Generating Wikipedia by Summarizing Long Sequences

Understand

We show that generating English Wikipedia articles can be approached as a multi- document summarization of source documents.

• We use extractive summarization to coarsely identify salient information and a neural abstractive model to generate the article.
• For the abstractive model, we introduce a decoder-only architecture that can scalably attend to very long sequences, much longer than typical encoder- decoder architectures used in sequence transduction.
• We show that this model can generate fluent, coherent multi-sentence paragraphs and even whole Wikipedia articles.