1 code implementation • ACL 2021 • Jong-Hoon Oh, Ryu Iida, Julien Kloetzer, Kentaro Torisawa
We show that on the GLUE tasks, the combination of our pretrained CNN with ALBERT outperforms the original ALBERT and achieves a similar performance to that of SOTA.
no code implementations • 30 Mar 2021 • Masahiro Tanaka, Kenjiro Taura, Toshihiro Hanawa, Kentaro Torisawa
RaNNC also achieved better training throughputs than GPipe on both the enlarged BERT model pre-training (GPipe with hybrid parallelism) and the enlarged ResNet models (GPipe with model parallelism) in all of the settings we tried.
no code implementations • LREC 2020 • Yoshihiko Asao, Julien Kloetzer, Junta Mizuno, Dai Saiki, Kazuma Kadowaki, Kentaro Torisawa
A dialog system that can monitor the health status of seniors has a huge potential for solving the labor force shortage in the caregiving industry in aging societies.
no code implementations • IJCNLP 2019 • Kazuma Kadowaki, Ryu Iida, Kentaro Torisawa, Jong-Hoon Oh, Julien Kloetzer
Furthermore, we investigate the effect of supplying background knowledge to our classifiers.
no code implementations • ACL 2019 • Jong-Hoon Oh, Kazuma Kadowaki, Julien Kloetzer, Ryu Iida, Kentaro Torisawa
In this paper, we propose a method for why-question answering (why-QA) that uses an adversarial learning framework.
no code implementations • COLING 2016 • Junta Mizuno, Masahiro Tanaka, Kiyonori Ohtake, Jong-Hoon Oh, Julien Kloetzer, Chikara Hashimoto, Kentaro Torisawa
We demonstrate our large-scale NLP systems: WISDOM X, DISAANA, and D-SUMM.
no code implementations • WS 2016 • Kentaro Torisawa
D-SUMM automatically summarizes a large number of disaster related reports concerning a specified area and helps rescue workers to understand disaster situations from a macro perspective.