Do these models really lie or do they only do what they are supposed to do - produce text that is statistically similar to the training set, but not in the training set (and thus can include false/made up statements)?
Now they add another run on top of it that is in principle prone to the same issues, except they reward the model for factuality instead of likeability. This is cool, but why not apply the same reward strategy to the answer itself?
Now they add another run on top of it that is in principle prone to the same issues, except they reward the model for factuality instead of likeability. This is cool, but why not apply the same reward strategy to the answer itself?