Synergizing Senses: the Fusion of Vision and Language in Multimodal Learning for Enhanced Understanding

EasyChair Preprint 11952

Abstract

Multimodal learning, an interdisciplinary approach, explores the seamless integration of visual and linguistic information to enhance the understanding of complex data. This paper delves into the synergistic potential of combining vision and language in the context of multimodal learning, examining its applications across various domains. The study emphasizes the significance of leveraging diverse sensory inputs to create more comprehensive models for improved cognitive processing and knowledge representation. Multimodal learning, the convergence of information from multiple sensory modalities, has emerged as a powerful paradigm in artificial intelligence and machine learning. This paper delves into the fascinating intersection of vision and language, focusing on the advancements, challenges, and applications of multimodal learning. With a comprehensive review of the foundational concepts and recent breakthroughs in the field, we explore the synergy between vision and language, shedding light on the profound impact this interdisciplinary research area has on a myriad of domains, including computer vision, natural language processing, and robotics. In this extensive examination, we aim to provide a holistic understanding of multimodal learning's evolution and its potential for shaping the future of AI.

Keyphrases: Vision and Language Integration, cognitive processing, interdisciplinary approach, knowledge representation, multimodal learning

@booklet{EasyChair:11952,
  author    = {Asad Ali and Pitter Butta},
  title     = {Synergizing Senses: the Fusion of Vision and Language in Multimodal Learning for Enhanced Understanding},
  howpublished = {EasyChair Preprint 11952},
  year      = {EasyChair, 2024}}