PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India

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

Submission Type: Regular Long Paper

Submission Track: Resources and Evaluation

Submission Track 2: Summarization

Keywords: multilingual, cross-lingual, summarization, dataset, benchmark, languages in India

TL;DR: We propose a summarization dataset for languages in India which provides the current widest language pair coverage.

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.

Submission Number: 395