Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey

In three linesSystematic survey on Mixture-of-Experts (MoE) applied to multimodal learning. Analyzes MoE from three perspectives: efficient engine (scalability, redundancy reduction), representation learner (multi-expert alignment), modular adapter (modality imbalance, missing data). Identifies gaps: interpretable routing, expert communication, modality integration, lifelong learning.

Summary generated by Claude — human-verified