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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 BASE Show 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; van Noord, Gertjan. - : arXiv, 2020 Abstract: Recent advances in multilingual dependency parsing have brought the idea of a truly universal parser closer to reality. However, cross-language interference and restrained model capacity remain major obstacles. To address this, we propose a novel multilingual task adaptation approach based on contextual parameter generation and adapter modules. This approach enables to learn adapters via language embeddings while sharing model parameters across languages. It also allows for an easy but effective integration of existing linguistic typology features into the parsing network. The resulting parser, UDapter, outperforms strong monolingual and multilingual baselines on the majority of both high-resource and low-resource (zero-shot) languages, showing the success of the proposed adaptation approach. Our in-depth analyses show that soft parameter sharing via typological features is key to this success. ... : In EMNLP 2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2004.14327 https://dx.doi.org/10.48550/arxiv.2004.14327 BASE Hide 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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