## Heatmap: Zero-shot - Core Generalization - GPT-4o ### Overview The image is a heatmap visualizing the zero-shot core generalization performance of GPT-4o. The heatmap displays accuracy percentages for different "Types" across varying "Lengths." The color intensity corresponds to the accuracy, with darker blue shades indicating higher accuracy and lighter shades indicating lower accuracy. ### Components/Axes * **Title:** Zero-shot - Core Generalization - GPT-4o * **X-axis:** Length (ranging from 0 to 19) * **Y-axis:** Type (categorical, labeled 1 through 7) * **Color Scale (Legend):** Accuracy (%) ranging from 0% (lightest shade) to 100% (darkest shade of blue). The color bar is vertically oriented on the right side of the heatmap. ### Detailed Analysis The heatmap presents accuracy values for each combination of "Type" and "Length." Here's a breakdown of the data: * **Type 1:** * Length 0: 37.0% * Length 1: 31.0% * Length 2: 22.0% * Length 3: 12.0% * Length 4: 6.0% * Length 5: 3.0% * Length 6: 1.0% * Length 7: 2.0% * Length 8: 1.0% * Length 9: 1.0% * **Type 2:** * Length 0: 49.0% * Length 1: 66.0% * Length 2: 67.0% * Length 3: 45.0% * Length 4: 62.0% * Length 5: 41.0% * Length 6: 44.0% * Length 7: 48.0% * Length 8: 37.0% * Length 9: 45.0% * **Type 3:** * Length 0: 13.0% * Length 1: 42.0% * Length 2: 22.0% * Length 3: 9.0% * Length 4: 10.0% * Length 5: 5.0% * Length 6: 3.0% * Length 7: 3.0% * Length 8: 3.0% * Length 9: 3.0% * Length 10: 0.0% * Length 11: 1.0% * Length 12: 1.0% * Length 13: 1.0% * Length 14: 1.0% * Length 15: 1.0% * Length 16: 1.0% * Length 17: 0.0% * Length 18: 1.0% * Length 19: 1.0% * **Type 4:** * Length 1: 62.0% * Length 2: 65.0% * Length 3: 45.0% * Length 4: 26.0% * Length 5: 24.0% * Length 6: 19.0% * Length 7: 14.0% * Length 8: 17.0% * Length 9: 13.0% * Length 10: 9.0% * Length 11: 9.0% * **Type 5:** * Length 7: 0.0% * Length 8: 0.0% * Length 9: 0.0% * Length 10: 0.0% * Length 11: 0.0% * Length 12: 0.0% * Length 13: 0.0% * Length 14: 0.0% * Length 15: 0.0% * Length 16: 0.0% * Length 17: 2.0% * Length 18: 0.0% * Length 19: 4.0% * **Type 6:** * Length 0: 22.0% * Length 1: 59.0% * Length 2: 35.0% * Length 3: 24.0% * Length 4: 15.0% * Length 5: 20.0% * Length 6: 17.0% * Length 7: 5.0% * Length 8: 8.0% * Length 9: 15.0% * Length 10: 8.0% * Length 11: 14.0% * Length 12: 6.0% * Length 13: 6.0% * Length 14: 11.0% * Length 15: 8.0% * Length 16: 5.0% * Length 17: 7.0% * Length 18: 2.0% * **Type 7:** * Length 0: 39.0% * Length 1: 36.0% * Length 2: 26.0% * Length 3: 26.0% * Length 4: 17.0% * Length 5: 18.0% * Length 6: 4.0% * Length 7: 11.0% * Length 8: 10.0% * Length 9: 7.0% * Length 10: 2.0% * Length 11: 2.0% * Length 12: 5.0% * Length 13: 2.0% ### Key Observations * Types 2 and 4 generally exhibit higher accuracy compared to other types. * Type 5 has very low accuracy across all lengths, with most values at 0%. * For most types, accuracy tends to decrease as the length increases. * There are variations in accuracy across different types for the same length, indicating that the model's performance is type-dependent. ### Interpretation The heatmap provides insights into the zero-shot core generalization capabilities of the GPT-4o model. The model's performance varies significantly depending on the "Type" and "Length" of the input. The higher accuracy values for Types 2 and 4 suggest that the model is better at generalizing for these specific types. The decreasing accuracy with increasing length indicates that the model's performance degrades as the input sequence becomes longer, which is a common challenge in sequence modeling. The near-zero accuracy for Type 5 suggests a significant limitation in the model's ability to generalize to this particular type. These findings can be used to identify areas where the model excels and areas where further improvements are needed to enhance its generalization capabilities.