Papers with MaXM
MaXM: Towards Multilingual Visual Question Answering (2023.findings-emnlp)
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Soravit Changpinyo, Linting Xue, Michal Yarom, Ashish Thapliyal, Idan Szpektor, Julien Amelot, Xi Chen, Radu Soricut
| Challenge: | Visual Question Answering (VQA) has been studied in the English language, but in other languages it would require a considerable amount of resources. |
| Approach: | They propose scalable solutions to multilingual visual question answering using an English language framework and an annotation protocol. |
| Outcome: | The proposed framework reduces human annotation efforts and creates a test-only VQA benchmark in 7 languages. |