this post was submitted on 25 May 2026
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[–] chunes@lemmy.world -3 points 9 hours ago (4 children)
[–] CmdrShepard49@sh.itjust.works 1 points 2 hours ago* (last edited 2 hours ago)

Our key finding is that by injecting information through an external synthetic data verifier, whether a human or a better model, synthetic retraining will not cause model collapse.

Lol, so to make a great model, they just need to have an even better one available first or a human who can verify every single thing it ingests.

Hmm, call me skeptical on this claim.

[–] corsicanguppy@lemmy.ca 2 points 5 hours ago

This assumes everything is valid on the external. If one slop cluster feeds off another - a slopveyor? - then there is nothing external for the validation hall-monitor to compare against. They're trusting another model's output as if it were gospel.

[–] Grandwolf319@sh.itjust.works 12 points 8 hours ago (1 children)

Our key finding is that by injecting information through an external synthetic data verifier, whether a human or a better model, synthetic retraining will not cause model collapse.

Yeah if you have a source of truth then your model is basically getting trained on that.

It’s like already having the answer

[–] chunes@lemmy.world -2 points 8 hours ago (1 children)

The point is that it only needs to comprise a very small part of the model.

[–] Grandwolf319@sh.itjust.works 5 points 6 hours ago

My point was that having a verifier means your not really training a model on another model’s data, it’s basically as if you get new raw data from a non AI source