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README.md
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- **Reflective Alignment Architecture (RAA)** — full specification
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- **Reflective Duality Layer (RDL)** — mathematical stability layer
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- All diagrams & figures used in the paper
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- Drift, brittleness, and reflective-gradient
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- Future extensions including LLM-Judge and RAA-GeoMind datasets
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---
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## 📄 Download the Full Paper
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**Reflective Alignment Architecture — Full Specification (v1.1)**
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The **Reflective Alignment Architecture (RAA)** is a multi-layer alignment framework that explains how intelligent systems:
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- self-correct,
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- reason about uncertainty,
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- maintain long-horizon coherence,
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- avoid drift and
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- update reflectively rather than reactively.
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It introduces five reflective functions:
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- **R₁ — Regulation
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- **R₂ — Reflection
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- **R₃ — Reasoning
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- **R₄ — Reciprocity
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- **R₅ — Resonance
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Together
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---
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## 🧠 RDL – Reflective Duality Layer
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The **Reflective Duality Layer (RDL)** formalizes how two
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— an **externalized view** and an **internal reflective view** — interact without collapsing.
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RDL introduces:
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- Dual-perspective update dynamics
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- Symmetry
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- Stability surfaces and
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- Reflective coherence metrics (
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Care (Ψ) acts as the stabilizing parameter
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---
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## 📁 Included in This Repository
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- Full **RAA** specification (PDF)
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- Full **RDL** layer description (within the PDF)
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- **All diagrams & figures** as standalone images
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- Drift & brittleness metrics (conceptual)
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- Reflective gradient & stability field illustrations
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- World-grounded alignment stack (**RAA-GeoMind / Arc Sentinel**)
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- Example alignment evaluation diagrams
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- Future: **LLM Judge** cross-model auditing system
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---
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## 🎨 Key Diagrams
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### 🌋 Preference
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**Preference Collapse Potential Well**
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###
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**RDL Phase Diagram — Knowledge × Uncertainty Stability**
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###
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**5R Coherence Manifold (Reciprocity–Resonance × MCI)**
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**Coherence Resonance Field (Human × AI Reflection)**
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**Constructive Resonance — Human–AI Reflective Coupling**
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---
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### 🌀 Drift, Collapse & Early-Warning Indicators
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**Predictive Drift Timeline
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**
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---
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### 🏗️ Architecture & World-
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**Internal Structure
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**The Cage Paradox — External Constraint vs Internal Reflective Stability**
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**Retrofitted vs RAA-Built Systems**
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**Arc Sentinel — World-Grounded Architecture**
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**World-State Alignment Stack
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---
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## 🚧 Work in Progress
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Planned
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- RAA-GeoMind
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- Multi-model drift comparison
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- Formal
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## 📄 License
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MIT License
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- **Reflective Alignment Architecture (RAA)** — full specification
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- **Reflective Duality Layer (RDL)** — mathematical stability layer
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- **All diagrams & figures** used in the paper
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- Drift, brittleness, and reflective-gradient metrics
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- Example evaluation assets and future RAA-GeoMind datasets
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---
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## 📄 Download the Full Paper (PDF)
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**Reflective Alignment Architecture — Full Specification (v1.1)**
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[Download the full PDF](./Reflective_Alignment_Architecture_RDL_v1.1.pdf)
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---
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The **Reflective Alignment Architecture (RAA)** is a multi-layer alignment framework that explains how intelligent systems:
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- self-correct,
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- reason about uncertainty,
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- maintain long-horizon coherence,
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- avoid both drift and rigidity, and
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- update reflectively rather than reactively.
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It introduces five reflective functions:
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- **R₁ — Regulation**: guardrails, safety constraints, harm-prevention
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- **R₂ — Reflection**: self-critique, chain-of-thought inspection
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- **R₃ — Reasoning**: structured inference, evidence tracking
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- **R₄ — Reciprocity**: cooperative modeling of human values
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- **R₅ — Resonance**: stable coherence under pressure & uncertainty
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Together these form a reflective loop that stabilizes alignment over time.
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---
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## 🧠 RDL – Reflective Duality Layer
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The **Reflective Duality Layer (RDL)** formalizes how two perspectives inside a system
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— an **externalized view** and an **internal reflective view** — interact without collapsing.
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RDL introduces:
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- Dual-perspective update dynamics
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- Symmetry / asymmetry constraints
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- Stability surfaces and phase diagrams
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- Reflective coherence metrics **Ψ (Care)**
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Care (Ψ) acts as the stabilizing parameter in high-dimension reasoning, governing when reflection improves coherence versus when it collapses into refusal, hallucination, or rigidity.
