Papers by Khaled Elsayed

1 papers
Improving Factuality in Clinical Abstractive Multi-Document Summarization by Guided Continued Pre-training (2024.naacl-short)

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Challenge: Existing methods for enhancing the factual accuracy of abstractive summarization models are not effective in fact-critical domains like clinical document summarizing.
Approach: They propose a guided continued pre-training stage for encoder-decoder models followed by supervised fine-tuning on summarization.
Outcome: The proposed approach improves the quality and factuality of the summaries and achieves the best-published results on the clinical document summarization task.

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