PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India
Ashok Urlana, Pinzhen Chen, Zheng Zhao, Shay Cohen, Manish Shrivastava, Barry Haddow
Abstract
This paper introduces PMIndiaSum, a multilingual and massively parallel summarization corpus focused on languages in India. Our corpus provides a training and testing ground for four language families, 14 languages, and the largest to date with 196 language pairs. We detail our construction workflow including data acquisition, processing, and quality assurance. Furthermore, we publish benchmarks for monolingual, cross-lingual, and multilingual summarization by fine-tuning, prompting, as well as translate-and-summarize. Experimental results confirm the crucial role of our data in aiding summarization between Indian languages. Our dataset is publicly available and can be freely modified and re-distributed.- Anthology ID:
- 2023.findings-emnlp.777
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 11606–11628
- Language:
- URL:
- https://aclanthology.org/2023.findings-emnlp.777
- DOI:
- 10.18653/v1/2023.findings-emnlp.777
- Cite (ACL):
- Ashok Urlana, Pinzhen Chen, Zheng Zhao, Shay Cohen, Manish Shrivastava, and Barry Haddow. 2023. PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 11606–11628, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India (Urlana et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.findings-emnlp.777.pdf