回到起点：生成具有相关首尾句的叙事
Returning to the Start: Generating Narratives with Related Endpoints
AI总结：
本文提出可控故事生成范式 RENarGen，通过让首尾句相关再填充中间内容来增强叙事闭合性，实验表明其生成质量优于现有自回归模型。
摘要：
人类作家常常用与开头句子相呼应的结尾句子来“首尾呼应”自己的作品，以构成一个令人满意的、“闭环”的叙事。受这一观察启发，我们提出了 RENarGen，一种可控的故事生成范式，它通过确保首句和末句相关、然后填充中间句子来生成叙事。我们的贡献包括对叙事学中各种首尾呼应方法如何影响故事语言建模的初步探索。自动评估和人工评估表明，RENarGen 比当前的自动回归模型能生成更好的故事，并具有更强的叙事闭合性。
英文摘要：
Human writers often bookend their writing with ending sentences that relate back to the beginning sentences in order to compose a satisfying narrative that "closes the loop." Motivated by this observation, we propose RENarGen, a controllable story-generation paradigm that generates narratives by ensuring the first and last sentences are related and then infilling the middle sentences. Our contributions include an initial exploration of how various methods of bookending from Narratology affect language modeling for stories. Automatic and human evaluations indicate RENarGen produces better stories with more narrative closure than current autoregressive models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
