Research Paper
Multi-Step General Reasoning Without an LLM: A Structural-Mechanics Architecture Outperforms GPT-5.2 on a Seven-Family Reasoning Battery
A technical paper on structured multi-step reasoning, benchmark discipline, and what governed AI systems can learn from non-prompt-only evaluation methods.
Abstract
This paper examines whether multi-step reasoning can be evaluated through a structured control architecture rather than prompt-only language-model behaviour. The public abstract focuses on reasoning-task design, benchmark discipline, verifier-mediated repair, and the implications for governed AI systems where traceability and stability matter.
Citation
Ken Morkaya. (2026). Multi-Step General Reasoning Without an LLM: A Structural-Mechanics Architecture Outperforms GPT-5.2 on a Seven-Family Reasoning Battery. Newport Resonance. /research/multi-step-general-reasoning-without-an-llm-a-structural-mechanics-architecture-outperforms-gpt-5-2-on-a-seven-family-reasoning-battery.pdf