Summarization is (Almost) Dead

I can't help but smile :-).

Checkout this paper. It evaluates the zero-shot summarization capabilities of large language models (LLMs) across five tasks: single-news, multi-news, dialogue, source code, and cross-lingual summarization. Through human evaluations, the researchers found that LLM summaries were significantly preferred to human-written references and fine-tuned model summaries. Analyses revealed that LLM summaries exhibited better factual consistency with fewer hallucinations. Given the strong performance of LLMs, the researchers argue that most prior work in text summarization may no longer be necessary. However, they note opportunities remain in developing higher-quality test datasets and more reliable evaluation methods. Overall, the findings suggest that LLMs have substantially advanced the state of text summarization. Read the entire paper.