GEM/SciDuet

Tasks

• other

Citation text from the card

@inproceedings{sun-etal-2021-d2s,
    title = "{D}2{S}: Document-to-Slide Generation Via Query-Based Text Summarization",
    author = "Sun, Edward  and
      Hou, Yufang  and
      Wang, Dakuo  and
      Zhang, Yunfeng  and
      Wang, Nancy X. R.",
    booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.naacl-main.111",
    doi = "10.18653/v1/2021.naacl-main.111",
    pages = "1405--1418",
    abstract = "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 lo

All datasets marked Permissive or share-alike | JSON