Paranoid Transformer: Reading Narrative of Madness as Computational Approach to Creativity
Computation and Language
2022-11-15 v1 Artificial Intelligence
Computers and Society
Abstract
This papers revisits the receptive theory in context of computational creativity. It presents a case study of a Paranoid Transformer - a fully autonomous text generation engine with raw output that could be read as the narrative of a mad digital persona without any additional human post-filtering. We describe technical details of the generative system, provide examples of output and discuss the impact of receptive theory, chance discovery and simulation of fringe mental state on the understanding of computational creativity.
Cite
@article{arxiv.2007.06290,
title = {Paranoid Transformer: Reading Narrative of Madness as Computational Approach to Creativity},
author = {Yana Agafonova and Alexey Tikhonov and Ivan P. Yamshchikov},
journal= {arXiv preprint arXiv:2007.06290},
year = {2022}
}