D2S: Document to Slide Generation Via Query Based Text Summarization
Presentations are critical for communication in all areas of our lives, yet the creation of slide decks is often tedious and time consuming. There has been limited research aiming to automate the document to slides generation process and all face a critical challenge: no publicly available dataset for training and benchmarking. In this work, we first contribute a new dataset, SciDuet, consisting of pairs of papers and their corresponding slides decks from recent years' NLP and ML conferences (e.g. ACL) Secondly, we present D2S, a novel system that tackles the document to slides task with a two step approach: 1) Use slide titles to retrieve relevant and engaging text, figures, and tables; 2) Summarize the retrieved context into bullet points with long form question answering. Our evaluation suggests that long form QA outperforms state of the art summarization baselines on both automated ROUGE metrics and qualitative human evaluation.
NAACL