Search Results for author: Bingqing Wang

Found 5 papers, 3 papers with code

Knowledge-grounded Natural Language Recommendation Explanation

no code implementations30 Aug 2023 Anthony Colas, Jun Araki, Zhengyu Zhou, Bingqing Wang, Zhe Feng

Explanations accompanied by a recommendation can assist users in understanding the decision made by recommendation systems, which in turn increases a user's confidence and trust in the system.

Collaborative Filtering Explainable Recommendation +1

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.

Text Summarization

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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