A multimodal Jev concept for scoring how well text fits an image

A user proposes a multimodal version of Jev that would take an image and a set of freeform texts, then score how well each text fits the image. They suggest it could give yes/no answers using a sigmoid and produce calibrated scores. They also speculate about releasing it with open weights and fewer than 1 billion parameters, perhaps around 400 million.