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Leveraging Lead Bias for News Summarization by glory.reji is a document available to read on EtoBox.

The paper proposes a method to leverage lead bias in news articles for pretraining abstractive summarization models, using the top sentences as target summaries. The transformer-based model achieves state-of-the-art results on various datasets without finetuning and outperforms competitive baselines after finetuning. This approach allows for effective summarization without the need for extensive labeled data, making it a significant contribution to the field.

Author
glory.reji
Language
EN