---
abstract: 'Neural controllable text generation is an important area gaining attention due to its plethora of applications. In this work, we provide a new schema of the pipeline of the generation process by classifying it into five modules. We present an overview of the various techniques used to modulate each of these five modules to provide with control of attributes in the generation process. We also provide an analysis on the advantages and disadvantages of these techniques and open paths to develop new architectures based on the combination of the modules described in this paper.'
author:
- |
    Shrimai Prabhumoye, Alan W Black, Ruslan Salakhutdinov\
    School of Computer Science\
    Carnegie Mellon University\
    Pittsburgh, PA, USA\
    `sprabhum, awb, rsalakhu@cs.cmu.edu`\
bibliography:
- 'acl2020.bib'
title: Exploring Controllable Text Generation Techniques
---

Introduction
============

Controllable text generation is the task of generating realistic sentences whose attributes can be controlled. The attributes to control can range from being stylistic such politeness, sentiment, formality, etc.; demographic attributes of the person writing the text such as gender, age, etc.; content such as information, keywords, entities, etc to be generated, ordering of information, events, like plot summaries etc. Controlling various attributes of text generation has manifold applications. 