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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 Page: 1 2 Hits 1 – 20 of 24 1 Can Synthetic Translations Improve Bitext Quality? ... Briakou, Eleftheria; Carpuat, Marine. - : arXiv, 2022 BASE Show details 2 Rule-based Morphological Inflection Improves Neural Terminology Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Carpuat, Marine; Xu, Weijia. - : Underline Science Inc., 2021 BASE Show details 3 Rule-based Morphological Inflection Improves Neural Terminology Translation ... Xu, Weijia; Carpuat, Marine. - : arXiv, 2021 BASE Show details 4 Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer ... Briakou, Eleftheria; Agrawal, Sweta; Tetreault, Joel. - : arXiv, 2021 BASE Show details 5 Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural 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; Briakou, Eleftheria; Carpuat, Marine. - : Underline Science Inc., 2021 BASE Show details 6 The UMD Submission to the Explainable MT Quality Estimation Shared Task: Combining Explanation Models with Sequence Labeling ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Carpuat, Marine; Kabir, Tasnim. - : Underline Science Inc., 2021 BASE Show details 7 Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Joel; Agrawal, Sweta. - : Underline Science Inc., 2021 BASE Show details 8 How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation? ... Xu, Weijia; Ma, Shuming; Zhang, Dongdong. - : arXiv, 2021 BASE Show details 9 EDITOR: an Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints ... 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; Carpuat, Marine; Xu, Weijia. - : Underline Science Inc., 2021 BASE Show details 10 A Non-Autoregressive Edit-Based Approach to Controllable Text Simplification ... 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; Agrawal, Sweta; Carpuat, Marine. - : Underline Science Inc., 2021 BASE Show details 11 Detecting Fine-Grained Cross-Lingual Semantic Divergences without Supervision by Learning to Rank ... Briakou, Eleftheria; Carpuat, Marine. - : arXiv, 2020 BASE Show details 12 Incorporating Terminology Constraints in Automatic Post-Editing ... Wan, David; Kedzie, Chris; Ladhak, Faisal. - : arXiv, 2020 BASE Show details 13 EDITOR: an Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints ... Xu, Weijia; Carpuat, Marine. - : arXiv, 2020 BASE Show details 14 Controlling Neural Machine Translation Formality with Synthetic Supervision ... Niu, Xing; Carpuat, Marine. - : arXiv, 2019 BASE Show details 15 Controlling Text Complexity in Neural Machine Translation ... Agrawal, Sweta; Carpuat, Marine. - : arXiv, 2019 BASE Show details 16 Identifying Semantic Divergences Across Languages Vyas, Yogarshi. - 2019 BASE Show details 17 Formality Style Transfer Within and Across Languages with Limited Supervision Niu, Xing. - 2019 Abstract: While much natural language processing work focuses on analyzing language content, language style also conveys important information about the situational context and purpose of communication. When editing an article, professional editors take into account the target audience to select appropriate word choice and grammar. Similarly, professional translators translate documents for a specific audience and often ask what is the expected tone of the content when taking a translation job. Computational models of natural language should consider both their meaning and style. Controlling style is an emerging research area in text rewriting and is under-investigated in machine translation. In this dissertation, we present a new perspective which closely connects formality transfer and machine translation: we aim to control style in language generation with a focus on rewriting English or translating French to English with a desired formality. These are challenging tasks because annotated examples of style transfer are only available in limited quantities. We first address this problem by inducing a lexical formality model based on word embeddings and a small number of representative formal and informal words. This enables us to assign sentential formality scores and rerank translation hypotheses whose formality scores are closer to user-provided formality level. To capture broader formality changes, we then turn to neural sequence to sequence models. Joint modeling of formality transfer and machine translation enables formality control in machine translation without dedicated training examples. Along the way, we also improve low-resource neural machine translation. Keyword: Artificial intelligence; Computer science; formality; machine translation; style transfer URL: http://hdl.handle.net/1903/25379 https://doi.org/10.13016/nb3v-spmo BASE Hide details 18 Identifying Semantic Divergences in Parallel Text without Annotations ... Vyas, Yogarshi; Niu, Xing; Carpuat, Marine. - : arXiv, 2018 BASE Show details 19 Bi-Directional Neural Machine Translation with Synthetic Parallel Data ... Niu, Xing; Denkowski, Michael; Carpuat, Marine. - : arXiv, 2018 BASE Show details 20 Multi-Task Neural Models for Translating Between Styles Within and Across Languages ... Niu, Xing; Rao, Sudha; Carpuat, Marine. - : arXiv, 2018 BASE Show details Page: 1 2

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