## Heatmap: Llama 4 Maverick ### Overview The image is a heatmap displaying performance scores of "Llama 4 Maverick" across different mathematical subjects (Algebra, Count. & Prob., Geometry, Inter. Algebra, Number Theory, Prealgebra, Precalculus) for four different evaluation methods (PoT, CR, MACM, and IIPC). The color intensity represents the performance score, with lighter shades indicating higher scores. ### Components/Axes * **Title:** Llama 4 Maverick * **Rows (Y-axis):** Mathematical Subjects * Algebra * Count. & Prob. (Counting and Probability) * Geometry * Inter. Algebra (Intermediate Algebra) * Number Theory * Prealgebra * Precalculus * **Columns (X-axis):** Evaluation Methods * PoT * CR * MACM * IIPC * **Color Scale:** The color scale is not explicitly defined, but it appears that lighter, more yellow colors represent higher scores, while darker, more green colors represent lower scores. ### Detailed Analysis Here's a breakdown of the performance scores for each subject and evaluation method: * **Algebra:** * PoT: 95.81 * CR: 97.21 * MACM: 98.14 * IIPC: 98.60 * Trend: Scores are high across all methods, with a slight increase from PoT to IIPC. * **Count. & Prob.:** * PoT: 91.00 * CR: 91.00 * MACM: 92.42 * IIPC: 91.47 * Trend: Scores are relatively consistent across all methods, with a slight peak at MACM. * **Geometry:** * PoT: 79.52 * CR: 80.00 * MACM: 75.24 * IIPC: 80.48 * Trend: Geometry scores are the lowest compared to other subjects. MACM has the lowest score. * **Inter. Algebra:** * PoT: 83.72 * CR: 80.00 * MACM: 84.19 * IIPC: 87.44 * Trend: The score is lowest for CR and highest for IIPC. * **Number Theory:** * PoT: 91.09 * CR: 94.06 * MACM: 91.09 * IIPC: 94.06 * Trend: Scores are consistent, with CR and IIPC showing the same higher value. * **Prealgebra:** * PoT: 94.42 * CR: 95.35 * MACM: 94.42 * IIPC: 96.74 * Trend: Scores are high, with IIPC having the highest score. * **Precalculus:** * PoT: 86.98 * CR: 85.12 * MACM: 85.12 * IIPC: 89.77 * Trend: IIPC has the highest score, while CR and MACM share the lowest score. ### Key Observations * Algebra consistently scores the highest across all evaluation methods. * Geometry consistently scores the lowest across all evaluation methods. * IIPC generally yields the highest scores for most subjects. * CR and MACM sometimes yield lower scores compared to PoT and IIPC. ### Interpretation The heatmap provides a visual representation of the performance of "Llama 4 Maverick" on different mathematical subjects using various evaluation methods. The data suggests that the model performs best in Algebra and Prealgebra, and relatively weaker in Geometry. The IIPC evaluation method seems to yield the highest performance scores overall, suggesting it might be a more suitable evaluation metric for this model. The differences in scores across subjects and evaluation methods could be attributed to the model's architecture, training data, or the specific challenges posed by each subject. The lower scores in Geometry might indicate an area where the model needs further improvement.