You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository has been archived by the owner on Jan 30, 2021. It is now read-only.
In most text generating architecture, beam search provide a quality improvement by generating more natural text.
Is it useful to use beam search with XLNet ?
As far as I understand, since token are generated one by one, beam search is completely useless.
But what about generating tokens 2 by 2 ? Would it be useful to add beam search ?
Are you going to try it ?
The text was updated successfully, but these errors were encountered:
Beam search and greedy decoding causes degradation of text (it becomes repetitive) in open ended generation tasks. More discussion at https://arxiv.org/abs/1904.09751. I have observed that the same issues persist with XLNet.
Beam search is more helpful with translation and summarization where the generated text length is in the order of the context text length. The probability of degradation increases with length of the generated text for greedy (and beam search). This is still a research area so proper explanation is yet to be found.
Sign up for freeto subscribe to this conversation on GitHub.
Already have an account?
Sign in.
In most text generating architecture, beam search provide a quality improvement by generating more natural text.
Is it useful to use beam search with XLNet ?
As far as I understand, since token are generated one by one, beam search is completely useless.
But what about generating tokens 2 by 2 ? Would it be useful to add beam search ?
Are you going to try it ?
The text was updated successfully, but these errors were encountered: