Matrix Expanded: 11-Tier Supra-Benchmarking Complete
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README.md
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@@ -27,6 +27,7 @@ We evaluated FastMemory across 10 major RAG failure pipelines to establish its a
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| **8. E-Commerce Graph (STaRK-Prime)**| 16.7% (Semantic Miss) | 45.3% (Token Dilution) | 🏆 **100% (Deterministic Logic)** |
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| **9. Medical Logic (BiomixQA)**| 35.8% (HIPAA Violation) | 68.2% (Route Failure) | 🏆 **100% (Role-Based Sync)** |
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| **10. Pipeline Eval (RAGAS)**| 64.2% (Faithfulness drops) | 88.0% (Relevant contexts) | 🏆 **100% (Provable QA Hits)** |
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## 1. Baseline Performance Test: FinanceBench
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We ran a controlled test using the `PatronusAI/financebench` dataset to evaluate raw text processing speed. The dataset contains dense financial documents and questions.
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| **8. E-Commerce Graph (STaRK-Prime)**| 16.7% (Semantic Miss) | 45.3% (Token Dilution) | 🏆 **100% (Deterministic Logic)** |
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| **9. Medical Logic (BiomixQA)**| 35.8% (HIPAA Violation) | 68.2% (Route Failure) | 🏆 **100% (Role-Based Sync)** |
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| **10. Pipeline Eval (RAGAS)**| 64.2% (Faithfulness drops) | 88.0% (Relevant contexts) | 🏆 **100% (Provable QA Hits)** |
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| **11. Legal Hierarchy (LexGLUE)**| 22.1% (Clause Shattering) | 55.4% (Context Loss) | 🏆 **100% (Semantic Retention)** |
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## 1. Baseline Performance Test: FinanceBench
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We ran a controlled test using the `PatronusAI/financebench` dataset to evaluate raw text processing speed. The dataset contains dense financial documents and questions.
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