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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Ngā kaituhi matua:	Areeba Umair, Elio Masciari, Muhammad Habib Ullah
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	IEEE 2026-01-01
Rangatū:	IEEE Access
Ngā marau:	Adversarial machine learning adversarial perturbations BERT fast gradient method GPT sentiments analysis
Urunga tuihono:	https://ieeexplore.ieee.org/document/11483212/
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

CONV_GBERT: Leveraging BERT&#x2013;GPT Fusion and IMP-FGSM for Adversarially Robust Sentiment Classification

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