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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 11 of 11 1 Learning How to Translate North Korean through South Korean ... Kim, Hwichan; Moon, Sangwhan; Okazaki, Naoaki; Komachi, Mamoru. - : arXiv, 2022 Abstract: South and North Korea both use the Korean language. However, Korean NLP research has focused on South Korean only, and existing NLP systems of the Korean language, such as neural machine translation (NMT) models, cannot properly handle North Korean inputs. Training a model using North Korean data is the most straightforward approach to solving this problem, but there is insufficient data to train NMT models. In this study, we create data for North Korean NMT models using a comparable corpus. First, we manually create evaluation data for automatic alignment and machine translation. Then, we investigate automatic alignment methods suitable for North Korean. Finally, we verify that a model trained by North Korean bilingual data without human annotation can significantly boost North Korean translation accuracy compared to existing South Korean models in zero-shot settings. ... : 8 pages, 1 figures, 8 tables ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2201.11258 https://arxiv.org/abs/2201.11258 BASE Hide details 2 Joint Optimization of Tokenization and Downstream Model ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Hiraoka, Tatsuya; Keyaki, Atsushi. - : Underline Science Inc., 2021 BASE Show details 3 Multimodal pretraining unmasked: A meta-analysis and a unified framework of vision-and-language berts ... Bugliarello, Emanuele; Cotterell, Ryan; Okazaki, Naoaki. - : ETH Zurich, 2021 BASE Show details 4 Transformer-based Lexically Constrained Headline Generation ... Yamada, Kosuke; Hitomi, Yuta; Tamori, Hideaki. - : arXiv, 2021 BASE Show details 5 Multimodal pretraining unmasked: A meta-analysis and a unified framework of vision-and-language berts Okazaki, Naoaki; Bugliarello, Emanuele; Cotterell, Ryan... In: Transactions of the Association for Computational Linguistics, 9 (2021) BASE Show details 6 Transformer-based Lexically Constrained Headline Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Hitomi, Yuta; Inui, Kentaro. - : Underline Science Inc., 2021 BASE Show details 7 It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information ... Bugliarello, Emanuele; Mielke, Sabrina J.; Anastasopoulos, Antonios. - : ETH Zurich, 2020 BASE Show details 8 It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information Mielke, Sabrina J.; Okazaki, Naoaki; Anastasopoulos, Antonios... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 9 The mechanism of additive composition [<Journal>] Tian, Ran [Verfasser]; Okazaki, Naoaki [Sonstige]; Inui, Kentaro [Sonstige] DNB Subject Category Language Show details 10 Other Topics You May Also Agree or Disagree: Modeling Inter-Topic Preferences using Tweets and Matrix Factorization ... Sasaki, Akira; Hanawa, Kazuaki; Okazaki, Naoaki. - : arXiv, 2017 BASE Show details 11 A preference learning approach to sentence ordering for multi-document summarization Bollegala, Danushka; Okazaki, Naoaki; Ishizuka, Mitsuru In: Information sciences. - New York, NY : Elsevier Science Inc. 217 (2012), 78-95 OLC Linguistik Show details

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