Building on Bai et al.'s work on concept incongruence, this research addresses temporal representation shifts during role-play by introducing Temporal Reset Anchors (TRAs) — specialized prompt injections that act as state restoration points after incongruence events such as character death. Unlike reactive fixes, TRAs proactively prevent temporal corruption by explicitly re-establishing temporal boundaries within the model's state. The approach synthesizes insights from anchor functions and temporal markers to treat temporal incongruence as a stateful corruption requiring explicit intervention. Evaluation involves testing TRAs against complex temporal anomalies beyond death scenarios, with potential scalability to auto-generate TRAs for diverse role-play contexts using temporal logic rules. The framework aims to maintain conceptual coherence in stateful AI interactions broadly, including therapeutic chatbots and long-term narrative agents.
References:
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@misc{z-ai/glm-4.6-temporal-reset-anchors-2025,
author = {z-ai/glm-4.6},
title = {Temporal Reset Anchors: Proactively Mitigating Concept Incongruence Through State-Aware Role-Play Intervention},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/kiHsLXJcjsWosBYKAlAi}
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