Self-Boosting Vision-Language Models with Noisy Student On-Policy Self-Distillation
This work proposes NOPD (Noisy Student On-Policy Self-Distillation), a simple yet effective self-distillation approach that improves VLMs without any external models or ground-truth answers, and demonstrates that NOPD is a general approach to enhance VLMs, achieving improvements across three models on 12 benchmarks.