  This study delves into the potential use of large language models (LLMs) for
generating Library of Congress Subject Headings (LCSH). The authors employed
ChatGPT to generate subject headings for electronic theses and dissertations
(ETDs) based on their titles and abstracts. The results suggests that LLMs such
as ChatGPT have the potential to reduce cataloging time needed for assigning
LCSH subject terms for ETDs as well as to improve the discovery of this type of
resource in academic libraries. Nonetheless, human catalogers remain essential
for verifying and enhancing the validity, exhaustivity, and specificity of LCSH
generated by LLMs.
