Exploring Controllable Text Generation Techniques
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by
Shrimai Prabhumoye, Alan W Black, Ruslan Salakhutdinov
2020
Abstract
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.
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