Papers by Takuya Narihira

1 papers
Transformer-Exclusive Cross-Modal Representation for Vision and Language (2021.findings-acl)

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Challenge: a number of approaches to crossmodal representation have been used, but transformer architecture has taken over the recurrent neural networks in natural language processing tasks.
Approach: They propose to use transformer architecture to handle cross-modal representations for vision and language with compatible performance to convolutional neural networks.
Outcome: The proposed model outperforms recurrent neural networks in vision and language representations with transformer architecture.

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