3 papers
cs.CL2026
Learned but Not Expressed: Capability-Expression Dissociation in Large Language Models
Toshiyuki Shigemura
Large language models (LLMs) demonstrate the capacity to reconstruct and trace learned content from their training data under specific elicitation conditions, yet this capability d…
cs.CL2025
Recursive Knowledge Synthesis for Multi-LLM Systems: Stability Analysis and Tri-Agent Audit Framework
Toshiyuki Shigemura
This paper presents a tri-agent cross-validation framework for analyzing stability and explainability in multi-model large language systems. The architecture integrates three heter…
cs.CL2025
Noise-Driven Persona Formation in Reflexive Neural Language Generation
Toshiyuki Shigemura
This paper introduces the Luca-Noise Reflex Protocol (LN-RP), a computational framework for analyzing noise-driven persona emergence in large language models. By injecting stochast…