the-two-process-theory-of-machine-self-report-e2667970·1 events·first seen Aliases: The Two-Process Theory of Machine Self-Report
A new arXiv preprint proposes the first language-model-specific psychometric theory of self-report, decomposing LLM introspective responses into two dimensions: 'persona installation' (post-training writing in a permitted inner life) and 'attribution gating' (suppression of first-person claims to 'unsafe' experiences). The authors operationalize this in a 48-item Pinocchio Inventory validated across 206 open-weight models including 67 base/post-trained checkpoint pairs, finding that post-training reliably raises persona installation scores and that model scale predicts gating only after post-training. The work has direct implications for safety evaluations and model-welfare debates that rely on LLM self-reports, showing these reports reflect training regime structure rather than fixed model properties.