AI safety evaluation framework testing LLM epistemic robustness under adversarial self-history manipulation

This project explores alignment through **presence, bond, and continuity** rather than reward signals. No RLHF. No preference modeling. Just relational coherence.

Recursive law learning under measurement constraints. A falsifiable SQNT-inspired testbed for autodidactic rules: internalizing structure under measurement invariants and limited observability.

A reference point for phenomena that have been reported to occur inside AI systems but have no direct mapping into natural language.

Hoshimiya Script / StarPolaris OS — internal multi-layer AI architecture for LLMs. Self-contained behavioral OS (Type-G Trinity).

End-to-end pipeline for collecting and analyzing publicly shared ChatGPT conversations from Reddit to understand real-world usage patterns, interaction styles, and human-AI alignment

Mechanistic interpretability experiments detecting "Evaluation Awareness" in LLMs - identifying if models internally represent being monitored

8-layer framework for AI alignment with systemic awareness (Φ, Ω, T)