Don’t Give Me The Details, Just The Summary! Topic-aware Convolutional Neural Networks For Extreme Summarization | Awesome LLM Papers Add your paper to Awesome LLM Papers

Don't Give Me The Details, Just The Summary! Topic-aware Convolutional Neural Networks For Extreme Summarization

Shashi Narayan, Shay B. Cohen, Mirella Lapata . Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing 2018 – 365 citations

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Datasets EMNLP Interdisciplinary Approaches Model Architecture Neural Machine Translation Variational Autoencoders

We introduce extreme summarization, a new single-document summarization task which does not favor extractive strategies and calls for an abstractive modeling approach. The idea is to create a short, one-sentence news summary answering the question “What is the article about?”. We collect a real-world, large-scale dataset for this task by harvesting online articles from the British Broadcasting Corporation (BBC). We propose a novel abstractive model which is conditioned on the article’s topics and based entirely on convolutional neural networks. We demonstrate experimentally that this architecture captures long-range dependencies in a document and recognizes pertinent content, outperforming an oracle extractive system and state-of-the-art abstractive approaches when evaluated automatically and by humans.

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