Papers by Mayu Otani

2 papers
Attending Self-Attention: A Case Study of Visually Grounded Supervision in Vision-and-Language Transformers (2021.acl-srw)

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Challenge: a growing body of research has been focused on what attention heads learn during the pre-training of visual grounded language models.
Approach: They propose to use visual grounding to supervise attention directly to learn visual ground.
Outcome: The proposed method improves the performance of a state-of-the-art visual grounded language model on vision-and-language tasks.
iParaphrasing: Extracting Visually Grounded Paraphrases via an Image (C18-1)

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Challenge: iParaphrasing extracts visually grounded paraphrases, which are different phrasal expressions describing the same visual concept in an image.
Approach: They propose a task to extract visually grounded paraphrases from images . they propose to model the similarity between the extracted VGPs using existing methods .
Outcome: The proposed task extracts visually grounded paraphrases from images . the proposed method has the potential to improve multimodal language and image tasks .

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