论文标题
叙事插值来产生和理解故事
Narrative Interpolation for Generating and Understanding Stories
论文作者
论文摘要
我们提出了一种用于控制叙事/故事生成的方法，我们能够通过插值来指导模型以用户指定的目标结尾来产生连贯的叙事：例如，我们被告知吉姆去远足了，最终需要救出吉姆，我们希望该模型沿途逐步生成。我们方法的核心是基于GPT-2的插值模型，该模型在上一个句子上的条件和叙述中的下一个句子，并填补了空白。此外，Reranker有助于控制生成的文本的连贯性。通过人类的评估，我们表明，结束引导的一代会导致叙事具有连贯性，对给定的结局指南忠于人，并且需要与过去的方法相比，人类向导作者的手动努力少。
We propose a method for controlled narrative/story generation where we are able to guide the model to produce coherent narratives with user-specified target endings by interpolation: for example, we are told that Jim went hiking and at the end Jim needed to be rescued, and we want the model to incrementally generate steps along the way. The core of our method is an interpolation model based on GPT-2 which conditions on a previous sentence and a next sentence in a narrative and fills in the gap. Additionally, a reranker helps control for coherence of the generated text. With human evaluation, we show that ending-guided generation results in narratives which are coherent, faithful to the given ending guide, and require less manual effort on the part of the human guide writer than past approaches.
