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What is Efficient Text Summarization with Transformers about?

The document discusses a novel approach to text summarization using a pre-trained Transformer language model that enhances sample efficiency by utilizing a decoder-only architecture. Experiments on the CNN/Daily Mail dataset demonstrate that this method significantly outperforms traditional encoder-decoder models, achieving a ROUGE-2 score of 13.1 with only 1% of the training data. The findings suggest that this approach could be beneficial for low-resource summarization tasks by effectively leveraging pre-

Author

your.stranger.guy

Language

EN