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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 3 4 5 6 7...18 Hits 41 – 60 of 360 41 A Graph Auto-encoder Model of Derivational Morphology Schütze, Hinrich; Pierrehumbert, Janet; Hofmann, Valentin. - : Ludwig-Maximilians-Universität München, 2020 BASE Show details 42 Relational and Fine-Grained Argument Mining Trautmann, Dietrich; Fromm, Michael; Tresp, Volker... In: Datenbank-Spektrum (2020) BASE Show details 43 Identifying Elements Essential for BERT’s Multilinguality Schütze, Hinrich; Dufter, Philipp. - 2020 BASE Show details 44 SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings Sabet, Masoud Jalili; Dufter, Philipp; Schütze, Hinrich In: Findings of ACL: EMNLP 2020 (2020) BASE Show details 45 Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations Liang, Sheng; Dufter, Philipp; Schütze, Hinrich. - 2020 BASE Show details 46 Increasing Learning Efficiency of Self-Attention Networks through Direct Position Interactions, Learnable Temperature, and Convoluted Attention Schütze, Hinrich; Dufter, Philipp; Schmitt, Martin. - 2020 BASE Show details 47 SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings ... Sabet, Masoud Jalili; Dufter, Philipp; Yvon, François; Schütze, Hinrich. - : arXiv, 2020 Abstract: Word alignments are useful for tasks like statistical and neural machine translation (NMT) and cross-lingual annotation projection. Statistical word aligners perform well, as do methods that extract alignments jointly with translations in NMT. However, most approaches require parallel training data, and quality decreases as less training data is available. We propose word alignment methods that require no parallel data. The key idea is to leverage multilingual word embeddings, both static and contextualized, for word alignment. Our multilingual embeddings are created from monolingual data only without relying on any parallel data or dictionaries. We find that alignments created from embeddings are superior for four and comparable for two language pairs compared to those produced by traditional statistical aligners, even with abundant parallel data; e.g., contextualized embeddings achieve a word alignment F1 for English-German that is 5 percentage points higher than eflomal, a high-quality statistical ... : EMNLP (Findings) 2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2004.08728 https://dx.doi.org/10.48550/arxiv.2004.08728 BASE Hide details 48 Identifying Necessary Elements for BERT's Multilinguality ... Dufter, Philipp; Schütze, Hinrich. - : arXiv, 2020 BASE Show details 49 Identifying Elements Essential for BERT’s Multilinguality ... Dufter, Philipp; Schütze, Hinrich. - : Universitätsbibliothek der Ludwig-Maximilians-Universität München, 2020 BASE Show details 50 Identifying Necessary Elements for BERT’s Multilinguality ... Dufter, Philipp; Schütze, Hinrich. - : Universitätsbibliothek der Ludwig-Maximilians-Universität München, 2020 BASE Show details 51 Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations ... Liang, Sheng; Dufter, Philipp; Schütze, Hinrich. - : Universitätsbibliothek der Ludwig-Maximilians-Universität München, 2020 BASE Show details 52 SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings ... Sabet, Masoud Jalili; Dufter, Philipp; Schütze, Hinrich. - : Universitätsbibliothek der Ludwig-Maximilians-Universität München, 2020 BASE Show details 53 Dynamic Contextualized Word Embeddings ... Hofmann, Valentin; Pierrehumbert, Janet B.; Schütze, Hinrich. - : arXiv, 2020 BASE Show details 54 Predicting the Growth of Morphological Families from Social and Linguistic Factors ... Hofmann, Valentin; Pierrehumbert, Janet; Schütze, Hinrich. - : Association for Computational Linguistics, 2020 BASE Show details 55 Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly ... Kassner, Nora; Schütze, Hinrich. - : Association for Computational Linguistics, 2020 BASE Show details 56 Quantifying the Contextualization of Word Representations with Semantic Class Probing ... Zhao, Mengjie; Dufter, Philipp; Yaghoobzadeh, Yadollah. - : Association for Computational Linguistics, 2020 BASE Show details 57 Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity ... Poerner, Nina; Waltinger, Ulli; Schütze, Hinrich. - : Association for Computational Linguistics, 2020 BASE Show details 58 Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations ... The 28th International Conference on Computational Linguistics 2020; ., Hinrich; Dufter, Philipp. - : Underline Science Inc., 2020 BASE Show details 59 A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ... Zhao, Mengjie; Zhu, Yi; Shareghi, Ehsan. - : arXiv, 2020 BASE Show details 60 Unsupervised Embedding-based Detection of Lexical Semantic Changes ... Asgari, Ehsaneddin; Ringlstetter, Christoph; Schütze, Hinrich. - : arXiv, 2020 BASE Show details Page: 1 2 3 4 5 6 7...18

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