Sennay Ghebreab — accepted AI-conference papers

2026

Same Content, Different Answers: Cross-Modal Inconsistency in MLLMs

Angela van Sprang, Laurens Samson, Ana Lucic, Erman Acar, Sennay Ghebreab, Yuki M. Asano

CVPR 2026

We introduce two new benchmarks REST and REST+ (Render-Equivalence Stress Tests) to enable systematic evaluation of cross-modal inconsistency in multimodal large language models (MLLMs). MLLMs are trained to represent vision and language in the same embedding space, yet they cannot perform the same

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2025

EMPLACE: Self-Supervised Urban Scene Change Detection

Tim Alpherts, Sennay Ghebreab, Nanne van Noord

AAAI 2025technical

Urban change is a constant process that influences the perception of neighbourhoods and the lives of the people within them. The field of Urban Scene Change Detection (USCD) aims to capture changes in street scenes using computer vision and can help raise awareness of changes that make it possible t…

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