SupMPN: Supervised Multiple Positives and Negatives Contrastive Learning Model for Semantic Textual Similarity

Semantic Textual Similarity (STS) is an important task in the area of Natural Language Processing (NLP) that measures the similarity of the underlying semantics of two texts. Although pre-trained contextual embedding models such as Bidirectional Encoder Representations from Transformers (BERT) have...

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Principais autores:	Somaiyeh Dehghan, Mehmet Fatih Amasyali
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2022-09-01
coleção:	Applied Sciences
Assuntos:	Natural Language Processing sentence embedding Semantic Textual Similarity BERT contrastive learning deep learning
Acesso em linha:	https://www.mdpi.com/2076-3417/12/19/9659
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