Apprentices to Research Assistants: Advancing Research with Large
  Language Models
M. Namvarpour A. Razi
Large Language Models (LLMs) have emerged as powerful tools in various
research domains. This article examines their potential through a literature
review and firsthand experimentation. While LLMs offer benefits like
cost-effectiveness and efficiency, challenges such as prompt tuning, biases,
and subjectivity must be addressed. The study presents insights from
experiments utilizing LLMs for qualitative analysis, highlighting successes and
limitations. Additionally, it discusses strategies for mitigating challenges,
such as prompt optimization techniques and leveraging human expertise. This
study aligns with the 'LLMs as Research Tools' workshop's focus on integrating
LLMs into HCI data work critically and ethically. By addressing both
opportunities and challenges, our work contributes to the ongoing dialogue on
their responsible application in research.