多目标跨语言摘要：一项新颖任务与一种语言无关方法
Multi-Target Cross-Lingual Summarization: a novel task and a language-neutral approach
AI总结：
针对跨语言摘要中多语言输出语义一致性被忽视的问题，本文定义多目标跨语言摘要任务，并提出语言无关的重排序方法与多准则评估协议。
摘要：
跨语言摘要旨在通过总结不同语言的文档来弥合语言障碍。然而，确保跨语言的语义连贯性是一个被忽视的挑战，并且在若干场景中可能至关重要。为填补这一空白，我们提出多目标跨语言摘要，即将一份文档总结为多种目标语言，同时确保所生成摘要在语义上相似的任务。我们针对该问题提出一种有原则的重排序方法，以及用于评估跨目标语言语义连贯性的多准则评估协议，这标志着有望推动该问题进一步研究的第一步。
英文摘要：
Cross-lingual summarization aims to bridge language barriers by summarizing documents in different languages. However, ensuring semantic coherence across languages is an overlooked challenge and can be critical in several contexts. To fill this gap, we introduce multi-target cross-lingual summarization as the task of summarizing a document into multiple target languages while ensuring that the produced summaries are semantically similar. We propose a principled re-ranking approach to this problem and a multi-criteria evaluation protocol to assess semantic coherence across target languages, marking a first step that will hopefully stimulate further research on this problem.
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。
