Document (#43775)

Author

Liu, P.J.
Saleh, M.
Pot, E.
Goodrich, B.
Sepassi, R.
Kaiser, L.
Shazeer, N.

Title

Generating Wikipedia by summarizing long sequences

Issue

[30.01.2018].

Source

https://arxiv.org/abs/1801.10198

Year

2018

Abstract

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. When given reference documents, we show it can extract relevant factual information as reflected in perplexity, ROUGE scores and human evaluations.

Content

Vgl.: https://doi.org/10.48550/arXiv.1801.10198.

Theme

Computerlinguistik

Object

GPT-3
Wikipedia

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