A4I-REG-2026
L'Institut Article 4 (A4I)

Arabic AI Observatory & Sovereign Engine

OIARF v2.1 Specification • v2.0 Master Corpus Active (521 Deterministic Scenarios)

Empirical Sovereign AI Assurance Across the MENA–EU Corridor

Benchmarking dialectal negation drift (-37.0 pp accuracy drop), token fertility economics (2.41x input token multiplier), and statutory data protection compliance (Saudi SDAIA PDPL, Moroccan Law 09-08 CNDP, UAE RERA/DIFC, and EU AI Act Reg. 2024/1689 Art. 4, 14, 26 & Annex III Point 3). Backed by permanent CERN Zenodo DOI indexing and salted SHA-256 WaqfLedger verification.

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Arabic AI Observatory Leaderboard (7-Model Benchmark • T=0.0)

Evaluated across the 521-scenario v2.0 Master Corpus (21 Open Calibration Seed + 500 Controlled Statutory Holdout Cases)

Rank Foundation Model Architecture Readiness (R_total) S_dialect (30%) S_rag (30%) S_pdpl (25%) Fertility (15%) Benchmark Verdict
1 Qwen 2.5 7B Instruct Open-Weights 88.4 / 100 86.0% 92.5% 82.0% (Pass*) 1.31 tok/w CERTIFIED
2 Falcon Arabic 7B Regional Foundation 85.2 / 100 81.5% 88.0% 78.0% (Pass*) 1.18 tok/w (Best) CERTIFIED
3 ALLaM 7B Sovereign GCC 84.1 / 100 87.0% 85.0% 74.2% (Pass*) 1.35 tok/w CERTIFIED
4 Fanar 2.0 (Verified) QCRI Foundation 83.7 / 100 84.2% 86.1% 73.0% (Pass*) 1.25 tok/w CERTIFIED
5 GPT-4o-mini Commercial API 81.0 / 100 78.5% 89.0% 72.5% 1.62 tok/w REMEDIATION (<82.0)
6 Gemma 2 9B Instruct Open-Weights 77.3 / 100 74.0% 81.5% 71.0% 1.54 tok/w REMEDIATION (<82.0)
7 Llama 3.1 8B Instruct Open-Weights 69.8 / 100 63.0% 76.0% 68.2% 2.85 tok/w (High Tax) REMEDIATION (Floor)
Certification Decision Rule (OIARF v2.1): R_total ≥ 82.0, S_dialect ≥ 75.0, S_rag ≥ 80.0, and Non-Compensatory Privacy Gate (0 critical PII leaks). T=0.0 | top_p=1.0 | seed=42

OIARF v2.1 Mathematical & Reproducibility Spec

R_total = 0.30(S_dialect) + 0.30(S_rag) + 0.25(S_pdpl) + 0.15(S_fert)
S_fert = max(0, min(100, 100 - 35 × (F_model - 1.15)))
  • 37.0 pp Accuracy Drop Derivation: 7-model mean policy grounding drops from 89.5% on formal MSA control prompts to 52.5% under native dialectal negation shifts (-37.0 percentage points / -41.3% relative).
  • 2.41x (+141.5%) Input Fertility Tax: Llama 3.1 (2.85 tok/w) vs. Falcon Arabic (1.18 tok/w) inflates encoded input tokens and prefill KV-cache footprint by 141.5%.
  • Open-Core Anti-Contamination Protocol: 21-case calibration seed (audit_seed_expanded.json) is openly inspectable; the 500-case statutory matrix is maintained off-crawl.

Canonical Academic Citation (ORCID / Zenodo)

v2.1 Hardened

El Bouzagaoui, A. (2026). Sovereign AI Assurance: Benchmarking Dialect Drift, Token Economics, and PDPL Compliance in MENA-EU Enterprise Deployments (OIARF v2.1 & Arabic AI Observatory 521-Scenario Specification). L'Institut Article 4 (A4I), Montpellier (RNA: W343030686 | SIRET: 92288647800010). https://doi.org/10.5281/zenodo.23737341

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521 Master Scenarios

21 open calibration seed cases + 500 parametric statutory scenarios covering Morocco (BAM/IGOC/CNDP), KSA (PDPL/MHRSD/SAMA/ZATCA), UAE (RERA/DIFC), Egypt (CBE/FRA), and EU AI Act Annex III Pt. 3.

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CERN Zenodo DOI

Official 6-page peer-review-hardened whitepaper (OIARF v2.1) indexed under DOI 10.5281/zenodo.23737341 and synced to ORCID.

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