Enhanced Natural Language Understanding Using XLNET

Golakoti Vinoothna, Jeevakala Siva RamaKrishna, Bandarapu Varun Kumar, Pasumarthi Mahesh

2025

Abstract

Sentiment analysis has gained importance in understanding consumer opinions, enabling businesses and researchers to derive insights from vast amounts of unstructured text data. Traditional NLP models such as RNNs and CNNs have difficulty capturing long-range dependencies and fail to interpret sarcasm or ambiguous sentiment effectively. Transformer-based models, particularly BERT, have improved NLP tasks by leveraging bidirectional attention mechanisms. However, BERT relies on masked language modeling, which limits its ability to learn from complete sequences. XLNet overcomes this by using a permutation-based training method, allowing it to capture a broader range of word dependencies. This paper aims to evaluate the effectiveness of XLNet in sentiment analysis by fine-tuning it on the IMDB dataset. We analyze its performance against other models and highlight its advantages in handling sentiment-rich data.

Paper Citation

in Harvard Style

Vinoothna G., Siva RamaKrishna J., Varun Kumar B. and Mahesh P. (2025). Enhanced Natural Language Understanding Using XLNET. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 812-819. DOI: 10.5220/0013603100004664

in Bibtex Style

@conference{incoft25,
author={Golakoti Vinoothna and Jeevakala Siva RamaKrishna and Bandarapu Varun Kumar and Pasumarthi Mahesh},
title={Enhanced Natural Language Understanding Using XLNET},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={812-819},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013603100004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Enhanced Natural Language Understanding Using XLNET
SN - 978-989-758-763-4
AU - Vinoothna G.
AU - Siva RamaKrishna J.
AU - Varun Kumar B.
AU - Mahesh P.
PY - 2025
SP - 812
EP - 819
DO - 10.5220/0013603100004664
PB - SciTePress