ESsEN: Training Compact Discriminative Vision-Language Transformers in a Low-Resource Setting

ArXi:2604.18452v1 Announce Type: cross Vision-language modeling is rapidly increasing in popularity with an ever expanding list of available models. In most cases, these vision-language models have parameters in the tens of billions, which is necessary for some needs, but in many cases smaller models are necessary (e.g., on edge devices or independent robotic platforms). Unfortunately, there is little research in producing light-weight models or in