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Simple Search
Hits 1 – 9 of 9
1
Improving Word Translation via Two-Stage Contrastive Learning ...
Li, Yaoyiran
;
Liu, Fangyu
;
Collier, Nigel
. - : arXiv, 2022
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2
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
Liu, Fangyu
;
Vulić, Ivan
;
Korhonen, Anna
. - : arXiv, 2021
BASE
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3
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
Liu, Qianchu
;
Liu, Fangyu
;
Collier, Nigel
. - : arXiv, 2021
BASE
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4
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
Liu, Qianchu
;
Liu, Fangyu
;
Collier, Nigel
. - : Apollo - University of Cambridge Repository, 2021
BASE
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5
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
., Nigel
;
Korhonen, Anna
. - : Underline Science Inc., 2021
BASE
Show details
6
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Nigel
;
Korhonen, Anna
. - : Underline Science Inc., 2021
BASE
Show details
7
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
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8
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
Liu, Fangyu
;
Vulić, Ivan
;
Korhonen, Anna
. - : arXiv, 2021
BASE
Show details
9
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Nigel
;
Korhonen, Anna
. - : Underline Science Inc., 2021
BASE
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