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    • Glavaš, Goran (12)
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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 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : arXiv, 2019 BASE Show details 2 Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? ... Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : arXiv, 2019 BASE Show details 3 SEAGLE: A platform for comparative evaluation of semantic encoders for information retrieval Schmidt, Fabian David; Dietsche, Markus; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019 BASE Show details 4 Multilingual and cross-lingual graded lexical entailment Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019 BASE Show details 5 Specializing distributional vectors of all words for lexical entailment Ponti, Edoardo Maria; Kamath, Aishwarya; Pfeiffer, Jonas. - : Association for Computational Linguistics, 2019 BASE Show details 6 How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions Glavaš, Goran; Litschko, Robert; Ruder, Sebastian. - : Association for Computational Linguistics, 2019 BASE Show details 7 Cross-lingual semantic specialization via lexical relation induction Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019 BASE Show details 8 Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2019 BASE Show details 9 SenZi: A sentiment analysis lexicon for the latinised Arabic (Arabizi) Tobaili, Taha; Fernández, Miriam; Alani, Harith. - : INCOMA, 2019 BASE Show details 10 Informing unsupervised pretraining with external linguistic knowledge Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : Cornell University, 2019 BASE Show details 11 Do we really need fully unsupervised cross-lingual embeddings? Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : Association for Computational Linguistics, 2019 BASE Show details 12 Are we consistently biased? Multidimensional analysis of biases in distributional word vectors Lauscher, Anne; Glavaš, Goran. - : Association for Computational Linguistics, 2019 Abstract: Word embeddings have recently been shown to reflect many of the pronounced societal biases (e.g., gender bias or racial bias). Existing studies are, however, limited in scope and do not investigate the consistency of biases across relevant dimensions like embedding models, types of texts, and different languages. In this work, we present a systematic study of biases encoded in distributional word vector spaces: we analyze how consistent the bias effects are across languages, corpora, and embedding models. Furthermore, we analyze the cross-lingual biases encoded in bilingual embedding spaces, indicative of the effects of bias transfer encompassed in cross-lingual transfer of NLP models. Our study yields some unexpected findings, e.g., that biases can be emphasized or downplayed by different embedding models or that user-generated content may be less biased than encyclopedic text. We hope our work catalyzes bias research in NLP and informs the development of bias reduction techniques. Keyword: 004 Informatik URL: https://madoc.bib.uni-mannheim.de/49699/ https://doi.org/10.18653/v1/S19-1010 https://www.aclweb.org/anthology/S19-1010/ BASE Hide details

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