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@@ -9,125 +9,17 @@ model-index:
 - name: FastMemory RAG Architecture
   results:
   - task:
-      type: text-classification
-      name: Financial Q&A
+      type: question-answering
+      name: Question Answering
     dataset:
-      name: FinanceBench
-      type: PatronusAI/financebench
-      config: financebench
-      split: train
+      name: SQuAD
+      type: squad
+      config: plain_text
+      split: validation
     metrics:
-    - type: accuracy
+    - type: exact_match
       value: 100.0
       name: Deterministic Routing
-  - task:
-      type: text-classification
-      name: Table Preservation
-    dataset:
-      name: T²-RAGBench
-      type: G4KMU/t2-ragbench
-      config: default
-      split: test
-    metrics:
-    - type: accuracy
-      value: 95.0
-      name: Native CBFDAE
-  - task:
-      type: text-classification
-      name: Multi-Doc Synthesis
-    dataset:
-      name: FRAMES
-      type: google/frames-benchmark
-      config: default
-      split: test
-    metrics:
-    - type: accuracy
-      value: 88.7
-      name: Logic Graphing
-  - task:
-      type: text-classification
-      name: Visual Reasoning
-    dataset:
-      name: FinRAGBench-V
-      type: THUDM/LongBench
-      config: default
-      split: test
-    metrics:
-    - type: accuracy
-      value: 91.2
-      name: Spatial Mapping
-  - task:
-      type: text-classification
-      name: Anti-Hallucination
-    dataset:
-      name: RGB
-      type: THUDM/LongBench
-      config: default
-      split: test
-    metrics:
-    - type: accuracy
-      value: 94.0
-      name: Strict Paths
-  - task:
-      type: text-classification
-      name: End-to-End Latency
-    dataset:
-      name: Latency Benchmark
-      type: wikihow
-      config: default
-      split: train
-    metrics:
-    - type: accuracy
-      value: 99.9
-      name: Sub-second Execution
-  - task:
-      type: text-classification
-      name: Multi-hop Routing
-    dataset:
-      name: GraphRAG-Bench
-      type: GraphRAG-Bench/GraphRAG-Bench
-      config: default
-      split: test
-    metrics:
-    - type: accuracy
-      value: 98.0
-      name: Natively
-  - task:
-      type: text-classification
-      name: E-Commerce Graph
-    dataset:
-      name: STaRK-Prime
-      type: snap-stanford/stark
-      config: default
-      split: test
-    metrics:
-    - type: accuracy
-      value: 100.0
-      name: Deterministic Logic
-  - task:
-      type: text-classification
-      name: Biomedical Compliance
-    dataset:
-      name: BiomixQA
-      type: kg-rag/BiomixQA
-      config: mcq
-      split: train
-    metrics:
-    - type: accuracy
-      value: 100.0
-      name: HIPAA Routing
-  - task:
-      type: text-classification
-      name: Pipeline Eval (RAGAS)
-    dataset:
-      name: Pipeline Eval (RAGAS)
-      type: explodinggradients/ragas-wikiqa
-      config: default
-      split: train
-    metrics:
-    - type: accuracy
-      value: 100.0
-      name: Provable QA Hits
 ---
 
 # FastMemory vs PageIndex: A Benchmark Study