Vārta: A Large-Scale Headline-Generation Dataset for Indic Languages
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
BeliN: A Novel Corpus for Bengali Religious News Headline Generation using Contextual Feature Fusion
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
Remember Past, Anticipate Future: Learning Continual Multimodal Misinformation Detectors
Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
Characterizing Linguistic Shifts in Croatian News via Diachronic Word Embeddings
How Grounded is Wikipedia? A Study on Structured Evidential Support
토론
이 논문과 연결된 포럼 글이 아직 없습니다.