It still is, it’s just that beam search (or other search strategies) seem to be mostly useful for closed-end short text generation; translating a sentence apparently is a task with enough of a right-or-wrong-ness to it that beam search apparently taps into no pathologies. But they get exposed for open-ended longform generation.
Seq2seq used beam search and found it helped (https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43155.pdf). It was standard practice in the early days of NMT; I’m not sure when that changed.
This blog post gives some insight into why beam search might not be a good idea, and is generally very interesting: https://benanne.github.io/2020/09/01/typicality.html
It still is, it’s just that beam search (or other search strategies) seem to be mostly useful for closed-end short text generation; translating a sentence apparently is a task with enough of a right-or-wrong-ness to it that beam search apparently taps into no pathologies. But they get exposed for open-ended longform generation.