Papers by Hideaki Tamori
Transformer-based Lexically Constrained Headline Generation (2021.emnlp-main)
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Kosuke Yamada, Yuta Hitomi, Hideaki Tamori, Ryohei Sasano, Naoaki Okazaki, Kentaro Inui, Koichi Takeda
| Challenge: | Existing automatic headline generation methods cannot include a given phrase in the generated headline. |
| Approach: | They propose a Transformer-based method that guarantees to include a given phrase in a generated headline. |
| Outcome: | The proposed method achieves ROUGE scores comparable to previous methods with Japanese news corpus. |
A Japanese News Simplification Corpus with Faithfulness (2024.lrec-main)
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| Challenge: | Existing simplified corpora lack faithfulness to original text, resulting in errors in translation. |
| Approach: | They propose to simplify Japanese newspaper articles to prioritize faithfulness over automated models. |
| Outcome: | The proposed corpus preserves the original text, surpassing existing corpora. |