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.

In this work, we refine the centroid method even further: i) we utilize multilingual sentence embeddings Multi-document summarization (MDS) addresses to enable summarization of clusters of the need to condense content from multiple source documents in various languages; ii) we employ documents into concise and coherent summaries beam search for sentence selection, leading to a while preserving the essential context and meaning.