| Dependency tree-based sentiment classification using CRFs with hidden variables T Nakagawa, K Inui, S Kurohashi Human Language Technologies: The 2010 Annual Conference of the North …, 2010 | 489 | 2010 |
| Collecting evaluative expressions for opinion extraction N Kobayashi, K Inui, Y Matsumoto, K Tateishi, T Fukushima International Conference on Natural Language Processing, 596-605, 2004 | 395 | 2004 |
| Attention is not only a weight: Analyzing transformers with vector norms G Kobayashi, T Kuribayashi, S Yokoi, K Inui arXiv preprint arXiv:2004.10102, 2020 | 303 | 2020 |
| Extracting aspect-evaluation and aspect-of relations in opinion mining N Kobayashi, K Inui, Y Matsumoto Proceedings of the 2007 Joint Conference on Empirical Methods in Natural …, 2007 | 262 | 2007 |
| Emotion classification using massive examples extracted from the web R Tokuhisa, K Inui, Y Matsumoto Proceedings of the 22nd International Conference on Computational …, 2008 | 244 | 2008 |
| Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP) K Inui, J Jiang, V Ng, X Wan Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 241 | 2019 |
| Realtime qa: What's the answer right now? J Kasai, K Sakaguchi, R Le Bras, A Asai, X Yu, D Radev, NA Smith, ... Advances in neural information processing systems 36, 49025-49043, 2023 | 228 | 2023 |
| Text simplification for reading assistance: a project note K Inui, A Fujita, T Takahashi, R Iida, T Iwakura Proceedings of the second international workshop on Paraphrasing, 9-16, 2003 | 227 | 2003 |
| Selective sampling for example-based word sense disambiguation A Fujii, K Inui, T Tokunaga, H Tanaka Computational linguistics 24 (4), 573-597, 1998 | 206 | 1998 |
| Encoder-decoder models can benefit from pre-trained masked language models in grammatical error correction M Kaneko, M Mita, S Kiyono, J Suzuki, K Inui arXiv preprint arXiv:2005.00987, 2020 | 198 | 2020 |
| An empirical study of incorporating pseudo data into grammatical error correction S Kiyono, J Suzuki, M Mita, T Mizumoto, K Inui arXiv preprint arXiv:1909.00502, 2019 | 197 | 2019 |
| Taking sides: User classification for informal online political discourse R Malouf, T Mullen Internet Research 18 (2), 177-190, 2008 | 179 | 2008 |
| Language models as knowledge bases: On entity representations, storage capacity, and paraphrased queries B Heinzerling, K Inui Proceedings of the 16th conference of the european chapter of the …, 2021 | 174 | 2021 |
| 意見抽出のための評価表現の収集 小林のぞみ， 乾健太郎， 松本裕治， 立石健二， 福島俊一 自然言語処理 12 (3), 203-222, 2005 | 171 | 2005 |
| Neural architectures for fine-grained entity type classification S Shimaoka, P Stenetorp, K Inui, S Riedel Proceedings of the 15th conference of the european chapter of the …, 2017 | 159 | 2017 |
| What makes reading comprehension questions easier? S Sugawara, K Inui, S Sekine, A Aizawa arXiv preprint arXiv:1808.09384, 2018 | 147 | 2018 |
| Annotating a Japanese text corpus with predicate-argument and coreference relations R Iida, M Komachi, K Inui, Y Matsumoto Proceedings of the linguistic annotation workshop, 132-139, 2007 | 146 | 2007 |
| Experience mining: Building a large-scale database of personal experiences and opinions from web documents K Inui, S Abe, K Hara, H Morita, C Sao, M Eguchi, A Sumida, K Murakami, ... 2008 IEEE/WIC/ACM International Conference on Web Intelligence and …, 2008 | 111 | 2008 |
| Incorporating contextual cues in trainable models for coreference resolution R Iida, K Inui, H Takamura, Y Matsumoto Proceedings of the EACL Workshop on the Computational Treatment of Anaphora …, 2003 | 109 | 2003 |
| Can neural networks understand monotonicity reasoning? H Yanaka, K Mineshima, D Bekki, K Inui, S Sekine, L Abzianidze, J Bos arXiv preprint arXiv:1906.06448, 2019 | 106 | 2019 |
Yuji MatsumotoTeam Leader, RIKEN Center for Advanced Intelligence ProjectVerified email at is.naist.jp
