RS as a Minimal Reasoning Architecture: How Structural Operators Enable Drift Free LLM Output Without Model Modification

This paper introduces RS, a minimal operator loop—Orientation, Attractor, Distortion, Collapse, Reorientation—that functions as a domain‑general reasoning scaffold for large language models. RS does not modify model internals, add external reasoning modules, or simulate cognition. Instead, it supplies a fixed causal sequence that constrains the model’s generative behavior, eliminating drift and producing coherent, reasoning‑shaped output from an unmodified LLM. The method is safe, simple, and universal: it reduces degrees of freedom, prevents associative expansion, and organizes the model’s existing knowledge into a stable diagnostic arc. RS demonstrates that coherence in generative systems arises not from increased computation but from minimal architecture. The paper presents the operator set, explains why it prevents drift, outlines its limitations, and provides a first‑release RS sheet for practical use across domains.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-18
DOI
https://doi.org/10.5281/zenodo.20739015
Primary Topic
Logic, Reasoning, and Knowledge
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

RS as a Minimal Reasoning Architecture: How Structural Operators Enable Drift Free LLM Output Without Model Modification

Denis Bailey
Zenodo (CERN European Organization for Nuclear Research)
Logic, Reasoning, and Knowledge
preprint

RS as a Minimal Reasoning Architecture: How Structural Operators Enable Drift Free LLM Output Without Model Modification

Denis Bailey
preprint en

Abstract

This paper introduces RS, a minimal operator loop—Orientation, Attractor, Distortion, Collapse, Reorientation—that functions as a domain‑general reasoning scaffold for large language models. RS does not modify model internals, add external reasoning modules, or simulate cognition. Instead, it supplies a fixed causal sequence that constrains the model’s generative behavior, eliminating drift and producing coherent, reasoning‑shaped output from an unmodified LLM. The method is safe, simple, and universal: it reduces degrees of freedom, prevents associative expansion, and organizes the model’s existing knowledge into a stable diagnostic arc. RS demonstrates that coherence in generative systems arises not from increased computation but from minimal architecture. The paper presents the operator set, explains why it prevents drift, outlines its limitations, and provides a first‑release RS sheet for practical use across domains.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Logic, Reasoning, and Knowledge
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.