  Generic text summarization approaches often fail to address the specific
intent and needs of individual users. Recently, scholarly attention has turned
to the development of summarization methods that are more closely tailored and
controlled to align with specific objectives and user needs. Despite a growing
corpus of controllable summarization research, there is no comprehensive survey
available that thoroughly explores the diverse controllable attributes employed
in this context, delves into the associated challenges, and investigates the
existing solutions. In this survey, we formalize the Controllable Text
Summarization (CTS) task, categorize controllable attributes according to their
shared characteristics and objectives, and present a thorough examination of
existing datasets and methods within each category. Moreover, based on our
findings, we uncover limitations and research gaps, while also exploring
potential solutions and future directions for CTS. We release our detailed
analysis of CTS papers at
https://github.com/ashokurlana/controllable_text_summarization_survey.
