Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ryosuke Kohita"'
Publikováno v:
Journal of Natural Language Processing. 29:1198-1232
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::087cdb8c1ec30fd187d6c486277a8e1c
https://doi.org/10.5715/jnlp.29.1198
https://doi.org/10.5715/jnlp.29.1198
Autor:
Ryosuke Kohita, Daiki Kimura, Asim Munawar, Michiaki Tatsubori, Akifumi Wachi, Subhajit Chaudhury
Publikováno v:
ACL/IJCNLP (Findings)
Scopus-Elsevier
Scopus-Elsevier
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a407b0c82c70d3aebbf793b1b986c9fa
https://doi.org/10.18653/v1/2021.findings-acl.187
https://doi.org/10.18653/v1/2021.findings-acl.187
Publikováno v:
EMNLP (1)
Humans can learn structural properties about a word from minimal experience, and deploy their learned syntactic representations uniformly in different grammatical contexts. We assess the ability of modern neural language models to reproduce this beha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c67cc309c387531ad068fbe5ff1b56a
http://arxiv.org/abs/2010.05725
http://arxiv.org/abs/2010.05725
Publikováno v:
ACL
We propose a methodology to construct a term dictionary for text analytics through an interactive process between a human and a machine, which helps the creation of flexible dictionaries with precise granularity required in typical text analysis. Thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81d5a2377dd60daf493b08a951ee56c2
https://doi.org/10.18653/v1/2020.acl-main.72
https://doi.org/10.18653/v1/2020.acl-main.72
Publikováno v:
EMNLP (1)
Unsupervised methods are promising for abstractive text summarization in that the parallel corpora is not required. However, their performance is still far from being satisfied, therefore research on promising solutions is on-going. In this paper, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::07cadb5d5f9e2c9ec5ec766a85560386
Publikováno v:
Proceedings of the Workshop on the Relevance of Linguistic Structure in Neural Architectures for NLP.
This paper demonstrates a neural parser implementation suitable for consistently head-final languages such as Japanese. Unlike the transition- and graph-based algorithms in most state-of-the-art parsers, our parser directly selects the head word of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b52322ce11a898c16a049e0d37513e7
https://doi.org/10.18653/v1/w18-2906
https://doi.org/10.18653/v1/w18-2906
Multilingual Back-and-Forth Conversion between Content and Function Head for Easy Dependency Parsing
Publikováno v:
EACL (2)
Universal Dependencies (UD) is becoming a standard annotation scheme cross-linguistically, but it is argued that this scheme centering on content words is harder to parse than the conventional one centering on function words. To improve the parsabili
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c20564c4d99a926265a73d97591390a
https://doi.org/10.18653/v1/e17-2001
https://doi.org/10.18653/v1/e17-2001
Autor:
Daiki Kimura, Michiaki Tatsubori, Subhajit Chaudhury, Alexander G. Gray, Ryosuke Kohita, Akifumi Wachi, Don Joven Agravante, Asim Munawar, Masaki Ono
Publikováno v:
Scopus-Elsevier
We present Logical Optimal Actions (LOA), an action decision architecture of reinforcement learning applications with a neuro-symbolic framework which is a combination of neural network and symbolic knowledge acquisition approach for natural language
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::428cf6995847bc1fb34bdde06108eb43
http://www.scopus.com/inward/record.url?eid=2-s2.0-85118932769&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85118932769&partnerID=MN8TOARS