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Hi, I appreciate your work, and your paper is well written and easy to understand, but there's one issue I haven't found the answer for. I have read through the code and paper but still have no clue about how the weight of positive/negative weight is set. I can see that they depend on the time steps and classifier-free guidance, but still don't know the details. Can you please provide some insights regarding this? Much appreciated.
The text was updated successfully, but these errors were encountered:
Hi, thanks for the kind words! The weight of positive feedback is basically a scaled and shifted square function, with the min_weight usually being set to 0 or a small value like 0.1. Here's an illustration:
The feedback strength for negative feedback is set as a fraction of the positive weight, usually 0.5. So the shape is the same, it's just the scale that's different.
Hi, I appreciate your work, and your paper is well written and easy to understand, but there's one issue I haven't found the answer for. I have read through the code and paper but still have no clue about how the weight of positive/negative weight is set. I can see that they depend on the time steps and classifier-free guidance, but still don't know the details. Can you please provide some insights regarding this? Much appreciated.
The text was updated successfully, but these errors were encountered: