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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. - : arXiv, 2022 BASE Show 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; Inui, Kentaro. - : arXiv, 2017 Abstract: We present in this paper our approach for modeling inter-topic preferences of Twitter users: for example, those who agree with the Trans-Pacific Partnership (TPP) also agree with free trade. This kind of knowledge is useful not only for stance detection across multiple topics but also for various real-world applications including public opinion surveys, electoral predictions, electoral campaigns, and online debates. In order to extract users' preferences on Twitter, we design linguistic patterns in which people agree and disagree about specific topics (e.g., "A is completely wrong"). By applying these linguistic patterns to a collection of tweets, we extract statements agreeing and disagreeing with various topics. Inspired by previous work on item recommendation, we formalize the task of modeling inter-topic preferences as matrix factorization: representing users' preferences as a user-topic matrix and mapping both users and topics onto a latent feature space that abstracts the preferences. Our experimental ... : To appear in ACL2017 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1704.07986 https://dx.doi.org/10.48550/arxiv.1704.07986 BASE Hide 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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