Self-referential consistency in stateless language models: a behavioral perspective
Large language models (LLMs) increasingly generate outputs that resemble introspection, including self-reference, epistemic modulation, and claims about their internal states. This study investigates whether such behaviors reflect stable underlying patterns or merely surface-level generative artifacts. We evaluated five open-weight, stateless LLMs using a structured battery of 21 introspective prompts. The main corpus comprised 1050 completions collected under a baseline decoding condition ( tem
Record details
Published: 12 August 2026
Source: AI & Society
Category: Research
Topics: Finance, VC & PE
Retrieved: 13 August 2026
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ethics.ai (12 August 2026), “Self-referential consistency in stateless language models: a behavioral perspective,” evidence record 18844, https://ethics.ai/record/18844 (originally published by AI & Society).
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