Shenwei Li

Activating Visual Context and Commonsense Reasoning Through Masked Prediction in VLMs

Recent breakthroughs in reasoning models have markedly advanced the reasoning capabilities of large language models, particularly via training on tasks with verifiable rewards. Yet, a significant gap persists in their adaptation to real-world multimodal scenarios, most notably, vision-language tasks