Dec 9, 2022 · This work surveys the scientific literature to explore and analyze recent research on pre-trained language models and abstractive text summarization utilizing ...
This work surveys the scientific literature to explore and analyze recent research on pre-trained language models and abstractive text summarization utilizing ...
Dec 22, 2024 · This survey examines the state of the art in text summarization models, with a specific focus on the abstractive summarization approach. It ...
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A Survey of Abstractive Text Summarization Utilising Pretrained Language Models. Ayesha Ayub Syed, Ford Lumban Gaol, Alfred Boediman, Tokuro Matsuo, ...
This paper provides researchers with a comprehensive survey of DL-based abstractive summarization.
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Dec 22, 2024 · Transformer-based models like BERT [12], BART [6], PEGASUS [7], have demonstrated improved performance not only in text summarization but across ...
This paper utilized PLTMs (Pre-Trained Language Models) from the transformer architecture, namely T5. (Text-to-Text Transfer Transformer) which has been ...
Oct 28, 2024 · We categorize the techniques into traditional sequence-to-sequence models, pre-trained large language models, reinforcement learning, ...
Mar 24, 2024 · The research reviews the major advancements in neural network (NN) architectures and pre-trained language models applied to abstractive ...
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Jul 15, 2024 · Abstract. Text summarization using pre-trained encoders has become a crucial technique for efficiently managing large volumes of text data.
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