## Line Chart: Pass Rate vs. Steps ### Overview The image is a line chart comparing the "Pass Rate (%)" against "Steps" for two different methods: "SFT prior, Pass@3" and "RL prior, Pass@3". The chart displays how the pass rate changes over the number of steps for each method. ### Components/Axes * **X-axis:** "Steps", with labeled markers at 0, 50, 100, 150, 200, 250, and 300. * **Y-axis:** "Pass Rate (%)", with labeled markers at 42, 44, 46, 48, 50, 52, 54, and 56. * **Legend:** Located in the bottom-right of the chart. * Red line: "SFT prior, Pass@3" * Blue line: "RL prior, Pass@3" * The chart has a grid for easier reading of values. ### Detailed Analysis * **SFT prior, Pass@3 (Red Line):** * The line starts at approximately 42% at 0 steps. * The line generally slopes upward from 0 to 100 steps. * At 50 steps, the value is approximately 47%. * At 100 steps, the value is approximately 49%. * From 100 steps to 300 steps, the line fluctuates between approximately 47% and 52%. * At 150 steps, the value is approximately 47%. * At 200 steps, the value is approximately 51%. * At 250 steps, the value is approximately 50%. * At 300 steps, the value is approximately 51%. * **RL prior, Pass@3 (Blue Line):** * The line starts at approximately 45% at 0 steps. * The line generally slopes upward from 0 to 150 steps. * At 50 steps, the value is approximately 51%. * At 100 steps, the value is approximately 53%. * At 150 steps, the value is approximately 54%. * From 150 steps to 300 steps, the line fluctuates between approximately 51% and 56%. * At 200 steps, the value is approximately 52%. * At 250 steps, the value is approximately 55%. * At 300 steps, the value is approximately 54%. ### Key Observations * The "RL prior, Pass@3" method generally outperforms the "SFT prior, Pass@3" method, showing a higher pass rate across most of the steps. * Both methods show an initial increase in pass rate, but the "RL prior, Pass@3" method increases more rapidly. * Both lines exhibit fluctuations, indicating variability in the pass rate as the number of steps increases. ### Interpretation The chart suggests that using "RL prior, Pass@3" leads to a better pass rate compared to "SFT prior, Pass@3". The initial rapid increase in the "RL prior, Pass@3" method indicates a faster learning or adaptation rate. The fluctuations in both lines could be due to the inherent stochasticity in the learning process or the complexity of the task. The data demonstrates the impact of different prior methods on the pass rate of a system, highlighting the importance of selecting an appropriate prior for optimal performance.

## Line Chart: Pass Rate vs. Steps for SFT and RL Priors ### Overview This image is a 2D line chart comparing the performance of two different machine learning models or methodologies—labeled as "SFT prior" and "RL prior"—over a series of training or evaluation steps. The performance is measured by a "Pass Rate (%)" metric. The chart displays two highly volatile data series that generally trend upward over time, with the "RL prior" consistently outperforming the "SFT prior" for the majority of the recorded steps. ### Components/Axes **Component Isolation & Spatial Grounding:** * **Main Chart Area:** Occupies the majority of the image, featuring a light gray grid on a white background. The grid lines correspond to the major ticks on both axes. * **Y-Axis (Left):** * **Title:** "Pass Rate (%)" (Oriented vertically, reading bottom to top). * **Scale:** Ranges from 42 to 56. * **Markers/Ticks:** Major gridlines and labels are placed at intervals of 2: `42, 44, 46, 48, 50, 52, 54, 56`. * **X-Axis (Bottom):** * **Title:** "Steps" (Centered below the axis). * **Scale:** Ranges from 0 to 300. * **Markers/Ticks:** Major gridlines and labels are placed at intervals of 50: `0, 50, 100, 150, 200, 250, 300`. * **Legend (Bottom-Right):** Located inside the main chart area, positioned in the lower right quadrant (spanning roughly from step 120 to 300, and pass rate 42 to 46). It contains two entries: * `[Red Line with circular marker]` : "SFT prior, Pass@3" * `[Blue Line with circular