Attribution Regularization for Multimodal Paradigms

arXiv:2404.02359v1 Announce Type: new
Abstract: Multimodal machine learning has gained significant attention in recent years due to its potential for integrating information from multiple modalities to enhance learning and decision-making processes. However, it is commonly observed that unimodal models outperform multimodal models, despite the latter having access to richer information. Additionally, the influence of a single modality often dominates the decision-making process, resulting in suboptimal performance. This research project aims to address these challenges by proposing a novel regularization term …

abstract arxiv attention attribution cs.lg decision however influence information machine machine learning making multimodal multimodal models multiple processes regularization type