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Inverse Reinforcement Learning for Text Summarization
Yu Fu, Deyi Xiong, Yue Dong
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Faithful to the Document or to the World? Mitigating Hallucinations via Entity-linked Knowledge in Abstractive Summarization
Despite recent advances in abstractive summarization, current summarization systems still suffer from content hallucinations where …
Yue Dong, John Wieting, Pat Verga
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Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization
State-of-the-art abstractive summarization systems often generate hallucinations; i.e., content that is not directly inferable from the …
Meng Cao, Yue Dong, Jackie Cheung
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Learning with Rejection for Abstractive Text Summarization
State-of-the-art abstractive summarization systems frequently hallucinate content that is not supported by the source document, mainly …
Meng Cao, Yue Dong, Jingyi He, Jackie Cheung
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Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Faceted summarization provides briefings of a document from different perspectives. Readers can quickly comprehend the main points of a …
Rui Meng, khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
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On-the-Fly Attention Modulation for Neural Generation
Despite considerable advancements with deep neural language models (LMs), neural text generation still suffers from degeneration: the …
Yue Dong, Chandra Bhagavatula, Ximing Lu, Jena D. Hwang, Antoine Bosselut, Jackie Chi Kit Cheung, Yejin Choi
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Discourse-Aware Unsupervised Summarization of Long Scientific Documents
We propose an unsupervised graph-based ranking model for extractive summarization of long scientific documents. Our method assumes a …
Yue Dong, Andrei Mircea, Jackie Chi Kit Cheung
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Factual Error Correction for Abstractive Summarization Models
Neural abstractive summarization systems have achieved promising progress, thanks to the availability of large-scale datasets and …
Meng Cao, Yue Dong, Jiapeng Wu, Jackie Chi Kit Cheung
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Multi-Fact Correction in Abstractive Text Summarization
Pre-trained neural abstractive summarization systems have dominated extractive strategies on news summarization performance, at least …
Yue Dong, Shuohang Wang, Zhe Gan, Yu Cheng, Jackie Chi Kit Cheung, Jingjing Liu
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Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
Multi-document summarization is a challenging task for which there exists little large-scale datasets. We propose Multi-XScience, a …
Yao Lu, Yue Dong, Laurent Charlin
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