marker]` : "RL prior, Pass@3" ### Detailed Analysis **Trend Verification & Data Extraction:** Both data series consist of discrete data points connected by straight lines. There appears to be a data point plotted every 5 steps (60 points total per line). Due to the high density and volatility, approximate values (`~`) are extracted at major grid intervals and significant inflection points (peaks/valleys) to accurately reconstruct the chart's behavior. **1. RL prior, Pass@3 (Blue Line)** * *Visual Trend:* The blue line starts at a moderate pass rate, rises sharply within the first 20 steps, and then enters a highly volatile oscillation pattern. It generally maintains a higher baseline than the red line, frequently peaking above 54%, but experiences occasional sharp drops. * *Key Data Points (Approximate ±0.5%):* * Step 0: ~45.4% (Starting point) * Step 20: ~50.6% (Initial peak) * Step 50: ~47.8% * Step 75: ~51.4% * Step 95: ~53.2% * Step 100: ~50.6% * Step 130: ~54.6% (Major peak) * Step 150: ~54.4% * Step 170: ~48.2% (Significant valley/drop) * Step 200: ~51.2% * Step 220: ~54.8% * Step 240: ~56.0% (Absolute maximum peak on the chart) * Step 250: ~54.2% * Step 300: ~51.4% (Ending point) **2. SFT prior, Pass@3 (Red Line)** * *Visual Trend:* The red line starts at the lowest point on the chart. It exhibits a steep initial climb similar to the blue line but generally oscillates at a lower tier (mostly between 46% and 52%). It has a few distinct, sharp spikes that briefly surpass the blue line. * *Key Data Points (Approximate ±0.5%):* * Step 0: ~41.8% (Starting point, absolute minimum) * Step 20: ~47.0% * Step 50: ~46.2% * Step 80: ~50.4% * Step 100: ~49.4% * Step 130: ~51.8% * Step 150: ~47.0% (Valley) * Step 185: ~54.2% (Absolute maximum peak for this series) * Step 200: ~50.6% * Step 220: ~46.8% (Deep valley) * Step 250: ~51.8% * Step 290: ~53.0% (Late peak) * Step 300: ~52.0% (Ending point) ### Key Observations * **Performance Gap:** The RL prior (blue) demonstrates a clear advantage over the SFT prior (red) for the vast majority of the 300 steps. The blue line is visibly shifted upward relative to the red line. * **Volatility:** Both metrics are incredibly noisy. A pass rate might jump or drop by 4% to 6% within a span of just 5 to 10 steps (e.g., the blue line dropping from ~52% at step 165 to ~48% at step 170, then back up to ~51% at step 175). * **Crossovers:** While RL is generally better, the SFT prior does occasionally spike higher than the RL prior at specific intervals (most notably around step 185, and briefly near step 290). * **Convergence:** Towards the end of the chart (steps 250-300), the two lines appear to entangle more frequently, suggesting the performance gap may be narrowing as the number of steps increases. ### Interpretation * **Contextual Meaning:** The chart likely represents the evaluation of Large Language Models (LLMs) on a coding or reasoning benchmark. "Pass@3" means the model is considered successful if the correct answer is generated within 3 attempts. "SFT" stands for Supervised Fine-Tuning, and "RL" stands for Reinforcement Learning. * **Data Implications:** The data strongly suggests that using a Reinforcement Learning prior provides a better starting point (Step 0 is ~3.6% higher) and maintains a higher average performance ceiling throughout the training/evaluation process compared to a Supervised Fine-Tuning prior. * **Reading Between the Lines (Peircean Investigative):** The extreme step-to-step volatility (the "sawtooth" pattern) is highly indicative of a small evaluation dataset or a small batch size during these steps. If the evaluation set were large, the pass rate would likely smooth out. The fact that both models trend upward indicates that whatever process is occurring over these "Steps" (likely further training, optimization, or a search process) is generally effective at improving the Pass@3 rate, despite the high variance. The RL prior's massive spike to 56% at step 240 shows its peak potential, but its inability to maintain that level suggests instability in the model's generation consistency.