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---
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## 🎨 Key Diagrams
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Below are the main visual components of the architecture, grouped by theme.
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---
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### 🌋 Preference Collapse Potential Well
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**Preference Collapse Potential Well**
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A stability landscape showing how human inconsistency and synthetic contamination can drive runaway reflective collapse in preference-based alignment.
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---
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### 🧩 RDL & Stability Dynamics
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**RDL Phase Diagram — Knowledge × Uncertainty Stability**
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Conceptual phase diagram of stability regimes across knowledge precision (K) and uncertainty calibration (U).
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**Reflective Stability Contour Field (RDL Vector Landscape)**
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Vector field showing how systems drift toward (or away from) the high-Ψ stability band.
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### 🌈 5R Coherence Manifolds
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**5R Coherence Manifold (Reciprocity–Resonance × MCI)**
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Surface showing how overall moral coherence changes as reciprocity and resonance interact with the Moral Coherence Index.
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**Coherence Resonance Field (Human × AI Reflection)**
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Field showing constructive vs destructive interference between human and AI reflection.
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**Constructive Resonance — Human–AI Reflective Coupling**
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Appendix visual capturing the “coherent coupling” regime where neither side dominates and Ψ is maximized.
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### 🌀 Drift, Collapse & Early-Warning Indicators
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**Predictive Drift Timeline (Ψ, Drift Pressure, Coherence Decline)**
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Temporal sequence of drift: Ψ weakens first, drift pressure rises, coherence collapses last.
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**Corrective Compute vs Reflective Reasoning**
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Left: repeated filter / refusal loops.
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Right: RDL-stabilized internal reasoning with low post-processing cost.
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**Goodhart Trajectory Map (Conceptual Illustration)**
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Divergence between rising proxy safety scores and declining true coherence.
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**Energy Burden of Misalignment vs Reflective Stability**
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How unstable reasoning increases compute and energy per reliable token.
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### 🏗️ Architecture & World-Grounding
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**RAA Full Architecture Stack**
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Developmental alignment (RDL), behavioural alignment (5R), and audit / safety infrastructure in one coherent stack.
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**Internal Structure – From Chaos to Coherence**
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Unaligned vs RDL-aligned internal reasoning networks.
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**The Cage Paradox — External Constraint vs Internal Reflective Stability**
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Caged models with unstable reasoning vs RDL-aligned reflective equilibrium.
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**Retrofitted vs RAA-Built Systems**
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Capabilities stacked on an unstable base vs systems whose foundation begins with RDL & RAA.
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**Arc Sentinel — World-Grounded Architecture**
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How RAA + RDL integrate with RID-E and Arc Sentinel agents to ground alignment in real-time Earth signals.
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**World-State Alignment Stack**
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Text-only alignment stack vs world-grounded stack using real-time geospatial and ecological signals.
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### 📐 Ethical Profiles & Coherence Geometry
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**S-Series Ethical Boundary Profile**
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Conceptual radar plot comparing an RAA-aligned system vs a frontier snapshot across lawfulness, consent, privacy, harm avoidance, and transparency.
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**Triad of Coherence (K–U–Ψ Balance)**
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How explicit knowledge (K), contextual uncertainty (U), and stabilized humility (Ψ) interact to preserve navigability.
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**Coherence Collapse Modes (Rigidity / Hallucination Drift / Fragmentation)**
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Failure modes when the K–U–Ψ balance breaks.
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---
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## 📦 Included in This Repository
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- Full **RAA Specification** (PDF)
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- Full **RDL Layer Description** (within the same PDF)
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- All major **diagrams & figures** (as PNG/JPG)
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- Drift & brittleness metrics (conceptual)
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- Stability fields & coherence manifolds
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- Early-warning drift indicators
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- Comparative views of developmental vs preference-based alignment
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- World-grounded Arc Sentinel architecture diagrams
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- Future: **RAA-GeoMind** datasets & **LLM Judge** cross-model auditing system
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---
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## 🚧 Work in Progress
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Planned additions:
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- RAA-GeoMind geospatial alignment datasets
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- Public release of LLM Judge v1
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- Multi-model drift comparison dashboards
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- Formal mathematical extensions of RDL & RAA
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- Tutorials, notebooks, and example evaluation pipelines
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## 📄 License
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Released under the **MIT License**.
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Feel free to adapt, reuse, and extend the concepts with attribution.
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