3 ms·

I can't speak for LLMs, but Stable Diffusion goes above and beyond bias you would expect in a dataset. Corporate executive photos are an often cited example, b

I can't speak for LLMs, but Stable Diffusion goes above and beyond bias you would expect in a dataset. Corporate executive photos are an often cited example, but a good one. It almost exclusively generates stereotypical white guys, where the dataset can't be that homogenous. "Dark skin" pretty much exclusively generates African Americans, and its hard to steer away. Its also almost impossible to generate a dark skinned person with light eyes. What I am getting at is that reasonable dataset correlations can turn into hard assumptions in diffusion, and maybe other transformers models.

GaggiX 3y ago
That's probably all to blame on CFG.
pk-protect-ai 3y ago
You can't blame this on the math or transformers though. This is the thing about statistic, - the datasets have a tendency inherited from the human perception and biases. You can actually spend some time and money to analyze the LION 5B dataset to find out how homogeneous it is. People create photos and tag them, however small the bias in initial data is, it will be exposed by the NN, because it is more probable.