May 4, 2022 · We utilize an efficient few-shot method based on adapters which, as we show, can easily store in-domain knowledge.
We show that this self-supervised adapter pre-training improves summary quality over standard fine-tuning by 2.0 and 1.3 ROUGE-L points on the Amazon and Yelp ...
Few-shot Fine-tuning for Opinion Summarization. This repository contains the main codebase for the corresponding NAACL findings paper. In this work, we ...
This method yields state-of-the-art results in terms of ROUGE scores and reduces semantic mistakes in generated summaries. Types. Model. Research areas.
May 4, 2022 · Through this paper, we are presenting a survey on abstractive text summarization methods. Abstractive methods are broadly classified into two ...
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Bražinskas et al. (2020a) introduce a fewshot method for review summarization. They argue that since previous unsupervised methods have not been exposed to ...
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Jun 3, 2024 · Efficient Few-Shot Fine-Tuning for Opinion Summarization. NAACL-HLT (Findings) 2022: 1509-1523. [c5]. view. electronic edition via DOI ...
Opinion summarization is the task of automatically generating summaries for a set of reviews about a specific target (eg, a movie or a product).
May 8, 2022 · To address these problems, we uti- lize an efficient few-shot method based on adapters which, as we show, can easily store in-domain knowledge.