  This paper demonstrates a task to finetune a BART model so it can construct a
sentence from an arbitrary set of words, which used to be a difficult NLP task.
The training task is making sentences with four words, but the trained model
can generate sentences when fewer or more words are provided. The output
sentences have high quality in general. The model can have some real-world
applications, and this task can be used as an evaluation mechanism for any
language model as well.
