DyMU: Dynamic Merging and Virtual Unmerging for Efficient VLMs

Zhenhailong Wang, Senthil Purushwalkam, Caiming Xiong +3

We present DyMU, an efficient, training-free framework that dynamically reduces the computational burden of vision-language models (VLMs) while maintaining high task performance. O…