no code implementations • 27 Aug 2020 • Takeshi Onishi
Constructing a machine that understands human language is one of the most elusive and long-standing challenges in artificial intelligence.
no code implementations • 17 Jan 2019 • Chuan Wang, Takeshi Onishi, Keiichi Nemoto, Kwan-Liu Ma
Deep Recurrent Neural Network (RNN) has gained popularity in many sequence classification tasks.
no code implementations • WS 2018 • Takeshi Onishi, Davy Weissenbacher, Ari Klein, Karen O{'}Connor, Gonzalez-Hern, Graciela ez
Through a semi-automatic analysis of tweets, we show that Twitter users not only express Medication Non-Adherence (MNA) in social media but also their reasons for not complying; further research is necessary to fully extract automatically and analyze this information, in order to facilitate the use of this data in epidemiological studies.
no code implementations • WS 2017 • Hai Wang, Takeshi Onishi, Kevin Gimpel, David Mcallester
A significant number of neural architectures for reading comprehension have recently been developed and evaluated on large cloze-style datasets.
no code implementations • EMNLP 2016 • Takeshi Onishi, Hai Wang, Mohit Bansal, Kevin Gimpel, David Mcallester
We have constructed a new "Who-did-What" dataset of over 200, 000 fill-in-the-gap (cloze) multiple choice reading comprehension problems constructed from the LDC English Gigaword newswire corpus.