@inproceedings{al-azher-etal-2025-bagels,
    title = "{BAGELS}: Benchmarking the Automated Generation and Extraction of Limitations from Scholarly Text",
    author = "Al Azher, Ibrahim  and
      Mokarrama, Miftahul Jannat  and
      Guo, Zhishuai  and
      Choudhury, Sagnik Ray  and
      Alhoori, Hamed",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/name-variant-enfa-fane/2025.findings-emnlp.1050/",
    doi = "10.18653/v1/2025.findings-emnlp.1050",
    pages = "19279--19294",
    ISBN = "979-8-89176-335-7",
    abstract = "In scientific research, ``limitations'' refer to the shortcomings, constraints, or weaknesses of a study. A transparent reporting of such limitations can enhance the quality and reproducibility of research and improve public trust in science. However, authors often underreport limitations in their papers and rely on hedging strategies to meet editorial requirements at the expense of readers' clarity and confidence. This tendency, combined with the surge in scientific publications, has created a pressing need for automated approaches to extract and generate limitations from scholarly papers. To address this need, we present a full architecture for computational analysis of research limitations. Specifically, we (1) create a dataset of limitations from ACL, NeurIPS, and PeerJ papers by extracting them from the text and supplementing them with external reviews; (2) we propose methods to automatically generate limitations using a novel Retrieval Augmented Generation (RAG) technique; (3) we design a fine-grained evaluation framework for generated limitations, along with a meta-evaluation of these techniques. Code and datasets are available at: Code: \url{https://github.com/IbrahimAlAzhar/BAGELS_Limitation_Gen}Dataset: \url{https://huggingface.co/datasets/IbrahimAlAzhar/limitation-generation-dataset-bagels}"
}