Multimodal Alignment and Fusion: A Survey - A comprehensive review of multimodal alignment and fusion in machine learning

## Title of the Paper The title of the paper is "Multimodal Alignment and Fusion: A Survey." ## Publication Date of the Paper The paper was published on November 26, 2024. ## Data Types Covered in the Paper The paper covers text, images, audio, and video as the primary data types. ## Benefits of Multimodal Integration Multimodal integration improves model accuracy and applicability by leveraging complementary information from different modalities, especially in scenarios with limited data. ## Challenges in Multimodal Data Integration The paper addresses challenges such as alignment issues, noise resilience, and feature representation differences in multimodal data integration. ## Application Areas in the Paper The paper highlights applications in social media analysis, medical imaging, and emotion recognition. ## Number of Related Studies Analyzed The paper systematically classifies and analyzes over 200 related studies. ## Access to the Full Paper The full paper can be accessed via the [arXiv PDF link](https://arxiv.org/pdf/2411.17040). ### Citation sources: - [Multimodal Alignment and Fusion: A Survey](https://arxiv.org/abs/2411.17040) - Official URL Updated: 2025-03-28