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        <title>Self-Supervised and Controlled Multi-Document Opinion Summarization</title>
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    <abstract>We address the problem of unsupervised abstractive summarization of collections of user generated reviews through self-supervision and control. We propose a self-supervised setup that considers an individual document as a target summary for a set of similar documents. This setting makes training simpler than previous approaches by relying only on standard log-likelihood loss and mainstream models. We address the problem of hallucinations through the use of control codes, to steer the generation towards more coherent and relevant summaries.</abstract>
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%0 Conference Proceedings
%T Self-Supervised and Controlled Multi-Document Opinion Summarization
%A Elsahar, Hady
%A Coavoux, Maximin
%A Rozen, Jos
%A Gallé, Matthias
%Y Merlo, Paola
%Y Tiedemann, Jorg
%Y Tsarfaty, Reut
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F elsahar-etal-2021-self
%X We address the problem of unsupervised abstractive summarization of collections of user generated reviews through self-supervision and control. We propose a self-supervised setup that considers an individual document as a target summary for a set of similar documents. This setting makes training simpler than previous approaches by relying only on standard log-likelihood loss and mainstream models. We address the problem of hallucinations through the use of control codes, to steer the generation towards more coherent and relevant summaries.
%R 10.18653/v1/2021.eacl-main.141
%U https://aclanthology.org/2021.eacl-main.141/
%U https://doi.org/10.18653/v1/2021.eacl-main.141
%P 1646-1662

Markdown (Informal)

[Self-Supervised and Controlled Multi-Document Opinion Summarization](https://aclanthology.org/2021.eacl-main.141/) (Elsahar et al., EACL 2021)

• Self-Supervised and Controlled Multi-Document Opinion Summarization (Elsahar et al., EACL 2021)

ACL

• Hady Elsahar, Maximin Coavoux, Jos Rozen, and Matthias Gallé. 2021. Self-Supervised and Controlled Multi-Document Opinion Summarization. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 1646–1662, Online. Association for Computational Linguistics.