PMIndiaSum: Multilingual and cross-lingual headline summarization for languages in India

Ashok Urlana; Pinzhen Chen; Zheng Zhao; Shay Cohen; Manish Shrivastava; Barry Haddow

doi:10.18653/v1/2023.findings-emnlp.777

PMIndiaSum: Multilingual and cross-lingual headline summarization for languages in India

Ashok Urlana
, Pinzhen Chen
, Zheng Zhao
, Shay Cohen
, Manish Shrivastava
, Barry Haddow

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

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.

Original language	English
Title of host publication	Findings of the Association for Computational Linguistics: EMNLP 2023
Editors	Houda Bouamor, Juan Pino, Kalika Bali
Place of Publication	Singapore
Publisher	Association for Computational Linguistics
Pages	11606-11628
Number of pages	23
ISBN (Electronic)	9798891760615
DOIs	https://doi.org/10.18653/v1/2023.findings-emnlp.777
Publication status	Published - 01 Dec 2023
Externally published	Yes

Access to Document

10.18653/v1/2023.findings-emnlp.777Licence: CC BY

Multilingual and cross-lingual headline summarization for languages in India
© 2023 The Authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
Final published version, 596 KBLicence: CC BY

Cite this

Urlana, A., Chen, P., Zhao, Z., Cohen, S., Shrivastava, M., & Haddow, B. (2023). PMIndiaSum: Multilingual and cross-lingual headline summarization for languages in India. In H. Bouamor, J. Pino, & K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 11606-11628). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.777

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Urlana, A, Chen, P, Zhao, Z, Cohen, S, Shrivastava, M & Haddow, B 2023, PMIndiaSum: Multilingual and cross-lingual headline summarization for languages in India. in H Bouamor, J Pino & K Bali (eds), Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics, Singapore, pp. 11606-11628. https://doi.org/10.18653/v1/2023.findings-emnlp.777

PMIndiaSum: Multilingual and cross-lingual headline summarization for languages in India. / Urlana, Ashok; Chen, Pinzhen; Zhao, Zheng et al.
Findings of the Association for Computational Linguistics: EMNLP 2023. ed. / Houda Bouamor; Juan Pino; Kalika Bali. Singapore: Association for Computational Linguistics, 2023. p. 11606-11628.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Urlana A, Chen P, Zhao Z, Cohen S, Shrivastava M, Haddow B. PMIndiaSum: Multilingual and cross-lingual headline summarization for languages in India. In Bouamor H, Pino J, Bali K, editors, Findings of the Association for Computational Linguistics: EMNLP 2023. Singapore: Association for Computational Linguistics. 2023. p. 11606-11628 doi: 10.18653/v1/2023.findings-emnlp.777