@inproceedings{kumar-etal-2024-longform,
    title = "Longform Multimodal Lay Summarization of Scientific Papers: Towards Automatically Generating Science Blogs from Research Articles",
    author = "Kumar, Sandeep  and
      Kohli, Guneet Singh  and
      Ghosal, Tirthankar  and
      Ekbal, Asif",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.942",
    pages = "10790--10801",
    abstract = "Science communication, in layperson{'}s terms, is essential to reach the general population and also maximize the impact of underlying scientific research. Hence, good science blogs and journalistic reviews of research articles are so well-read and critical to conveying science. Scientific blogging goes beyond traditional research summaries, offering experts a platform to articulate findings in layperson{'}s terms. It bridges the gap between intricate research and its comprehension by the general public, policymakers, and other researchers. Amid the rapid expansion of scientific data and the accelerating pace of research, credible science blogs serve as vital artifacts for evidence-based information to the general non-expert audience. However, writing a scientific blog or even a short lay summary requires significant time and effort. Here, we are intrigued \textit{what if the process of writing a scientific blog based on a given paper could be semi-automated to produce the first draft?} In this paper, we introduce a novel task of Artificial Intelligence (AI)-based science blog generation from a research article. We leverage the idea that presentations and science blogs share a symbiotic relationship in their aim to clarify and elucidate complex scientific concepts. Both rely on visuals, such as figures, to aid comprehension. With this motivation, we \textit{create a new dataset of science blogs} using the presentation transcript and the corresponding slides. We create a dataset containing a paper{'}s presentation transcript and figures annotated from nearly 3000 papers. We then propose a multimodal attention model to generate a blog text and select the most relevant figures to explain a research article in layperson{'}s terms, essentially a science blog. Our experimental results with respect to both automatic and human evaluation metrics show the effectiveness of our proposed approach and the usefulness of our proposed dataset.",
}

Science communication, in layperson{'}s terms, is essential to reach the general population and also maximize the impact of underlying scientific research. Hence, good science blogs and journalistic reviews of research articles are so well-read and critical to conveying science. Scientific blogging goes beyond traditional research summaries, offering experts a platform to articulate findings in layperson{'}s terms. It bridges the gap between intricate research and its comprehension by the general public, policymakers, and other researchers. Amid the rapid expansion of scientific data and the accelerating pace of research, credible science blogs serve as vital artifacts for evidence-based information to the general non-expert audience. However, writing a scientific blog or even a short lay summary requires significant time and effort. Here, we are intrigued \textit{what if the process of writing a scientific blog based on a given paper could be semi-automated to produce the first draft?} In this paper, we introduce a novel task of Artificial Intelligence (AI)-based science blog generation from a research article. We leverage the idea that presentations and science blogs share a symbiotic relationship in their aim to clarify and elucidate complex scientific concepts. Both rely on visuals, such as figures, to aid comprehension. With this motivation, we \textit{create a new dataset of science blogs} using the presentation transcript and the corresponding slides. We create a dataset containing a paper{'}s presentation transcript and figures annotated from nearly 3000 papers. We then propose a multimodal attention model to generate a blog text and select the most relevant figures to explain a research article in layperson{'}s terms, essentially a science blog. Our experimental results with respect to both automatic and human evaluation metrics show the effectiveness of our proposed approach and the usefulness of our proposed dataset.
Kumar, S eep Kohli, Guneet Singh Ghosal, Tirthankar Ekbal, Asif
Longform Multimodal Lay Summarization of Scientific Papers: Towards Automatically Generating Science Blogs from Research Articles