A Neural Attention Model for Abstractive Sentence Summarization [article]

Alexander M. Rush, Sumit Chopra, Jason Weston
2015 arXiv   pre-print
Summarization based on text extraction is inherently limited, but generation-style abstractive methods have proven challenging to build. In this work, we propose a fully data-driven approach to abstractive sentence summarization. Our method utilizes a local attention-based model that generates each word of the summary conditioned on the input sentence. While the model is structurally simple, it can easily be trained end-to-end and scales to a large amount of training data. The model shows
more » ... icant performance gains on the DUC-2004 shared task compared with several strong baselines.
arXiv:1509.00685v2 fatcat:35wuwlmxjretvbvwhthmgvzsfm