Dimensional Behavioral Specification: A Design Methodology for LLM Behavioral Control via State-Space Mapping and Partial Ordering

v2 (June 2026) - Reframed DBS from "universal design methodology" to "model-conditioned overlay architecture" — DBS now positioned as an adapter layer that organizes behavioral constraints on top of existing orchestration prompts, rather than as a standalone replacement.- Added Section 6.2: ablation study design comparing three prompt conditions (Sisyphus-only, DBS-only, Sisyphus+DBS) across two model families (Claude / DeepSeek), with placeholder metrics for delegation correctness, safety compliance, task completion, and token efficiency.- Added model-class dependency discussion to Section 6.1 (Limitations): DBS effectiveness is likely modulated by model architecture, with principle-driven models potentially benefiting more from the compact overlay than mechanical-driven models.- Revised title, abstract, introduction, contributions, and conclusion for internal consistency with the reframed thesis.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-16
DOI
https://doi.org/10.5281/zenodo.20714604
Primary Topic
Safety Systems Engineering in Autonomy
Type
preprint
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preprint

Dimensional Behavioral Specification: A Design Methodology for LLM Behavioral Control via State-Space Mapping and Partial Ordering

inoribea
Zenodo (CERN European Organization for Nuclear Research)
Safety Systems Engineering in Autonomy
preprint

Dimensional Behavioral Specification: A Design Methodology for LLM Behavioral Control via State-Space Mapping and Partial Ordering

inoribea
preprint en

Abstract

v2 (June 2026) - Reframed DBS from "universal design methodology" to "model-conditioned overlay architecture" — DBS now positioned as an adapter layer that organizes behavioral constraints on top of existing orchestration prompts, rather than as a standalone replacement.- Added Section 6.2: ablation study design comparing three prompt conditions (Sisyphus-only, DBS-only, Sisyphus+DBS) across two model families (Claude / DeepSeek), with placeholder metrics for delegation correctness, safety compliance, task completion, and token efficiency.- Added model-class dependency discussion to Section 6.1 (Limitations): DBS effectiveness is likely modulated by model architecture, with principle-driven models potentially benefiting more from the compact overlay than mechanical-driven models.- Revised title, abstract, introduction, contributions, and conclusion for internal consistency with the reframed thesis.

Zenodo (CERN European Organization for Nuclear Research)
Wuhan Institute of Technology (CN)
Safety Systems Engineering in Autonomy
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