Cross-lingual summarization consists of generating a summary in one language
given an input document in a different language, allowing for the dissemination
of relevant content across speakers of other languages. However, this task
remains challenging, mainly because of the need for cross-lingual datasets and
the compounded difficulty of summarizing and translating. This work presents
$\mu$PLAN, an approach to cross-lingual summarization that uses an intermediate
planning step as a cross-lingual bridge. We formulate the plan as a sequence of
entities that captures the conceptualization of the summary, i.e. identifying
the salient content and expressing in which order to present the information,
separate from the surface form. Using a multilingual knowledge base, we align
the entities to their canonical designation across languages. $\mu$PLAN models
first learn to generate the plan and then continue generating the summary
conditioned on the plan and the input. We evaluate our methodology on the
XWikis dataset on cross-lingual pairs across four languages and demonstrate
that this planning objective achieves state-of-the-art performance in terms of
ROUGE and faithfulness scores. Moreover, this planning approach improves the
zero-shot transfer to new cross-lingual language pairs compared to non-planning
baselines.

本文介绍一种名为 μPLAN 的跨语言概括方法，该方法使用中间计划步骤作为跨语言桥梁，通过多语言知识库对计划进行对齐来生成摘要。在针对 XWikis 数据集的评估中，该规划方法通过 ROUGE 和忠实度比分方面取得了最先进的性能，并且比非规划基线提高了零 - shot 转移到新的跨语言语言配对的能力。