For the application: being able to prompt anywhere in the sequence can be of interest. For what we've seen in the experiment, the rejection sampling leads to similar generation than the autoregressive one, we did not…
Hey! I'm Arnaud, first author of the paper. XLNet also shuffles the data during training, but they use a masking mechanism instead of the causal + double positional encoding. The application differs, XLNet is not AFAIK…
For the application: being able to prompt anywhere in the sequence can be of interest. For what we've seen in the experiment, the rejection sampling leads to similar generation than the autoregressive one, we did not…
Hey! I'm Arnaud, first author of the paper. XLNet also shuffles the data during training, but they use a masking mechanism instead of the causal + double positional encoding. The application differs, XLNet is not AFAIK…