# Paranoid Transformer: Reading Narrative of Madness as Computational Approach to Creativity

arXiv: https://arxiv.org/abs/2007.06290 · HTML: https://mlsanity.com/paper/2007.06290/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jul 2020.

## Built on by (most cited first, 8 of 8)

- [Human Evaluation of Creative NLG Systems: An Interdisciplinary Survey on Recent Papers](https://mlsanity.com/paper/2108.00308/) (2021)
- [Humor Mechanics: Advancing Humor Generation with Multistep Reasoning](https://mlsanity.com/paper/2405.07280/) (2024)
- [StoryDB: Broad Multi-language Narrative Dataset](https://mlsanity.com/paper/2109.14396/) (2021)
- [DYPLODOC: Dynamic Plots for Document Classification](https://mlsanity.com/paper/2107.12226/) (2021)
- [What is Wrong with Language Models that Can Not Tell a Story?](https://mlsanity.com/paper/2211.05044/) (2022)
- [Actionable Entities Recognition Benchmark for Interactive Fiction](https://mlsanity.com/paper/2109.13855/) (2021)
- [Machine Apophenia: The Kaleidoscopic Generation of Architectural Images](https://mlsanity.com/paper/2407.09172/) (2024)
- [lmfaoooo at SemEval-2026 Task 1: Humor Is an Audience. Preference Modeling for Constrained Humor Generation](https://mlsanity.com/paper/2606.00022/) (2026)

## Abstract (arXiv)

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.