Rakuten’s Participation in WAT 2022: Parallel Dataset Filtering by Leveraging Vocabulary Heterogeneity

no code implementations • WAT 2022 • Alberto Poncelas, Johanes Effendi, Ohnmar Htun, Sunil Yadav, Dongzhe Wang, Saurabh Jain

This paper introduces our neural machine translation system’s participation in the WAT 2022 shared translation task (team ID: sakura).

Machine Translation Translation

RakutenAI-7B: Extending Large Language Models for Japanese

no code implementations • 21 Mar 2024 • Rakuten Group, Aaron Levine, Connie Huang, Chenguang Wang, Eduardo Batista, Ewa Szymanska, Hongyi Ding, Hou Wei Chou, Jean-François Pessiot, Johanes Effendi, Justin Chiu, Kai Torben Ohlhus, Karan Chopra, Keiji Shinzato, Koji Murakami, Lee Xiong, Lei Chen, Maki Kubota, Maksim Tkachenko, Miroku Lee, Naoki Takahashi, Prathyusha Jwalapuram, Ryutaro Tatsushima, Saurabh Jain, Sunil Kumar Yadav, Ting Cai, Wei-Te Chen, Yandi Xia, Yuki Nakayama, Yutaka Higashiyama

We introduce RakutenAI-7B, a suite of Japanese-oriented large language models that achieve the best performance on the Japanese LM Harness benchmarks among the open 7B models.

Comparative Snippet Generation

1 code implementation • ECNLP (ACL) 2022 • Saurabh Jain, Yisong Miao, Min-Yen Kan

We model product reviews to generate comparative responses consisting of positive and negative experiences regarding the product.

Sentence

MRCBert: A Machine Reading ComprehensionApproach for Unsupervised Summarization

1 code implementation • 1 May 2021 • Saurabh Jain, Guokai Tang, Lim Sze Chi

We demonstrated our results on reviews of a product from the Electronics category in the Amazon Reviews dataset.

Decision Making Machine Reading Comprehension +1