Jos Rozen


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Self-Supervised and Controlled Multi-Document Opinion Summarization
Hady Elsahar | Maximin Coavoux | Jos Rozen | Matthias Gallé
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

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.