International Journal of Technology and Applied Science

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Call for Paper Volume 17 Issue 10 (October 2026) Submit your research before the last 3 days of this month to publish your research paper in the current issue.
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Volume 17 Issue 10
October 2026

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Structured Analysis of the Transformer Architecture Within the Context of Machine Translation (MT)

Author(s) DR. S. THILAGAVATHI, DR. P. BALAMUTHUKUMAR
Country India
Abstract The introduction of the Transformer architecture in 2017 revolutionized the field of Machine Translation by shifting the paradigm from recurrent, sequential processing to a parallelizable, attention-based framework. By utilizing the self-attention mechanism, the Transformer effectively captures long-range dependencies in text, overcoming the limitations of previous architectures like Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) units. This report analyzes the architecture, its comparative advantages, technical challenges, and its role as the foundation for modern Natural Language Processing (NLP).
Keywords Machine Translation (MT), Neural Machine Translation, Parallelization, Long-Range Dependency Modeling, Global Context
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 17, Issue 5, May 2026
Published On 2026-05-10
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Crossref DOI prefix of IJTAS is 10.71097/IJTAS

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