xGQA: Cross-Lingual Visual Question Answering
Recent advances in multimodal vision and language modeling have predominantly focused on the English language, mostly due to the lack of multilingual multimodal datasets to steer modeling efforts. In this work, we address this gap and provide xGQA, a new multilingual evaluation benchmark for the visual question answering task. We extend the established English GQA dataset to 7 typologically diverse languages, enabling us to detect and explore crucial challenges in cross-lingual visual question answering. We further propose new adapter-based approaches to adapt multimodal transformer-based models to become multilingual, and -- vice versa -- multilingual models to become multimodal. Our proposed methods outperform current state-of-the-art multilingual multimodal models (e.g., M3P) in zero-shot cross-lingual settings, but the accuracy remains low across the board; a performance drop of around 38 accuracy points in target languages showcases the difficulty of zero-shot cross-lingual transfer for this task. Our results suggest that simple cross-lingual transfer of multimodal models yields latent multilingual multimodal misalignment, calling for more sophisticated methods for vision and multilingual language modeling.
Code (1)
Tasks
Cross-Lingual TransferLanguage ModelingLanguage ModellingQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)Zero-Shot Cross-Lingual TransferSimilar Papers 제목 키워드 기반
xGQA: Cross-Lingual Visual Question Answering
Recent advances in multimodal vision and language modeling have predominantly focused on the English language, mostly due to the lack of multilingual multimodal datasets to steer modeling efforts. In this work, we addres…
Cross-Lingual TransferLanguage ModelingLanguage ModellingQuestion Answering+3Improving the Cross-Lingual Generalisation in Visual Question Answering
While several benefits were realized for multilingual vision-language pretrained models, recent benchmarks across various tasks and languages showed poor cross-lingual generalisation when multilingually pre-trained visio…
Cross-Lingual TransferQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)+1MaXM: Towards Multilingual Visual Question Answering
Visual Question Answering (VQA) has been primarily studied through the lens of the English language. Yet, tackling VQA in other languages in the same manner would require a considerable amount of resources. In this paper…
Question AnsweringTranslationVisual Question AnsweringVisual Question Answering (VQA)Worldly Wise (WoW) - Cross-Lingual Knowledge Fusion for Fact-based Visual Spoken-Question Answering
Although Question-Answering has long been of research interest, its accessibility to users through a speech interface and its support to multiple languages have not been addressed in prior studies. Towards these ends, we…
Knowledge GraphsQuestion AnsweringSpeech-to-TextSpoken Language Understanding+1Visual Question Answering Dataset for Bilingual Image Understanding: A Study of Cross-Lingual Transfer Using Attention Maps
Visual question answering (VQA) is a challenging task that requires a computer system to understand both a question and an image. While there is much research on VQA in English, there is a lack of datasets for other lang…
Cross-Lingual TransferImage CaptioningQuestion AnsweringVisual Question Answering+1