  The introduction of large language models (LLMs) has advanced natural
language processing (NLP), but their effectiveness is largely dependent on
pre-training resources. This is especially evident in low-resource languages,
such as Sinhala, which face two primary challenges: the lack of substantial
training data and limited benchmarking datasets. In response, this study
introduces NSINA, a comprehensive news corpus of over 500,000 articles from
popular Sinhala news websites, along with three NLP tasks: news media
identification, news category prediction, and news headline generation. The
release of NSINA aims to provide a solution to challenges in adapting LLMs to
Sinhala, offering valuable resources and benchmarks for improving NLP in the
Sinhala language. NSINA is the largest news corpus for Sinhala, available up to
date.
