Ai-assisted text composition for automated content authoring using transformer-based language models

Abstract

In this paper, we introduce a hybrid method that combines the use of Controllable Text Generation (CTG) approach via Large Language Models (LLMs), fine-tuned language models and sentence transformers in a single framework to generate real-author styled articles in Turkish language. As such, we seek to exemplify hybrid solutions that produce real-human styled high-quality contents, given limited resources and relatively short text prompts as inputs. To achieve this, we introduce a novel method to assemble an author-specific article in different coherence and fluency levels, based on phrasal control of the CTG process. Control phrases are automatically assembled based on a semantic correlation measure calculated using sentence embed dings corresponding to author articles, that are obtained from pre-trained sentence transformers.