@inproceedings{wang-etal-2024-towards-human,
    title = "Towards a Human-Computer Collaborative Scientific Paper Lifecycle: A Pilot Study and Hands-On Tutorial",
    author = "Wang, Qingyun  and
      Edwards, Carl  and
      Ji, Heng  and
      Hope, Tom",
    editor = "Klinger, Roman  and
      Okazaki, Naozaki  and
      Calzolari, Nicoletta  and
      Kan, Min-Yen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024): Tutorial Summaries",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-tutorials.10",
    pages = "56--67",
    abstract = "Due to the rapid growth of publications varying in quality, there exists a pressing need to help scientists digest and evaluate relevant papers, thereby facilitating scientific discovery. This creates a number of urgent questions; however, computer-human collaboration in the scientific paper lifecycle is still in the exploratory stage and lacks a unified framework for analyzing the relevant tasks. Additionally, with the recent significant success of large language models (LLMs), they have increasingly played an important role in academic writing. In this cutting-edge tutorial, we aim to provide an all-encompassing overview of the paper lifecycle, detailing how machines can augment every stage of the research process for the scientist, including scientific literature understanding, experiment development, manuscript draft writing, and finally draft evaluation. This tutorial is devised for researchers interested in this rapidly-developing field of NLP-augmented paper writing. The tutorial will also feature a session of hands-on exercises during which participants can guide machines in generating ideas and automatically composing key paper elements. Furthermore, we will address current challenges, explore future directions, and discuss potential ethical issues. A toolkit designed for human-computer collaboration throughout the paper lifecycle will also be made publically available.",
}

Due to the rapid growth of publications varying in quality, there exists a pressing need to help scientists digest and evaluate relevant papers, thereby facilitating scientific discovery. This creates a number of urgent questions; however, computer-human collaboration in the scientific paper lifecycle is still in the exploratory stage and lacks a unified framework for analyzing the relevant tasks. Additionally, with the recent significant success of large language models (LLMs), they have increasingly played an important role in academic writing. In this cutting-edge tutorial, we aim to provide an all-encompassing overview of the paper lifecycle, detailing how machines can augment every stage of the research process for the scientist, including scientific literature understanding, experiment development, manuscript draft writing, and finally draft evaluation. This tutorial is devised for researchers interested in this rapidly-developing field of NLP-augmented paper writing. The tutorial will also feature a session of hands-on exercises during which participants can guide machines in generating ideas and automatically composing key paper elements. Furthermore, we will address current challenges, explore future directions, and discuss potential ethical issues. A toolkit designed for human-computer collaboration throughout the paper lifecycle will also be made publically available.
Wang, Qingyun Edwards, Carl Ji, Heng Hope, Tom
Towards a Human-Computer Collaborative Scientific Paper Lifecycle: A Pilot Study and Hands-On Tutorial