PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India
This provides a valuable dataset and benchmarks for researchers working on multilingual and cross-lingual summarization for Indian languages, though it's incremental in expanding existing multilingual corpus approaches to this specific region.
The paper introduces PMIndiaSum, a multilingual summarization corpus covering 14 Indian languages with 196 language pairs, and demonstrates through experiments that this data significantly improves summarization performance between Indian languages.
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.