## Box Plot: Token Length Comparison ### Overview The image is a box plot comparing the token lengths of three different models: General-Reasoner, SimpleTIR, and FLV-RL. The y-axis represents "Token length", and the x-axis represents the model names. The plot displays the distribution of token lengths for each model, showing the median, quartiles, and outliers. ### Components/Axes * **X-axis:** Model names: General-Reasoner, SimpleTIR, FLV-RL * **Y-axis:** Token length, with a scale from 0 to 20000. Gridlines are present at intervals of approximately 5000. * **Box Plots:** Each box plot represents the distribution of token lengths for a specific model. * The box represents the interquartile range (IQR), containing the middle 50% of the data. * The line inside the box represents the median. * The whiskers extend to the furthest data point within 1.5 times the IQR from the box. * Outliers are represented as individual points beyond the whiskers. * **Data Labels:** Numerical values are displayed near each box plot, indicating specific statistical values. ### Detailed Analysis * **General-Reasoner (Green Box):** * Median: Approximately 933 * Q1 (25th percentile): Approximately 562 * Q3 (75th percentile): Approximately 1344 * The box is relatively small, indicating a narrow range of token lengths. * **SimpleTIR (Blue Box):** * Median: Approximately 4352 * Q1 (25th percentile): Approximately 2828 * Q3 (75th percentile): Approximately 6985 * The box is larger than that of General-Reasoner, indicating a wider range of token lengths. * **FLV-RL (Red Box):** * Median: Approximately 6180 * Q1 (25th percentile): Approximately 3478 * Q3 (75th percentile): Approximately 9862 * The box is the largest, indicating the widest range of token lengths. ### Key Observations * The median token length increases from General-Reasoner to SimpleTIR to FLV-RL. * The interquartile range (IQR) also increases from General-Reasoner to SimpleTIR to FLV-RL, indicating greater variability in token lengths for the latter models. * FLV-RL has a significantly larger range of token lengths compared to the other two models. ### Interpretation The box plot illustrates the distribution of token lengths generated by three different models. General-Reasoner produces the shortest and most consistent token lengths, while FLV-RL generates the longest and most variable token lengths. SimpleTIR falls in between these two. This suggests that FLV-RL might be generating more complex or verbose outputs compared to the other models. The wider range of token lengths for FLV-RL could also indicate that it is more sensitive to variations in input or task complexity.