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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 – 4 of 4 1 Distributionally Robust Multilingual Machine Translation ... Zhou, Chunting; Levy, Daniel; Li, Xian. - : arXiv, 2021 BASE Show details 2 Detecting Hallucinated Content in Conditional Neural Sequence Generation ... 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; Diab, Mona; Ghazvininejad, Marjan. - : Underline Science Inc., 2021 BASE Show details 3 Distributionally Robust Multilingual Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ghazvininejad, Marjan; Levy, Daniel; Li, Xian; Neubig, Graham; Zhou, Chunting. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.458/ Abstract: Multilingual neural machine translation (MNMT) learns to translate multiple language pairs with a single model, potentially improving both the accuracy and the memoryefficiency of deployed models. However, the heavy data imbalance between languages hinders the model from performing uniformly across language pairs. In this paper, we propose a new learning objective for MNMT based on distributionally robust optimization, which minimizes the worst-case expected loss over the set of language pairs. We further show how to practically optimize this objective for large translation corpora using an iterated best response scheme, which is both effective and incurs negligible additional computational cost compared to standard empirical risk minimization. We perform extensive experiments on three sets of languages from two datasets and show that our method consistently outperforms strong baseline methods in terms of average and per-language ... Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing URL: https://dx.doi.org/10.48448/kr4y-4087 https://underline.io/lecture/37597-distributionally-robust-multilingual-machine-translation BASE Hide details 4 Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations ... Chaudhary, Aditi; Zhou, Chunting; Levin, Lori. - : arXiv, 2018 BASE Show details

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