Enhancing Contextual Understanding in Large Language Models through  Multi-Modal Learning Approaches

Avinash Alugolu, Dr. Prasadu Peddi

Enhancing Contextual Understanding in Large Language Models through Multi-Modal Learning Approaches

Authors

Avinash Alugolu, Dr. Prasadu Peddi

Keywords:

Large Language Models, Multimodal Learning, Transformer Architectures, Cross-Modal Attention, Artificial Intelligence, Contextual Understanding, Deep Learning, Multimodal Fusion, Text-Image-Speech Integration, Representation Learning.

Abstract

Artificial Intelligence has undergone unprecedented transformation during the past decade,fundamentally reshaping computational capabilities across natural language processing, computer vision, speech recognition, and intelligent decision-making systems

References

A. Vaswani et al., “Attention Is All You Need,” Advances in Neural Information Processing Systems, 2017.

J. Devlin et al., “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,” NAACL, 2019.

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Published

2024-10-15

How to Cite

Avinash Alugolu, Dr. Prasadu Peddi. (2024). Enhancing Contextual Understanding in Large Language Models through Multi-Modal Learning Approaches . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 8706–8715. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5433