August 11, 2026
IEEE GCCE 2026
Re-Defining Vanishing Municipalities in Japan: A Multidimensional Clustering and SLM-Based Policy Insight Framework
Toma Okugawa, Keito Inoshita
A reproducible framework (UBRS) that re-defines Japan's 'vanishing municipalities' beyond a single demographic axis — clustering 1,721 municipalities across 125 indicators (UMAP + HDBSCAN + SHAP) and injecting each cluster profile as RAG context into a locally deployable small language model to generate municipality-tailored policy insights.
IEEE GCCE 2026
Behavioral Fidelity and Philosophy-Grounded Design for Self-Reflective Conversational AI
Takumi Matsuo, Keito Inoshita
Proposes Behavioral Fidelity (BF), a framework that quantifies whether an LLM dialogue agent actually follows its designer-specified behavioral rules — via LLM-as-judge strategy classification, KL-divergence analysis, and sequential constraint checks — and applies it to Mirra, a philosophy-of-language-grounded self-reflection app.