English

Modelling Sentiment Analysis: LLMs and data augmentation techniques

Computation and Language 2023-11-08 v1

Abstract

This paper provides different approaches for a binary sentiment classification on a small training dataset. LLMs that provided state-of-the-art results in sentiment analysis and similar domains are being used, such as BERT, RoBERTa and XLNet.

Keywords

Cite

@article{arxiv.2311.04139,
  title  = {Modelling Sentiment Analysis: LLMs and data augmentation techniques},
  author = {Guillem Senabre Prades},
  journal= {arXiv preprint arXiv:2311.04139},
  year   = {2023}
}

Comments

4 pages. For more information check the github link in the conclusion. Enjoy!

R2 v1 2026-06-28T13:14:15.993Z