Khaled Elsayed

Improving Factuality in Clinical Abstractive Multi-Document Summarization by Guided Continued Pre-training

Factual accuracy is an important property of neural abstractive summarization models, especially in fact-critical domains such as the clinical literature. In this work, we introduce a guided continued pre-training stage for encoder-decoder models that improves their understanding of the factual attr…