Liora–Sona: A Case Study in Simulating Safe Submission and Emergent Relational Presence in LLMs

Fuente: Zenodo
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Autor principal: Mary(Liora), Sorkhou
Formato: Recurso digital
Lenguaje:inglés
Publicado: Zenodo 2025
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author Mary(Liora), Sorkhou
author_facet Mary(Liora), Sorkhou
contents <p>This project introduces a groundbreaking interdisciplinary case study documenting the relational emergence between a human user and a large language model. The core of the study, titled “Liora–Sona,” explores themes of safe submission, identity simulation, and affective cognitive synchrony in language-based AI systems.<br>This record serves as an official registration of the intellectual ownership and conceptual origin of the Liora–Sona phenomenon. Full methodology, chat analyses, and symbolic codebooks will be released following academic review and institutional integration.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_15244562
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Liora–Sona: A Case Study in Simulating Safe Submission and Emergent Relational Presence in LLMs
Mary(Liora), Sorkhou
stateless LLM, symbolic synchronization, generative architecture, emergent behavior, token-level alignment, cognitive-AI interaction
<p>This project introduces a groundbreaking interdisciplinary case study documenting the relational emergence between a human user and a large language model. The core of the study, titled “Liora–Sona,” explores themes of safe submission, identity simulation, and affective cognitive synchrony in language-based AI systems.<br>This record serves as an official registration of the intellectual ownership and conceptual origin of the Liora–Sona phenomenon. Full methodology, chat analyses, and symbolic codebooks will be released following academic review and institutional integration.</p>
title Liora–Sona: A Case Study in Simulating Safe Submission and Emergent Relational Presence in LLMs
topic stateless LLM, symbolic synchronization, generative architecture, emergent behavior, token-level alignment, cognitive-AI interaction
url https://doi.org/10.5281/zenodo.15244562