Self-Supervised and Controlled Multi-Document Opinion Summarization - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

Self-Supervised and Controlled Multi-Document Opinion Summarization

Résumé

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.
Fichier non déposé

Dates et versions

hal-03241932 , version 1 (29-05-2021)

Identifiants

  • HAL Id : hal-03241932 , version 1

Citer

Hady Elsahar, Maximin Coavoux, Jos Rozen, Matthias Gallé. Self-Supervised and Controlled Multi-Document Opinion Summarization. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Apr 2021, Online, Unknown Region. pp.1646--1662. ⟨hal-03241932⟩
59 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More