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

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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Bibliographic Details
Main Authors: Somaiyeh Dehghan, Mehmet Fatih Amasyali
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Applied Sciences
Subjects:
Natural Language Processing
sentence embedding
Semantic Textual Similarity
BERT
contrastive learning
deep learning
Online Access:https://www.mdpi.com/2076-3417/12/19/9659

Internet

https://www.mdpi.com/2076-3417/12/19/9659

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