Advancements in Scientific Controllable Text Generation Methods
Arnav Goel, Medha Hira, Avinash Anand, Siddhesh Bangar, Rajiv Ratn, Shah

TL;DR
This paper introduces a new schema for organizing controllable text generation in scientific literature, analyzing modulation strategies and proposing future empirical comparisons to enhance understanding and development.
Contribution
It presents a novel schema with seven components for controllable text generation and discusses modulation strategies, enabling new architecture designs.
Findings
The schema organizes controllable generation components.
Qualitative analysis of modulation strategies.
Future empirical comparisons are suggested.
Abstract
The previous work on controllable text generation is organized using a new schema we provide in this study. Seven components make up the schema, and each one is crucial to the creation process. To accomplish controlled generation for scientific literature, we describe the various modulation strategies utilised to modulate each of the seven components. We also offer a theoretical study and qualitative examination of these methods. This insight makes possible new architectures based on combinations of these components. Future research will compare these methods empirically to learn more about their strengths and utility.
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Taxonomy
TopicsNatural Language Processing Techniques · Semantic Web and Ontologies · Advanced Text Analysis Techniques
