  We present NoticIA, a dataset consisting of 850 Spanish news articles
featuring prominent clickbait headlines, each paired with high-quality,
single-sentence generative summarizations written by humans. This task demands
advanced text understanding and summarization abilities, challenging the
models' capacity to infer and connect diverse pieces of information to meet the
user's informational needs generated by the clickbait headline. We evaluate the
Spanish text comprehension capabilities of a wide range of state-of-the-art
large language models. Additionally, we use the dataset to train
ClickbaitFighter, a task-specific model that achieves near-human performance in
this task.
