LimGen: Probing the LLMs for Generating Suggestive Limitations of
  Research Papers
Abdur Rahman Bin Md Faizullah Ashok Urlana Rahul Mishra
Examining limitations is a crucial step in the scholarly research reviewing
process, revealing aspects where a study might lack decisiveness or require
enhancement. This aids readers in considering broader implications for further
research. In this article, we present a novel and challenging task of
Suggestive Limitation Generation (SLG) for research papers. We compile a
dataset called LimGen, encompassing 4068 research papers and their associated
limitations from the ACL anthology. We investigate several approaches to
harness large language models (LLMs) for producing suggestive limitations, by
thoroughly examining the related challenges, practical insights, and potential
opportunities. Our LimGen dataset and code can be accessed at
https://github.com/armbf/LimGen.