Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects -- A Survey

TL;DR

This survey comprehensively reviews controllable text summarization, categorizing attributes, analyzing datasets and methods, and identifying challenges, limitations, and future research directions in the field.

Contribution

It formalizes the CTS task, categorizes controllable attributes, and provides a thorough analysis of existing datasets and methods, highlighting research gaps and future prospects.

Findings

Categorization of controllable attributes based on shared characteristics.

Analysis of datasets and methods used in CTS research.

Identification of limitations and future research directions.

Abstract

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.