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.- Anthology ID:
- 2024.findings-emnlp.755
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2024
- Month:
- November
- Year:
- 2024
- Address:
- Miami, Florida, USA
- Editors:
- Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 12908–12924
- Language:
- URL:
- https://preview.aclanthology.org/icon-24-ingestion/2024.findings-emnlp.755/
- DOI:
- 10.18653/v1/2024.findings-emnlp.755
- Cite (ACL):
- Diogo Pernes, Gonçalo M. Correia, and Afonso Mendes. 2024. Multi-Target Cross-Lingual Summarization: a novel task and a language-neutral approach. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 12908–12924, Miami, Florida, USA. Association for Computational Linguistics.
- Cite (Informal):
- Multi-Target Cross-Lingual Summarization: a novel task and a language-neutral approach (Pernes et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/icon-24-ingestion/2024.findings-emnlp.755.pdf