Augmented SBERT
Augmented SBERT
**Augmented SBERT** is a data augmentation strategy for pairwise sentence scoring that uses a [BERT](https://paperswithcode.com/method/bert) cross-encoder to improve the performance for the [SBERT](https://paperswithcode.com/method/sbert) bi-encoders. Given a pre-trained, well-performing crossencoder, we sample sentence pairs according to a certain sampling strategy and label these using the cross-encoder. We call these weakly labeled examples the silver dataset and they will be merged with the gold training dataset. We then train the bi-encoder on this extended training dataset.
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks
https://paperswithcode.com/paper/augmented-sbert-data-augmentation-method-for
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks