MSP: Modality Self-Play for Training Multimodal LLMs Without Paired Cross-Modal Data

Large multimodal models have achieved remarkable progress by scaling model capacity and training on massive paired multimodal data. However, this paradigm introduces a fundamental bottleneck: aligned multimodal datasets are expensive to curate, difficult to scale across diverse modality combinations