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Vārta: A Large-Scale Headline-Generation Dataset for Indic Languages (2305.05858v1)

Published 10 May 2023 in cs.CL

Abstract: 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 LLMs that outperform competitive baselines in both NLU and NLG benchmarks.

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Authors (4)
  1. Rahul Aralikatte (24 papers)
  2. Ziling Cheng (5 papers)
  3. Sumanth Doddapaneni (16 papers)
  4. Jackie Chi Kit Cheung (57 papers)
Citations (7)