Abstractive Text Summarization

Abstractive Text Summarization is a task in the field of natural language processing that aims to generate a short and concise summary capable of capturing the core ideas of the source text. Unlike extractive summarization, the summaries produced by this task may contain new phrases and sentences that do not necessarily appear in the original text, thereby conveying key information more flexibly. This technology has significant application value in areas such as news summarization, literature review, and information retrieval.