Xinghao Zhao

Curr-ReFT: Overcoming Training Bottlenecks in Small-scale Vision-Language Models via Curriculum Reinforcement Finetuning

State-of-the-art vision-language models (VLMs) require massive scaling that limits practical deployment. Small-scale VLMs offer a practical alternative but face out-of-domain (OOD) collapse when trained with traditional supervised fine-tuning (SFT). Through GeneralPoints experiments, we identify tha