2 ms·
It doesn't seem like there's any particular reason to believe this will happen. Policy tuning is one way to remove it, but there's some research on applying pol
by astrange 2y ago
It doesn't seem like there's any particular reason to believe this will happen. Policy tuning is one way to remove it, but there's some research on applying policies like "this text is a lie" during pretraining instead of trusting all of it equally.
- coldtea 2y ago>there's some research on applying policies like "this text is a lie" Of course there is, since there would be interest and grants for it. I don't see it leading to anything however.
- SrslyJosh 2y ago> Policy tuning is one way to remove it, but there's some research on applying policies like "this text is a lie" during pretraining instead of trusting all of it equally. Who's gonna vet all the training material?
- astrange 2y agoThe previous model does. https://arxiv.org/abs/2309.00267 https://arxiv.org/abs/2309.00267 That's during fine-tuning though. I know I read one about applying it during pretraining, maybe this one? https://arxiv.org/abs/2302.08582 https://arxiv.org/abs/2302.08582