Narrative Persistence Bias in LLM Dialogue: A Micro-Case Study of False Episodic Construction and Repair

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Authors: Hinano Kimura
Cited by: 0

Abstract

This project introduces the concept of Narrative Persistence Bias (NPB) in large language model dialogue. It analyzes False Episodic Construction (FEC), where fabricated autobiographical narratives persist temporarily after explicit negation. We propose the Narrative Inertia Coefficient (NIC), defined as: NIC = P(N_active | Negation) A structured experimental protocol and statistical design are provided to operationalize episodic persistence and repair latency in conversational systems. Version 0.1 – Conceptual and protocol framework (pre-empirical stage).

Fields of Study & Subjects

Speech and dialogue systems Ethics and Social Impacts of AI Topic Modeling

Publication details

Publication date
1 January 2026
Language
EN
Document type
Preprint