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Hidetaka Kamigaito
Hidetaka Kamigaito
Nara Institute of Science and Technology (NAIST)
Verified email at lr.pi.titech.ac.jp - Homepage
Title
Cited by
Cited by
Year
Top-down RST parsing utilizing granularity levels in documents
N Kobayashi, T Hirao, H Kamigaito, M Okumura, M Nagata
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8099-8106, 2020
332020
Supervised attention for sequence-to-sequence constituency parsing
H Kamigaito, K Hayashi, T Hirao, H Takamura, M Okumura, M Nagata
Proceedings of the Eighth International Joint Conference on Natural Language …, 2017
232017
Higher-order Syntactic Attention Network for Long Sentence Compression
H Kamigaito, K Hayashi, T Hirao, M Nagata
Proceedings of the 2018 Conference of the North American Chapter of the …, 2018
222018
Towards table-to-text generation with numerical reasoning
LH Suadaa, H Kamigaito, K Funakoshi, M Okumura, H Takamura
Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021
182021
An empirical study of building a strong baseline for constituency parsing
J Suzuki, S Takase, H Kamigaito, M Morishita, M Nagata
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
162018
Split or merge: Which is better for unsupervised RST parsing?
N Kobayashi, T Hirao, K Nakamura, H Kamigaito, M Okumura, M Nagata
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
152019
Similarity search for office XML documents based on style and structure data
Y Watanabe, H Kamigaito, H Yokota
International Journal of Web Information Systems, 2013
14*2013
Syntactically look-ahead attention network for sentence compression
H Kamigaito, M Okumura
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8050-8057, 2020
132020
SODA: Story oriented dense video captioning evaluation framework
S Fujita, T Hirao, H Kamigaito, M Okumura, M Nagata
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
112020
Improving neural RST parsing model with silver agreement subtrees
N Kobayashi, T Hirao, H Kamigaito, M Okumura, M Nagata
Proceedings of the 2021 Conference of the North American Chapter of the …, 2021
102021
Generating weather comments from meteorological simulations
S Murakami, S Tanaka, M Hangyo, H Kamigaito, K Funakoshi, ...
Proceedings of the 16th Conference of the European Chapter of the …, 2021
92021
Automatic pyramid evaluation exploiting EDU-based extractive reference summaries
T Hirao, H Kamigaito, M Nagata
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
92018
Discourse-aware hierarchical attention network for extractive single-document summarization
T Ishigaki, H Kamigaito, H Takamura, M Okumura
Proceedings of the International Conference on Recent Advances in Natural …, 2019
82019
Unsupervised word alignment using frequency constraint in posterior regularized EM
H Kamigaito, T Watanabe, H Takamura, M Okumura, E Sumita
Journal of Natural Language Processing 23 (4), 327-351, 2016
82016
Unsupervised word alignment using frequency constraint in posterior regularized EM
H Kamigaito, T Watanabe, H Takamura, M Okumura, E Sumita
Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014
82014
An empirical study of generating texts for search engine advertising
H Kamigaito, P Zhang, H Takamura, M Okumura
Proceedings of the 2021 Conference of the North American Chapter of the …, 2021
72021
Fusing label embedding into bert: An efficient improvement for text classification
Y Xiong, Y Feng, H Wu, H Kamigaito, M Okumura
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 …, 2021
62021
Considering nested tree structure in sentence extractive summarization with pre-trained transformer
J Kwon, N Kobayashi, H Kamigaito, M Okumura
Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021
52021
Abstractive document summarization with word embedding reconstruction
J You, C Hu, H Kamigaito, H Takamura, M Okumura
Proceedings of the International Conference on Recent Advances in Natural …, 2021
52021
Unified interpretation of softmax cross-entropy and negative sampling: With case study for knowledge graph embedding
H Kamigaito, K Hayashi
arXiv preprint arXiv:2106.07250, 2021
42021
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Articles 1–20