Master's course student at NAIST (Matsumoto Lab).
I'm interested in NLP and Deep Learning.
Especially skilled in Chainer, python based deep learning frameworks.
- Natural Language Processing (NLP)
- QA, Dialog Systems
- Word Segmentation, Named Entity Recognition
Motoki Sato, Hiroyuki Shindo, Ikuya Yamada, Yuji Matsumoto, "Segment-Level Neural Conditional Random Fields for Named Entity Recognition", IJCNLP 2017 (Short Paper) [Paper]
Motoki Sato, Hitoshi Manabe, Hiroshi Noji, Yuji Matsumoto, "Adversarial Training for Cross-Domain Universal Dependency Parsing", CoNLL 2017, (Ranked 6th in the Shared Task) [Paper] [Poster]
Ayaka Morimoto, Daiki Kubo, Motoki Sato, Hiroyuki Shindo and Yuji Matsumoto, "Legal Question Answering System using Neural Attention", COLIEE 2017. [paper]
Motoki Sato, Austin J. Brockmeier, Georgios Kontonatsios, Tingting Mu, John Y. Goulermas, Jun'ichi Tsujii and Sophia Ananiadou, "Distributed Document and Phrase Co-embeddings for Descriptive Clustering", EACL 2017 (Long Paper) [Paper] [bib]
Ikuya Yamada, Motoki Sato, Hiroyuki Shindo: "Ensemble of Neural Classifiers for Scoring Knowledge Base Triples", WSDM Cup 2017 (Ranked 2nd in the competition) [News] [Paper]
Motoki Sato, Takayuki Ito, "Text Filtering for Harmful Document Classification Method Based on Paragraph Vector and Multi Layer Perceptron" (Japanese Paper), IPSJ 2015 [Student Award]
- Machine Learning (Python)
- Web Applications (PHP, Ruby, MySQL, CSS, HTML)
- iOS Applications (Objective-C)
M.S. – Nara Institute of Science and Technology, April 2016 - March 2018.
B.S. – Nagoya Institute of Technology, April 2011 - March 2015.