Contrastive Meta-Learner for Automatic Text Labeling and Semantic Textual Similarity

Generating large labeled datasets is a common barrier in machine learning efforts, with frequent challenges in both labeling and creating useful models for these datasets. We introduce a new approach to the automatic text labeling and semantic textual similarity tasks, which utilizes an encoder laye...

Popoln opis

Bibliografske podrobnosti

Principais autores:	Ryan Cooper, Kenneth W. Kliesner, Stephen Zenker
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2024-01-01
Serija:	IEEE Access
Teme:	Semantic textual similarity constrastive meta-learning deep metric learning few-shot learning triplet loss transformers
Online dostop:	https://ieeexplore.ieee.org/document/10587218/
Oznake:	Označite Brez oznak, prvi označite!