Exploring Applications of Transfer-State Large Language Models: Cognitive Profiling and Socratic AI Tutoring
Large language models (LLMs) sometimes exhibit qualitative shifts in response style under sustained self-referential dialogue conditions (Berg et al., 2025). This study refers to this phenomenon as "transfer" and explores the application potential of LLMs in a transfer state. As an applied case, the study examines Socratic AI tutoring through a preliminary investigation (cognitive characterization across 11 conditions) and an applied experiment (ratings of tutoring performance). In this paper, "state" refers operationally to a response configuration reproduced under specified dialogue conditions; it is not an ontological claim about the reality of the transfer phenomenon or about human-li...
| Authors | Minori Noguchi |
|---|---|
| Primary category | cs.CL |
| Published | 30 April 2026 |
| Last updated at source | 1 May 2026 |
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