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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 Hits 1 – 20 of 53 1 Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ... Litschko, R; Vulić, I; Ponzetto, SP. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 2 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... Liu, Fangyu; Vulić, I; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 3 Towards zero-shot language modeling ... Ponti, Edoardo; Vulić, I; Cotterell, R. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 4 Cross-lingual semantic specialization via lexical relation induction ... Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 5 Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization ... Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 6 Do we really need fully unsupervised cross-lingual embeddings? ... Vulić, I; Glavaš, G; Reichart, R. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 7 On the relation between linguistic typology and (limitations of) multilingual language modeling ... Gerz, Daniela; Vulić, I; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 8 Cross-lingual semantic specialization via lexical relation induction Ponti, Edoardo; Vulić, I; Glavaš, G. - : EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2020 BASE Show details 9 On the relation between linguistic typology and (limitations of) multilingual language modeling Gerz, Daniela; Vulić, I; Ponti, Edoardo. - : Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, 2020 BASE Show details 10 Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization Ponti, Edoardo; Vulić, I; Glavaš, G. - : Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, 2020 BASE Show details 11 Do we really need fully unsupervised cross-lingual embeddings? Vulić, I; Glavaš, G; Reichart, R. - : EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2020 BASE Show details 12 Towards zero-shot language modeling Ponti, Edoardo; Vulić, I; Cotterell, R. - : EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2020 BASE Show details 13 A survey of cross-lingual word embedding models ... Ruder, S; Vulić, I; Søgaard, A. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 14 Zero-shot language transfer for cross-lingual sentence retrieval using bidirectional attention model ... Glavaš, G; Vulić, I. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 15 Learning unsupervised multilingual word embeddings with incremental multilingual hubs ... Heyman, G; Verreet, B; Vulić, I. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 16 Specializing distributional vectors of allwords for lexical entailment ... Kamath, A; Pfeiffer, J; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 17 Investigating cross-lingual alignment methods for contextualized embeddings with Token-level evaluation ... Liu, Qianchu; McCarthy, D; Vulić, I. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 18 Specializing distributional vectors of allwords for lexical entailment Kamath, A; Pfeiffer, J; Ponti, Edoardo. - : ACL 2019 - 4th Workshop on Representation Learning for NLP, RepL4NLP 2019 - Proceedings of the Workshop, 2019 BASE Show details 19 Investigating cross-lingual alignment methods for contextualized embeddings with Token-level evaluation Liu, Qianchu; McCarthy, D; Vulić, I. - : CoNLL 2019 - 23rd Conference on Computational Natural Language Learning, Proceedings of the Conference, 2019 BASE Show details 20 Learning unsupervised multilingual word embeddings with incremental multilingual hubs Heyman, G; Verreet, B; Vulić, I; Moens, MF. - : NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference, 2019 Abstract: Recent research has discovered that a shared bilingual word embedding space can be induced by projecting monolingual word embedding spaces from two languages using a self-learning paradigm without any bilingual supervision. However, it has also been shown that for distant language pairs such fully unsupervised self-learning methods are unstable and often get stuck in poor local optima due to reduced isomorphism between starting monolingual spaces. In this work, we propose a new robust framework for learning unsupervised multilingual word embeddings that mitigates the instability issues. We learn a shared multilingual embedding space for a variable number of languages by incrementally adding new languages one by one to the current multilingual space. Through the gradual language addition our method can leverage the interdependencies between the new language and all other languages in the current multilingual hub/space. We find that it is beneficial to project more distant languages later in the iterative process. Our fully unsupervised multilingual embedding spaces yield results that are on par with the state-of-the-art methods in the bilingual lexicon induction (BLI) task, and simultaneously obtain state-of-the-art scores on two downstream tasks: multilingual document classification and multilingual dependency parsing, outperforming even supervised baselines. This finding also accentuates the need to establish evaluation protocols for cross-lingual word embeddings beyond the omnipresent intrinsic BLI task in future work. URL: https://doi.org/10.17863/CAM.39779 https://www.repository.cam.ac.uk/handle/1810/292618 BASE Hide details Page: 1 2 3

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