TY - JOUR AU - Lin, Hui AU - Ng, Vincent PY - 2019/07/17 Y2 - 2024/03/28 TI - Abstractive Summarization: A Survey of the State of the Art JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 33 IS - 01 SE - Senior Member Presentation Track: Summary Talks DO - 10.1609/aaai.v33i01.33019815 UR - https://ojs.aaai.org/index.php/AAAI/article/view/5056 SP - 9815-9822 AB - <p>The focus of automatic text summarization research has exhibited a gradual shift from extractive methods to abstractive methods in recent years, owing in part to advances in neural methods. Originally developed for machine translation, neural methods provide a viable framework for obtaining an abstract representation of the meaning of an input text and generating informative, fluent, and human-like summaries. This paper surveys existing approaches to abstractive summarization, focusing on the recently developed neural approaches.</p> ER -