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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 Signed Coreference Resolution ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Yin, Kayo. - : Underline Science Inc., 2021 BASE Show details 2 Including Signed Languages in Natural Language Processing ... Yin, Kayo; Moryossef, Amit; Hochgesang, Julie. - : arXiv, 2021 BASE Show details 3 Including Signed Languages in Natural Language Processing ... 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; Alikhani, Malihe; Goldberg, Yoav. - : Underline Science Inc., 2021 BASE Show details 4 When Does Translation Require Context? A Data-driven, Multilingual Exploration ... Yin, Kayo; Fernandes, Patrick; Martins, André F. T.; Neubig, Graham. - : arXiv, 2021 Abstract: Although proper handling of discourse phenomena significantly contributes to the quality of machine translation (MT), common translation quality metrics do not adequately capture them. Recent works in context-aware MT attempt to target a small set of these phenomena during evaluation. In this paper, we propose a new metric, P-CXMI, which allows us to identify translations that require context systematically and confirm the difficulty of previously studied phenomena as well as uncover new ones that have not been addressed in previous work. We then develop the Multilingual Discourse-Aware (MuDA) benchmark, a series of taggers for these phenomena in 14 different language pairs, which we use to evaluate context-aware MT. We find that state-of-the-art context-aware MT models find marginal improvements over context-agnostic models on our benchmark, which suggests current models do not handle these ambiguities effectively. We release code and data to invite the MT research community to increase efforts on ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.2109.07446 https://arxiv.org/abs/2109.07446 BASE Hide details 5 Measuring and Increasing Context Usage in Context-Aware Machine Translation ... 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; Fernandes, Patrick; Martins, Andre. - : Underline Science Inc., 2021 BASE Show details 6 Data Augmentation for Sign Language Gloss Translation ... Moryossef, Amit; Yin, Kayo; Neubig, Graham. - : arXiv, 2021 BASE Show details 7 Do Context-Aware Translation Models Pay the Right Attention? ... Yin, Kayo; Fernandes, Patrick; Pruthi, Danish. - : arXiv, 2021 BASE Show details 8 When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection ... Chaudhary, Aditi; Yin, Kayo; Anastasopoulos, Antonios. - : arXiv, 2021 BASE Show details 9 When is Wall a Pared and when a Muro?: Extracting Rules Governing Lexical Selection ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Anastasopoulos, Antonios; Chaudhary, Aditi. - : Underline Science Inc., 2021 BASE Show details 10 Do Context-Aware Translation Models Pay the Right Attention? ... 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; Chaudhary, Aditi; Fernandes, Patrick. - : Underline Science Inc., 2021 BASE Show details 11 Better Sign Language Translation with STMC-Transformer ... Yin, Kayo; Read, Jesse. - : arXiv, 2020 BASE Show details

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