Search Results for author: Bingqing Wang

Found 2 papers, 2 papers with code

A New Approach to Overgenerating and Scoring Abstractive Summaries

1 code implementation NAACL 2021 Kaiqiang Song, Bingqing Wang, Zhe Feng, Fei Liu

We propose a new approach to generate multiple variants of the target summary with diverse content and varying lengths, then score and select admissible ones according to users' needs.

Controlling the Amount of Verbatim Copying in Abstractive Summarization

1 code implementation23 Nov 2019 Kaiqiang Song, Bingqing Wang, Zhe Feng, Liu Ren, Fei Liu

In this paper, we present a neural summarization model that, by learning from single human abstracts, can produce a broad spectrum of summaries ranging from purely extractive to highly generative ones.

Abstractive Text Summarization Language Modelling

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