@inproceedings{bandyopadhyay-etal-2024-enhancing-presentation,
    title = "Enhancing Presentation Slide Generation by {LLM}s with a Multi-Staged End-to-End Approach",
    author = "Bandyopadhyay, Sambaran  and
      Maheshwari, Himanshu  and
      Natarajan, Anandhavelu  and
      Saxena, Apoorv",
    editor = "Mahamood, Saad  and
      Minh, Nguyen Le  and
      Ippolito, Daphne",
    booktitle = "Proceedings of the 17th International Natural Language Generation Conference",
    month = sep,
    year = "2024",
    address = "Tokyo, Japan",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.inlg-main.18/",
    pages = "222--229",
    abstract = "Generating presentation slides from a long document with multimodal elements such as text and images is an important task. This is time consuming and needs domain expertise if done manually. Existing approaches for generating a rich presentation from a document are often semi-automatic or only put a flat summary into the slides ignoring the importance of a good narrative. In this paper, we address this research gap by proposing a multi-staged end-to-end model which uses a combination of LLM and VLM. We have experimentally shown that compared to applying LLMs directly with state-of-the-art prompting, our proposed multi-staged solution is better in terms of automated metrics and human evaluation."
}