## Line Chart: R1-Llama | AIME24 ### Overview The chart compares the accuracy (%) of four strategies ("Full", "Top", "Random", "Bottom") across varying ratios (%) from 2 to 50. The y-axis ranges from 30% to 65%, with the "Full" strategy consistently achieving the highest accuracy, while "Bottom" remains the lowest. The "Top" and "Random" strategies show distinct trends, with "Top" improving steadily and "Random" exhibiting a late surge. ### Components/Axes - **X-axis**: Ratio (%) (2, 4, 6, 8, 10, 20, 30, 40, 50) - **Y-axis**: Accuracy (%) (30–65%) - **Legend**: - Gray dashed line: "Full" - Red solid line: "Top" - Green solid line: "Random" - Blue solid line: "Bottom" - **Legend Position**: Top-right corner ### Detailed Analysis 1. **"Full" (Gray Dashed Line)**: - Flat line at ~65% accuracy across all ratios. - No variation observed; consistently the highest performer. 2. **"Top" (Red Solid Line)**: - Starts at ~55% (ratio 2) and increases steadily to ~62% (ratio 50). - Slope: ~0.14% accuracy gain per ratio increment. 3. **"Random" (Green Solid Line)**: - Begins at ~28% (ratio 2), dips to ~27% (ratio 8), then rises sharply. - Reaches ~48% at ratio 50, showing a U-shaped trend with a late surge. 4. **"Bottom" (Blue Solid Line)**: - Fluctuates between ~30–35% across all ratios. - Slight upward trend (from ~30% at ratio 2 to ~37% at ratio 50). ### Key Observations - **Outlier**: "Random" strategy underperforms initially but surpasses "Bottom" after ratio 20. - **Trend**: "Top" shows the most significant improvement with increasing ratios. - **Anomaly**: "Full" remains flat despite ratio changes, suggesting it is unaffected by the ratio parameter. ### Interpretation The chart demonstrates that the "Full" strategy is optimal, maintaining peak accuracy regardless of ratio. The "Top" strategy improves predictably with higher ratios, making it a viable alternative if resource constraints exist. The "Random" strategy’s late surge suggests potential inefficiencies in early stages or hidden patterns in later ratios. "Bottom" consistently underperforms, indicating systemic limitations. The data implies that strategy selection should prioritize "Full" for maximum accuracy, with "Top" as a secondary option for scalable applications.