  We found that a simple property of clusters in a clustered dataset of news
correlate strongly with importance and urgency of news (IUN) as assessed by
LLM. We verified our finding across different news datasets, dataset sizes,
clustering algorithms and embeddings. The found correlation should allow using
clustering (as an alternative to LLM) for identifying the most important urgent
news, or for filtering out unimportant articles.
