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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 Hits 1 – 20 of 26 1 On cross-lingual retrieval with multilingual text encoders Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : Springer Science + Business Media, 2022 BASE Show details 2 On Cross-Lingual Retrieval with Multilingual Text Encoders ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 3 Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 4 Evaluating multilingual text encoders for unsupervised cross-lingual retrieval Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : Springer, 2021 BASE Show details 5 AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings ... Lauscher, Anne; Takieddin, Rafik; Ponzetto, Simone Paolo. - : arXiv, 2020 BASE Show details 6 SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ... The 28th International Conference on Computational Linguistics 2020; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2020 BASE Show details 7 SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ... Glavas, Goran; Vulic, Ivan; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 8 SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment Glavas, Goran; Vulic, Ivan; Korhonen, Anna-Leena. - : International Committee for Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.semeval-1.2, 2020. : Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020), 2020 BASE Show details 9 AraWEAT: Multidimensional analysis of biases in Arabic word embeddings Lauscher, Anne; Takieddin, Rafik; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2020 BASE Show details 10 SemEval-2020 Task 2: Predicting multilingual and cross-lingual (graded) lexical entailment Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2020 BASE Show details 11 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 12 Multilingual and cross-lingual graded lexical entailment Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019 BASE Show details 13 Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only ... Litschko, Robert; Glavaš, Goran; Ponzetto, Simone Paolo. - : arXiv, 2018 BASE Show details 14 Unsupervised Cross-Lingual Information Retrieval Using Monolingual Data Only ... Litschko, Robert; Glavas, Goran; Ponzetto, Simone Paolo. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 15 A Resource-Light Method for Cross-Lingual Semantic Textual Similarity ... Glavaš, Goran; Franco-Salvador, Marc; Ponzetto, Simone Paolo. - : arXiv, 2018 BASE Show details 16 Unsupervised Cross-Lingual Information Retrieval Using Monolingual Data Only Litschko, Robert; Glavas, Goran; Ponzetto, Simone Paolo; Vulic, Ivan; SIGIR, ACM. - : ACM, 2018. : ACM/SIGIR PROCEEDINGS 2018, 2018 Abstract: We propose a fully unsupervised framework for ad-hoc cross-lingual information retrieval (CLIR) which requires no bilingual data at all. The framework leverages shared cross-lingual word embedding spaces in which terms, queries, and documents can be represented, irrespective of their actual language. The shared embedding spaces are induced solely on the basis of monolingual corpora in two languages through an iterative process based on adversarial neural networks. Our experiments on the standard CLEF CLIR collections for three language pairs of varying degrees of language similarity (English-Dutch/Italian/Finnish) demonstrate the usefulness of the proposed fully unsupervised approach. Our CLIR models with unsupervised cross-lingual embeddings outperform baselines that utilize cross-lingual embeddings induced relying on word-level and document-level alignments. We then demonstrate that further improvements can be achieved by unsupervised ensemble CLIR models. We believe that the proposed framework is the first step towards development of effective CLIR models for language pairs and domains where parallel data are scarce or non-existent. Keyword: cross-lingual vector spaces; Unsupervised cross-lingual IR URL: https://www.repository.cam.ac.uk/handle/1810/279400 https://doi.org/10.17863/CAM.26775 BASE Hide details 17 An argument-annotated corpus of scientific publications Ponzetto, Simone Paolo; Lauscher, Anne; Glavaš, Goran. - : Association for Computational Linguistics, 2018 BASE Show details 18 Investigating the role of argumentation in the rhetorical analysis of scientific publications with neural multi-task learning models Ponzetto, Simone Paolo; Eckert, Kai; Lauscher, Anne. - : Association for Computational Linguistics, 2018 BASE Show details 19 A resource-light method for cross-lingual semantic textual similarity Glavas, Goran; Rosso, Paolo; Franco-Salvador, Marc. - : Elsevier, 2018 BASE Show details 20 Unsupervised cross-lingual scaling of political texts Nanni, Federico; Ponzetto, Simone Paolo; Glavaš, Goran. - : Association for Computational Linguistics, 2017 BASE Show details Page: 1 2

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