Multi-Target Cross-Lingual Summarization: a novel task and a language-neutral approach
Abstract: 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.
Paper Type: Long
Research Area: Summarization
Research Area Keywords: abstractive summarization, multilingual summarization, cross-lingual summarization
Contribution Types: NLP engineering experiment, Publicly available software and/or pre-trained models, Data resources, Theory
Languages Studied: Arabic, Chinese, English, French, Portuguese, Russian, Spanish
Submission Number: 1392
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