Shun Qian

CR³: Boosting Compositional Reasoning in MLLMs Through Rule-Based Reinforcement Learning

Compositional reasoning is a critical capability for multimodal models, enabling systematic understanding of complex scenes through structured combinations of objects, attributes, and relations. However, existing research on this ability primarily focuses on vision-language models (VLMs, e.g., CLIP