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Hits 1 – 3 of 3
1
Specializing unsupervised pretraining models for word-level semantic similarity
Ponti, Edoardo Maria
;
Korhonen, Anna
;
Vulić, Ivan
. - : Association for Computational Linguistics, ACL, 2020
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2
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
Lauscher, Anne
;
Vulić, Ivan
;
Ponti, Edoardo Maria
;
Korhonen, Anna
;
Glavaš, Goran
. - : arXiv, 2019
Abstract:
Unsupervised pretraining models have been shown to facilitate a wide range of downstream NLP applications. These models, however, retain some of the limitations of traditional static word embeddings. In particular, they encode only the distributional knowledge available in raw text corpora, incorporated through language modeling objectives. In this work, we complement such distributional knowledge with external lexical knowledge, that is, we integrate the discrete knowledge on word-level semantic similarity into pretraining. To this end, we generalize the standard BERT model to a multi-task learning setting where we couple BERT's masked language modeling and next sentence prediction objectives with an auxiliary task of binary word relation classification. Our experiments suggest that our "Lexically Informed" BERT (LIBERT), specialized for the word-level semantic similarity, yields better performance than the lexically blind "vanilla" BERT on several language understanding tasks. Concretely, LIBERT ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://arxiv.org/abs/1909.02339
https://dx.doi.org/10.48550/arxiv.1909.02339
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3
Informing unsupervised pretraining with external linguistic knowledge
Lauscher, Anne
;
Vulić, Ivan
;
Ponti, Edoardo Maria
. - : Cornell University, 2019
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