R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?

The article introduces R1-SyntheticVL, a multimodal large language model trained on MMSynthetic-20K, utilizing a novel data synthesis technique called Collective Adversarial Data Synthesis (CADS). CADS comprises two phases: CAD-Generate for generating diverse multimodal data and CAD-Judge for assessing its quality, incorporating an Adversarial Context Optimization mechanism to enhance data challenge and value. This approach is significant for practitioners as it provides a framework for generating high-quality training data, potentially improving the performance of MLLMs on complex tasks.