Papers by Jan-Martin Steitz

1 papers
xGQA: Cross-Lingual Visual Question Answering (2022.findings-acl)

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Challenge: a lack of multilingual multimodal datasets has hindered multimodal vision and language modeling efforts.
Approach: They propose a multilingual evaluation benchmark for the visual question answering task . they extend the established English GQA dataset to 7 typologically diverse languages .
Outcome: The proposed methods outperform current state-of-the-art models in zero-shot cross-lingual settings, but the accuracy remains low across languages.

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