曾经有一个非常糟糕的诗人，它是自动的，但你不知道
There Once Was a Really Bad Poet, It Was Automated but You Didn't Know It
摘要：
利默里克一代体现了诗歌一代面临的一些最困难的挑战，因为诗歌必须只用五行来讲述一个故事，并且对押韵、重读和韵律有限制。为了解决这些挑战，我们引入LimGen，一种新颖的，完全自动化的打油诗生成系统，其性能优于最先进的基于神经网络的诗歌模型，以及先前的基于规则的诗歌模型。LimGen由三个重要部分组成：自适应多模板约束算法，它将我们的搜索限制在现实诗歌的空间，多模板束搜索算法，它可以有效地搜索整个空间，以及概率故事情节算法，它可以提供与用户提供的提示词相关的连贯故事情节。由此产生的打油诗满足诗意的限制，并有主题连贯的故事情节，这有时甚至是有趣的（当我们幸运）。
英文摘要：
Limerick generation exemplifies some of the most difficult challenges faced in poetry generation, as the poems must tell a story in only five lines, with constraints on rhyme, stress, and meter. To address these challenges, we introduce LimGen, a novel and fully automated system for limerick generation that outperforms state-of-the-art neural network-based poetry models, as well as prior rule-based poetry models. LimGen consists of three important pieces: the Adaptive Multi-Templated Constraint algorithm that constrains our search to the space of realistic poems, the Multi-Templated Beam Search algorithm which searches efficiently through the space, and the probabilistic Storyline algorithm that provides coherent storylines related to a user-provided prompt word. The resulting limericks satisfy poetic constraints and have thematically coherent storylines, which are sometimes even funny (when we are lucky).
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。
