[totetsu]

With llms there is a secondary training step to turn a foundational model into a chat bot. Is these something similar going on with these image generation models, that is making them all tend towards making pretty clean images and stopping them making half eaten food even if they have the capabilities?

[minimaxir]

In terms of prompt adherence, there are two issues with most image generation models, neither of which apply to Nano Banana:

1. The text encoders are primitive (e.g. CLIP) and have difficulty with nuance, such as "partially eaten", and model training can only partially overcome it. It's the same issue with the now-obsolete "half-filled" wine glass test.

2. Most models are diffusion-based, which means it denoises the entire image simultaneously. If it fails to account for the nuance in the first few passes, it can't go back and fix it.

I believe some image generation AIs were RLHFed like chat bot LLMs, but moreso to improve aesthetics rather than prompt adherence.