We present V\=arta, a large-scale multilingual dataset for headline
generation in Indic languages. This dataset includes 41.8 million news articles
in 14 different Indic languages (and English), which come from a variety of
high-quality sources. To the best of our knowledge, this is the largest
collection of curated articles for Indic languages currently available. We use
the data collected in a series of experiments to answer important questions
related to Indic NLP and multilinguality research in general. We show that the
dataset is challenging even for state-of-the-art abstractive models and that
they perform only slightly better than extractive baselines. Owing to its size,
we also show that the dataset can be used to pretrain strong language models
that outperform competitive baselines in both NLU and NLG benchmarks.

Varta 是一个大规模的多语言数据集，用于生成印度语言的标题。该数据集包含 14 种不同的印度语言（以及英语）的 4180 万篇新闻文章，是目前可用的经过精心筛选的印度语言文章的最大集合。该数据集可以用于预训练强大的语言模型，其表现优于竞争基线，在 NLU 和 NLG 基准测试中均表现出色。