## Line Graphs: Accuracy vs. K/V Compression Rate Across Datasets
### Overview
The image contains four line graphs comparing the accuracy of different compression methods (Single SVD and xKV variants) across four datasets (QA-1, QA-2, VT, N-MQ) at varying compression rates (2x, 4x, 8x, 16x). Each graph includes a legend with color-coded lines for "Single SVD (Value/Key)" and "xKV-2/4 (Value/Key)". Accuracy is measured on the y-axis (0–100%), while the x-axis represents compression rates. Dashed horizontal lines indicate target accuracy thresholds (85% for QA-1, 95% for VT/N-MQ).
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### Components/Axes
#### Common Elements:
- **X-axis**: "K/V Compression Rate" with markers at 2x, 4x, 8x, 16x.
- **Y-axis**: "Accuracy" (0–100% in 10% increments).
- **Legends**: Positioned on the right of each sub-chart, with:
- **Light blue**: Single SVD (Value)
- **Dark blue**: xKV-2 (Value)
- **Red**: xKV-4 (Value)
- **Pink**: Single SVD (Key)
- **Dark red**: xKV-2 (Key)
- **Dark red (bold)**: xKV-4 (Key)
#### Dataset-Specific Details:
1. **QA-1**:
- Dashed line at ~85% accuracy.
- Single SVD (Value) starts at ~85% and drops to ~70% at 16x.
- xKV-4 (Value) maintains ~80–85% accuracy across all rates.
2. **QA-2**:
- No dashed line.
- Single SVD (Value) starts at ~60% and drops to ~40% at 16x.
- xKV-4 (Value) remains stable at ~50–60%.
3. **VT**:
- Dashed line at ~95% accuracy.
- Single SVD (Value) starts at ~95% and drops to ~85% at 16x.
- xKV-4 (Value) stays near 95% until 16x, then drops to ~85%.
4. **N-MQ**:
- Dashed line at ~95% accuracy.
- Single SVD (Value) starts at ~95% and drops to ~85% at 16x.
- xKV-4 (Value) remains near 95% until 16x, then drops to ~90%.
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### Detailed Analysis
#### QA-1:
- **Single SVD (Value)**: Accuracy declines steadily from ~85% (2x) to ~70% (16x).
- **xKV-4 (Value)**: Maintains ~80–85% accuracy across all rates.
- **Single SVD (Key)**: Starts at ~85% and drops to ~75% at 16x.
- **xKV-4 (Key)**: Declines from ~85% to ~80% at 16x.
#### QA-2:
- **Single SVD (Value)**: Sharp decline from ~60% (2x) to ~40% (16x).
- **xKV-4 (Value)**: Stable at ~50–60% across all rates.
- **Single SVD (Key)**: Peaks at ~60% (4x), dips to ~55% (8x), then recovers to ~58% (16x).
- **xKV-4 (Key)**: Stable at ~58–62% across all rates.
#### VT:
- **Single SVD (Value)**: Declines from ~95% (2x) to ~85% (16x).
- **xKV-4 (Value)**: Stable at ~95% until 16x, then drops to ~85%.
- **Single SVD (Key)**: Starts at ~95%, drops to ~90% at 16x.
- **xKV-4 (Key)**: Declines from ~95% to ~90% at 16x.
#### N-MQ:
- **Single SVD (Value)**: Declines from ~95% (2x) to ~85% (16x).
- **xKV-4 (Value)**: Stable at ~95% until 16x, then drops to ~90%.
- **Single SVD (Key)**: Starts at ~95%, drops to ~90% at 16x.
- **xKV-4 (Key)**: Declines from ~95% to ~90% at 16x.
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### Key Observations
1. **Accuracy Degradation**: All methods show reduced accuracy as compression rates increase, but xKV variants degrade more slowly.
2. **xKV Superiority**: xKV-4 (Value/Key) consistently outperforms Single SVD across all datasets and compression rates.
3. **Dataset Variability**:
- **QA-1/QA-2**: Lower baseline accuracy; xKV-4 maintains ~10–15% higher accuracy than Single SVD.
- **VT/N-MQ**: Higher baseline accuracy; xKV-4 retains near-target thresholds (95%) longer.
4. **Anomalies**:
- In QA-2, Single SVD (Key) shows a non-monotonic trend (dips at 8x, recovers at 16x).
- VT/N-MQ xKV-4 (Value) lines exhibit a sharp drop at 16x, suggesting a threshold effect.
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### Interpretation
The data demonstrates that **xKV compression methods (especially xKV-4)** are more robust to compression than Single SVD, preserving accuracy better under higher compression rates. This suggests xKV is preferable for applications requiring both compression and accuracy. The dashed lines likely represent practical accuracy thresholds, with xKV-4 meeting or exceeding these in VT/N-MQ even at 16x compression. The anomalies in QA-2 (Single SVD Key) and VT/N-MQ (xKV-4 Value drop at 16x) warrant further investigation into compression-specific failure modes. Overall, the results highlight the trade-off between compression efficiency and accuracy, with xKV offering a better balance.
