CONV_GBERT: Leveraging BERT–GPT Fusion and IMP-FGSM for Adversarially Robust Sentiment Classification

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the local feature extraction strength of convolutional neural networks. By concaten...

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Bibliographic Details
Published in:IEEE Access
Main Authors: Areeba Umair, Elio Masciari, Muhammad Habib Ullah
Format: Article
Language:English
Published: IEEE 2026-01-01
Subjects:
Adversarial machine learning
adversarial perturbations
BERT
fast gradient method
GPT
sentiments analysis
Online Access:https://ieeexplore.ieee.org/document/11483212/

Internet

https://ieeexplore.ieee.org/document/11483212/

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