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Paranoid transformer: Reading narrative of madness as computational approach to creativity
Future Internet. 2020. Vol. 12. No. 11. Article 182.
Agafonova Y., Tikhonov A., Ivan P. Yamshchikov
This paper revisits the receptive theory in the 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.
Research target:
Computer Science
Mathematics
Philosophy, Ethics, and Religious Studies
Philology and Linguistics
Language:
English
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Ponomarenko A., / Series Computer Science "arxiv.org". 2025.
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A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
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