Silly question but is it right? I am in grad school and this semester we run multimodal data through ML and LLM-as-judge classifiers. Even plugging in ChatGPT with a relevant judge prompt produces relatively believable results. At the same time, I struggle to trust it to generalize. I’ve read that Jev does classification across many domains and is also powered by an LLM back-end? What separates it from my above approach outside of harness efforts and finetuning of the LLM? Thank you!