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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 – 12 of 12 1 Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language ... Edman, Lukas; Üstün, Ahmet; Toral, Antonio. - : arXiv, 2021 BASE Show details 2 On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions ... van der Goot, Rob; Üstün, Ahmet; Plank, Barbara. - : arXiv, 2021 Abstract: Recent complementary strands of research have shown that leveraging information on the data source through encoding their properties into embeddings can lead to performance increase when training a single model on heterogeneous data sources. However, it remains unclear in which situations these dataset embeddings are most effective, because they are used in a large variety of settings, languages and tasks. Furthermore, it is usually assumed that gold information on the data source is available, and that the test data is from a distribution seen during training. In this work, we compare the effect of dataset embeddings in mono-lingual settings, multi-lingual settings, and with predicted data source label in a zero-shot setting. We evaluate on three morphosyntactic tasks: morphological tagging, lemmatization, and dependency parsing, and use 104 datasets, 66 languages, and two different dataset grouping strategies. Performance increases are highest when the datasets are of the same language, and we know from ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2103.01273 https://arxiv.org/abs/2103.01273 BASE Hide details 3 Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ... Üstün, Ahmet; Bérard, Alexandre; Besacier, Laurent. - : arXiv, 2021 BASE Show details 4 Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Berard, Alexandre; Besacier, Laurent. - : Underline Science Inc., 2021 BASE Show details 5 From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding ... van der Goot, Rob; Sharaf, Ibrahim; Imankulova, Aizhan. - : arXiv, 2021 BASE Show details 6 On the Difficulty of Translating Free-Order Case-Marking Languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bisazza, Arianna; Sportel, Stephan. - : Underline Science Inc., 2021 BASE Show details 7 UDapter: Language Adaptation for Truly Universal Dependency Parsing ... Üstün, Ahmet; Bisazza, Arianna; Bouma, Gosse. - : arXiv, 2020 BASE Show details 8 FiSSA at SemEval-2020 Task 9: Fine-tuned For Feelings ... Braaksma, Bertelt; Scholtens, Richard; van Suijlekom, Stan. - : arXiv, 2020 BASE Show details 9 Incorporating word embeddings in unsupervised morphological segmentation Üstün, Ahmet; Can, Burcu In: 2020 ; 1 ; 21 (2020) BASE Show details 10 Characters or morphemes: how to represent words? Üstün, Ahmet; Kurfalı, Murathan; Can, Burcu. - : Association for Computational Linguistics, 2018 BASE Show details 11 A Trie-Structured Bayesian Model for Unsupervised Morphological Segmentation ... Kurfalı, Murathan; Üstün, Ahmet; Can, Burcu. - : arXiv, 2017 BASE Show details 12 Turkish PoS Tagging by Reducing Sparsity with Morpheme Tags in Small Datasets ... Can, Burcu; Üstün, Ahmet; Kurfalı, Murathan. - : arXiv, 2017 BASE Show details

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