论文标题
用多个指定单词构造句子
Construct a Sentence with Multiple Specified Words
论文作者
论文摘要
本文展示了一项修订BART模型的任务，因此它可以从任意单词集中构造句子，这曾经是一个困难的NLP任务。培训任务是用四个单词制作句子，但是当提供较少或更多的单词时，受过训练的模型可以生成句子。总体上，输出句子具有高质量。该模型可以具有一些现实世界的应用程序，并且此任务也可以用作任何语言模型的评估机制。
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.
