Incentivizing Neuro-symbolic Language-based Reasoning in VLMs via Reinforcement Learning

This work explores neuro-symbolic language reasoning in VLMs, leveraging Reinforcement Learning to improve analytical abilities and efficiency. It achieved a 3.33% accuracy increase on a vision-language evaluation dataset while reducing reasoning tokens by 75%.