, and my advisor @AlhamFikri for the valuable contributions along the way! #multimodal #vlm #multicultural #robustness #evaluation #NLProc #ComputerVision
