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Fauzan Farooqui

2 accepted papers

2025

CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation

EMNLP 2025

Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey sufficient context to capture region-specific meanings. In this work, we investigate whether images can act as cultural

2024

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

NeurIPS 2024oral

Visual Question Answering~(VQA) is an important task in multimodal AI, which requires models to understand and reason on knowledge present in visual and textual data. However, most of the current VQA datasets and models are primarily focused on English and a few major world languages, with images th…

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