Exploring Controllable Text Generation Techniques
This work provides a structured overview for researchers in text generation, but it is incremental as it synthesizes existing techniques without introducing new methods or data.
The paper tackles the lack of a unifying framework in neural controllable text generation by proposing a new schema that classifies the generation pipeline into five modules, analyzing techniques for modulating them and suggesting ways to develop new architectures.
Neural controllable text generation is an important area gaining attention due to its plethora of applications. Although there is a large body of prior work in controllable text generation, there is no unifying theme. In this work, we provide a new schema of the pipeline of the generation process by classifying it into five modules. The control of attributes in the generation process requires modification of these modules. We present an overview of different techniques used to perform the modulation of these modules. We also provide an analysis on the advantages and disadvantages of these techniques. We further pave ways to develop new architectures based on the combination of the modules described in this paper.