Machines That Understand: A Theoretical Survey of Deep Learning's Role in Shaping Natural Language Processing
Year: 2025
Type: article
Abstract: This theoretical survey explores how deep learning—particularly Transformer architectures like BERT and GPT—has transformed Natural Language Processing (NLP). It discusses semantic modelling, ethical concerns like bias and interpretability, and outlines a roadmap for responsible future research in NLP.
Author: Boddula, Vasisht
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6949679342
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