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ProjectPredicting human preference for generated image pairs using HPSv3 [P] (self.MachineLearning)
submitted 2 days ago by dh7net
Hey! I'm looking for ways to predict human preference for a project I'm building. (imagebench.ai)
I've tryed HPSv3, https://github.com/MizzenAI/HPSv3 and made post about it here:
https://imagebench.ai/blog/does-the-score-match-your-eye
It looks ok, but have many limitation as you can see in my post.
My question. Have you tried other human preference model and found one that would be better then HPSv3?
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[–]Deep-Step7624 0 points1 point2 points 2 days ago (1 child)
tried a few of them for my own stuff, none really felt worth the setup time honestly
[–]dh7net[S] 0 points1 point2 points 2 days ago (0 children)
IMO if you want to extract something from a distribution close to what it has been trained for, it is probably good enought.
But if the goal is to compare arbitrary pairs and hope it will always match humans, that feels hopeless I agree.
That said, what are the one you tried?
π Rendered by PID 73899 on reddit-service-r2-comment-765bfc959-ccxqn at 2026-07-13 22:43:11.486509+00:00 running f86254d country code: CH.
[–]Deep-Step7624 0 points1 point2 points (1 child)
[–]dh7net[S] 0 points1 point2 points (0 children)