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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. - : 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 Abstract: In this paper, we introduce a trie-structured Bayesian model for unsupervised morphological segmentation. We adopt prior information from different sources in the model. We use neural word embeddings to discover words that are morphologically derived from each other and thereby that are semantically similar. We use letter successor variety counts obtained from tries that are built by neural word embeddings. Our results show that using different information sources such as neural word embeddings and letter successor variety as prior information improves morphological segmentation in a Bayesian model. Our model outperforms other unsupervised morphological segmentation models on Turkish and gives promising results on English and German for scarce resources. ... : 12 pages, accepted and presented at the CICLING 2017 - 18th International Conference on Intelligent Text Processing and Computational Linguistics ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1704.07329 https://dx.doi.org/10.48550/arxiv.1704.07329 BASE Hide 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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