Papers by Yutaro Omote
Transformer-based Approach for Predicting Chemical Compound Structures (2020.aacl-main)
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| Challenge: | Existing methods to predict chemical compound structures from their names are limited and use handcrafted rules. |
| Approach: | They propose a Transformer-based model that predicts SMILES strings from chemical compound names instead of handcrafted rules. |
| Outcome: | The proposed model achieves higher F-measures than the existing model and the existing one. |
Supervised Visual Attention for Multimodal Neural Machine Translation (2020.coling-main)
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| Challenge: | Existing studies show that a conventional visual attention mechanism trained in an unsupervised manner is not effective for multimodal neural machine translation. |
| Approach: | They propose a supervised visual attention mechanism for multimodal neural machine translation that captures the relationship between a word and an image region more precisely than a conventional visual attention system. |
| Outcome: | The proposed model improves on English-German and German-English translation tasks and English-Japanese and Japanese-English tasks using the Flickr30k Entities JP dataset. |