论文标题
命令的文字编辑
Text Editing by Command
论文作者
论文摘要
神经文本生成中的典型范式是一代一代，其中文本是单步的。但是，当用户希望对生成的文本施加的约束是动态的，尤其是在创作更长的文档时，一个镜头设置不足。我们使用交互式文本生成设置来解决此限制，在该设置中，用户通过发出命令编辑现有文本来与系统进行交互。为此，我们提出了一项新颖的文本编辑任务，并介绍了Wikidocedits，Wikidocedits是一个从Wikipedia爬行的单句子编辑的数据集。我们表明，我们的交互式编辑器是一种基于变压器的模型，该模型在该数据集上训练，优于基准，并在自动和人类评估中获得了积极的结果。我们介绍了该模型性能的经验和定性分析。
A prevailing paradigm in neural text generation is one-shot generation, where text is produced in a single step. The one-shot setting is inadequate, however, when the constraints the user wishes to impose on the generated text are dynamic, especially when authoring longer documents. We address this limitation with an interactive text generation setting in which the user interacts with the system by issuing commands to edit existing text. To this end, we propose a novel text editing task, and introduce WikiDocEdits, a dataset of single-sentence edits crawled from Wikipedia. We show that our Interactive Editor, a transformer-based model trained on this dataset, outperforms baselines and obtains positive results in both automatic and human evaluations. We present empirical and qualitative analyses of this model's performance.
