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1
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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2
Towards zero-shot language modeling ...
Ponti, Edoardo; Vulić, I; Cotterell, R. - : Apollo - University of Cambridge Repository, 2020
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3
Cross-lingual semantic specialization via lexical relation induction ...
Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020
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4
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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5
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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6
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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7
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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8
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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9
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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10
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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11
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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12
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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13
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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14
A systematic study of leveraging subword information for learning word representations
Zhu, Y; Korhonen, Anna-Leena; 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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15
Acquiring verb classes through bottom-up semantic verb clustering ...
Majewska, Olga; McCarthy, D; Vulić, I. - : Apollo - University of Cambridge Repository, 2018
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16
Acquiring verb classes through bottom-up semantic verb clustering
Majewska, Olga; McCarthy, D; Vulić, I. - : LREC 2018 - 11th International Conference on Language Resources and Evaluation, 2018
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17
Decoding sentiment from distributed representations of sentences ...
Ponti, Edoardo; Vulić, I; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2017
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18
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment ...
Vulić, I; Gerz, D; Kiela, D. - : Apollo - University of Cambridge Repository, 2017
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19
Decoding sentiment from distributed representations of sentences
Ponti, Edoardo; Vulić, I; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : *SEM 2017 - 6th Joint Conference on Lexical and Computational Semantics, Proceedings, 2017
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20
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment
Vulić, I; Gerz, D; Kiela, D. - : MIT Press, 2017. : Computational Linguistics, 2017
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