mlsanityData to 14 Oct 2026

V=arta: A Large-Scale Headline-Generation Dataset for Indic Languages

arXiv 2305.05858 ↗First posted 10 May 2023cs.CLcited by 8

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Abstract (arXiv)

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.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 18 of its 49 references that are in the map. First posted on arXiv 10 May 2023.

Builds on

18 of 49 references.

References · 18

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  4. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
  5. 2018Datasheets for Datasetscited by 1,386
  6. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,317
  7. 2019PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationcited by 1,102
  8. 2018Adafactor: Adaptive Learning Rates with Sublinear Memory Costcited by 905
  9. 2016Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyondcited by 812
  10. 2015A Neural Attention Model for Abstractive Sentence Summarizationcited by 396
  11. 2021XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languagescited by 347
  12. 2016SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documentscited by 246
6 more
  1. 2019Leveraging Pre-trained Checkpoints for Sequence Generation Taskscited by 182
  2. 2020MLSUM: The Multilingual Summarization Corpuscited by 121
  3. 2022IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languagescited by 42
  4. 2021IndicBART: A Pre-trained Model for Indic Natural Language Generationcited by 39
  5. 2021Focus Attention: Promoting Faithfulness and Diversity in Summarizationcited by 30
  6. 2021Minimax and Neyman-Pearson Meta-Learning for Outlier Languagescited by 10

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 2; 2025: 3; 2026: 1.

8 papers.

  1. 2024SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languagescited by 16
  2. 2023PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in Indiacited by 11
  3. 2024Text Generation Models for Luxembourgish with Limited Data: A Balanced Multilingual Strategycited by 7
  4. 2026Beyond LLM-as-a-Judge: Deterministic Metrics for Multilingual Generative Text Evaluationcited by 3
  5. 2023Sequence-to-Sequence Spanish Pre-trained Language Modelscited by 2
  6. 2025COSMMIC: Comment-Sensitive Multimodal Multilingual Indian Corpus for Summarization and Headline Generationcited by 2
  7. 2025BeliN: A Novel Corpus for Bengali Religious News Headline Generation using Contextual Feature Fusioncited by 1
  8. 2025AKCIT-FN at CheckThat! 2025: Switching Fine-Tuned SLMs and LLM Prompting for Multilingual Claim Normalizationcited by 0