1 code implementation • EMNLP (ACL) 2021 • Shunyo Kawamoto, Yu Sawai, Kohei Wakimoto, Peinan Zhang
Working with a wide range of annotators with the same attributes is crucial, as in real-world applications.
no code implementations • 8 Mar 2024 • Sho Hoshino, Akihiko Kato, Soichiro Murakami, Peinan Zhang
Rather, we find a superiority of the Wikipedia domain over the NLI domain for these languages, in contrast to prior studies that focused on NLI as training data.
1 code implementation • 10 Jan 2024 • Yuu Jinnai, Ukyo Honda, Tetsuro Morimura, Peinan Zhang
We propose two variants of MBR, Diverse MBR (DMBR) and $k$-medoids MBR (KMBR), methods to generate a set of sentences with high quality and diversity.
1 code implementation • 21 Sep 2023 • Masato Mita, Soichiro Murakami, Akihiko Kato, Peinan Zhang
In response to the limitations of manual online ad production, significant research has been conducted in the field of automatic ad text generation (ATG).
no code implementations • 22 Jun 2023 • Soichiro Murakami, Sho Hoshino, Peinan Zhang
Natural language generation methods have emerged as effective tools to help advertisers increase the number of online advertisements they produce.
no code implementations • 2 Jun 2022 • Tetsuro Morimura, Kazuhiro Ota, Kenshi Abe, Peinan Zhang
However, since the standard MCTS does not have the ability to learn state representation, the size of the tree-search space can be too large to search.
no code implementations • NAACL (ACL) 2022 • Soichiro Murakami, Peinan Zhang, Sho Hoshino, Hidetaka Kamigaito, Hiroya Takamura, Manabu Okumura
Writing an ad text that attracts people and persuades them to click or act is essential for the success of search engine advertising.
no code implementations • NAACL 2021 • Hidetaka Kamigaito, Peinan Zhang, Hiroya Takamura, Manabu Okumura
Although there are many studies on neural language generation (NLG), few trials are put into the real world, especially in the advertising domain.