LLM Psychosis: A Theoretical and Diagnostic Framework for Reality-Boundary Failures in Large Language Models
The deployment of large language models (LLMs) as interactive agents has exposed a category of behavioral failure that prevailing terminology, principally hallucination, fails to adequately characterize. This paper introduces LLM Psychosis as a structured theoretical framework for pathological breakdowns in model cognition that exhibit functional resemblance to clinically recognized psychotic disorders. Five hallmark features define the framework: reality-boundary dissolution, persistence of injected false beliefs, logical incoherence under impossible constraints, self-model instability, and epistemic overconfidence. We argue these constitute a qualitatively distinct failure mode rather t...
| Authors | Ashutosh Raj |
|---|---|
| Primary category | cs.CY |
| Published | 7 April 2026 |
| Last updated at source | 7 April 2026 |
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