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1
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
Litschko, R; Vulić, I; Ponzetto, SP. - : Apollo - University of Cambridge Repository, 2021
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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
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3
Towards zero-shot language modeling ...
Ponti, Edoardo; Vulić, I; Cotterell, R. - : Apollo - University of Cambridge Repository, 2020
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4
Cross-lingual semantic specialization via lexical relation induction ...
Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020
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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
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6
Do we really need fully unsupervised cross-lingual embeddings? ...
Vulić, I; Glavaš, G; Reichart, R. - : Apollo - University of Cambridge Repository, 2020
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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
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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
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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
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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
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11
Do we really need fully unsupervised cross-lingual embeddings?
Vulić, I; Glavaš, G; Reichart, R; Korhonen, Anna-Leena. - : 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
Abstract: Recent efforts in cross-lingual word embedding (CLWE) learning have predominantly focused on fully unsupervised approaches that project monolingual embeddings into a shared cross-lingual space without any cross-lingual signal. The lack of any supervision makes such approaches conceptually attractive. Yet, their only core difference from (weakly) supervised projection-based CLWE methods is in the way they obtain a seed dictionary used to initialize an iterative self-learning procedure. The fully unsupervised methods have arguably become more robust, and their primary use case is CLWE induction for pairs of resource-poor and distant languages. In this paper, we question the ability of even the most robust unsupervised CLWE approaches to induce meaningful CLWEs in these more challenging settings. A series of bilingual lexicon induction (BLI) experiments with 15 diverse languages (210 language pairs) show that fully unsupervised CLWE methods still fail for a large number of language pairs (e.g., they yield zero BLI performance for 87/210 pairs). Even when they succeed, they never surpass the performance of weakly supervised methods (seeded with 500-1,000 translation pairs) using the same self-learning procedure in any BLI setup, and the gaps are often substantial. These findings call for revisiting the main motivations behind fully unsupervised CLWE methods.
URL: https://www.repository.cam.ac.uk/handle/1810/296966
https://doi.org/10.17863/CAM.44007
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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
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13
A survey of cross-lingual word embedding models ...
Ruder, S; Vulić, I; Søgaard, A. - : Apollo - University of Cambridge Repository, 2019
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14
Zero-shot language transfer for cross-lingual sentence retrieval using bidirectional attention model ...
Glavaš, G; Vulić, I. - : Apollo - University of Cambridge Repository, 2019
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15
Learning unsupervised multilingual word embeddings with incremental multilingual hubs ...
Heyman, G; Verreet, B; Vulić, I. - : Apollo - University of Cambridge Repository, 2019
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16
Specializing distributional vectors of allwords for lexical entailment ...
Kamath, A; Pfeiffer, J; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2019
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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
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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
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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
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20
Learning unsupervised multilingual word embeddings with incremental multilingual hubs
Heyman, G; Verreet, B; Vulić, I. - : NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference, 2019
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