## Scatter Plot: Dataset: PassageRet
### Overview
The image is a scatter plot visualizing the relationship between KV Cache Size (in GB) and LongBench Accuracy for different models on the PassageRet dataset. The plot includes five data series represented by distinct markers and colors, along with a Pareto Frontier line indicating optimal performance trade-offs.
### Components/Axes
- **X-axis**: KV Cache Size (GB), ranging from 0.00 to 2.00 in increments of 0.25.
- **Y-axis**: LongBench Accuracy, ranging from 6 to 12 in increments of 1.
- **Legend**: Located in the top-right corner, with the following mappings:
- Red squares: H2O
- Blue circles: KIVI
- Green diamonds: SnapKV
- Yellow triangles: MiniKV
- Black crosses: Pareto Frontier
### Detailed Analysis
#### Data Series
1. **H2O (Red Squares)**:
- Points: (0.1, 10.7), (0.3, 11.0), (0.6, 10.4), (1.0, 12.0), (1.8, 9.7), (2.0, 9.5)
- Trend: Slightly decreasing LongBench Accuracy with increasing KV Cache Size, but with a peak at 1.0 GB.
2. **KIVI (Blue Circles)**:
- Single point: (0.5, 11.3)
- Trend: High accuracy at 0.5 GB, but no additional data points.
3. **SnapKV (Green Diamonds)**:
- Points: (0.2, 8.3), (0.4, 9.3), (1.1, 9.1), (1.7, 8.8), (2.0, 8.7)
- Trend: Moderate accuracy, with a slight decline after 1.1 GB.
4. **MiniKV (Yellow Triangles)**:
- Points: (0.1, 6.3), (0.3, 7.3), (0.5, 8.0), (0.7, 7.5)
- Trend: Gradual increase in accuracy up to 0.5 GB, followed by a plateau.
5. **Pareto Frontier (Black Crosses)**:
- Line connecting: (0.1, 10.7), (0.5, 11.3), (1.0, 12.0)
- Trend: Upward-sloping line, representing the optimal trade-off between KV Cache Size and LongBench Accuracy.
### Key Observations
- **H2O and KIVI** consistently outperform other models, with H2O achieving the highest LongBench Accuracy (12.0) at 1.0 GB KV Cache Size.
- **SnapKV and MiniKV** show lower accuracy, with MiniKV having the lowest values (6.3–8.0) across all cache sizes.
- The **Pareto Frontier** highlights the most efficient models (H2O and KIVI) that maximize accuracy for a given cache size.
- **Outliers**: MiniKV at 0.1 GB (6.3) and H2O at 2.0 GB (9.5) deviate from the general trend of increasing accuracy with larger cache sizes.
### Interpretation
The data suggests that **H2O and KIVI** are the most efficient models for the PassageRet dataset, achieving high LongBench Accuracy even at smaller KV Cache Sizes. The Pareto Frontier underscores their superiority, as they lie above the line, indicating better performance per unit of resource. In contrast, **SnapKV and MiniKV** underperform, with MiniKV showing the least efficiency. The trend of decreasing accuracy for H2O at larger cache sizes (e.g., 2.0 GB) may indicate diminishing returns or model-specific limitations. This analysis highlights the importance of optimizing KV Cache Size and model selection for resource-constrained environments.
