AIM: Adaptive Intra-Network Modulation for Balanced Multimodal Learning

AIM, or Adaptive Intra-Network Modulation, addresses the challenges of imbalanced multimodal learning in machine learning. While multimodal learning has improved performance, it often struggles with balancing the contributions of different modalities. Traditional methods tend to hinder the learning of the dominant modality to support weaker ones, which can negatively impact overall performance. This research is significant as it seeks to refine these approaches, potentially leading to more effective and balanced learning systems.