\n ## Line Chart: Pass Rate vs. Steps ### Overview This image presents a line chart comparing the "Pass@3" rate of two models, "SFT prior" and "RL prior", over a range of "Steps" from 0 to 300. The chart visualizes the performance of each model as it progresses through training or evaluation steps, measured by the percentage of times it "passes" a certain criteria (Pass@3). ### Components/Axes * **X-axis:** "Steps" - ranging from 0 to 300, with tick marks at intervals of 50. * **Y-axis:** "Pass Rate (%)" - ranging from 42% to 56%, with tick marks at intervals of 2%. * **Data Series 1:** "SFT prior, Pass@3" - represented by a red line with circular markers. * **Data Series 2:** "RL prior, Pass@3" - represented by a blue line with circular markers. * **Legend:** Located in the bottom-right corner, clearly labeling each data series with its corresponding color. * **Grid:** A light gray grid is present in the background to aid in reading values. ### Detailed Analysis **SFT prior, Pass@3 (Red Line):** The red line starts at approximately 42% at Step 0 and generally increases until around Step 50, reaching approximately 49%. It then fluctuates between approximately 47% and 52% for the remainder of the steps, with some dips below 47% around Step 150 and Step 250. * Step 0: ~42% * Step 50: ~49% * Step 100: ~48% * Step 150: ~47% * Step 200: ~50% * Step 250: ~47% * Step 300: ~50% **RL prior, Pass@3 (Blue Line):** The blue line starts at approximately 45% at Step 0 and increases more rapidly than the red line, reaching approximately 53% at Step 50. It continues to fluctuate, generally remaining above the red line, with peaks around 55% at Step 100 and Step 250. * Step 0: ~45% * Step 50: ~53% * Step 100: ~55% * Step 150: ~52% * Step 200: ~53% * Step 250: ~55% * Step 300: ~54% ### Key Observations * The "RL prior" model consistently achieves a higher "Pass@3" rate than the "SFT prior" model across all steps. * Both models exhibit fluctuations in their "Pass@3" rates, suggesting instability or sensitivity to the training process. * The "RL prior" model shows a more rapid initial increase in "Pass@3" rate compared to the "SFT prior" model. * The "SFT prior" model experiences a noticeable dip in "Pass@3" rate around Step 250, while the "RL prior" model remains relatively stable. ### Interpretation The chart demonstrates that the "RL prior" model outperforms the "SFT prior" model in terms of "Pass@3" rate. This suggests that the reinforcement learning approach (RL prior) is more effective in achieving the desired outcome (passing the criteria) than the supervised fine-tuning approach (SFT prior). The fluctuations in both lines indicate that the training process is not entirely smooth and may require further optimization or regularization. The initial rapid increase in the "RL prior" model suggests that it learns quickly, while the later stability indicates that it converges to a relatively consistent performance level. The dip in the "SFT prior" model around Step 250 could be due to a variety of factors, such as a change in the training data or a temporary instability in the learning process. Further investigation would be needed to determine the root cause of this dip. The "Pass@3" metric likely refers to the percentage of times the model passes a specific test or evaluation after 3 attempts, indicating a measure of robustness or reliability.

## Line Chart: Pass Rate (%) vs. Training Steps for Two Prior Methods ### Overview The image is a line chart comparing the performance of two different prior methods—SFT (Supervised Fine-Tuning) and RL (Reinforcement Learning)—over the course of training steps. The performance metric is the "Pass Rate (%)" for a "Pass@3" evaluation. The chart shows the progression of this metric for both methods from step 0 to step 300. ### Components/Axes * **Chart Type:** Line chart with markers. * **X-Axis:** * **Label:** "Steps" * **Scale:** Linear, from 0 to 300. * **Major Ticks:** 0, 50, 100, 150, 200, 250, 300. * **Y-Axis:** * **Label:** "Pass Rate (%)" * **Scale:** Linear, from 42 to 56. * **Major Ticks:** 42, 44, 46, 48, 50, 52, 54, 56. * **Legend:** * **Position:** Bottom-right corner of the plot area. * **Series 1:** Red line with circular markers, labeled "SFT prior, Pass@3". * **Series 2:** Blue line with circular markers, labeled "RL prior, Pass@3". * **Grid:** A light gray grid is present for both major x and y ticks. ### Detailed Analysis **Data Series 1: SFT prior, Pass@3 (Red Line)** * **Trend:** Shows a general upward trend with significant volatility. It starts at the lowest point on the chart and ends at a high level, but with notable dips. * **Key Data Points (Approximate):** * Step 0: ~42.0% (lowest point for this series) * Step ~180: ~54.2% (peak for this series) * Step 300: ~52.0% * Notable dip at Step ~220: ~46.8% **Data Series 2: RL prior, Pass@3 (Blue Line)** * **Trend:** Also shows a general upward trend with high volatility. It starts higher than the SFT series and achieves the highest overall value on the chart. * **Key Data Points (Approximate):** * Step 0: ~45.5% * Step ~240: ~56.0% (highest point on the entire chart) * Step 300: ~51.5% * Notable dip at Step ~170: ~48.2% ### Key Observations 1. **Initial Performance Gap:** At step 0, the RL prior method starts with a pass rate approximately 3.5 percentage points higher than the SFT prior method. 2. **Overall Improvement:** Both methods demonstrate a clear improvement in pass rate over the 300 training steps. 3. **Volatility:** Both data series are highly volatile, with frequent sharp increases and decreases between consecutive measured steps. 4. **Peak Performance:** The RL prior method achieves the highest recorded pass rate (~56%) at approximately step 240. The SFT prior method's peak (~54.2%) occurs earlier, around step 180. 5. **Convergence and Divergence:** The two lines frequently cross each other, indicating periods where one method outperforms the other. However, the RL prior line is generally above the SFT prior line for the majority of the training steps, especially in the first half. 6. **Final Values:** By step 300, the performance of both methods is relatively close, with SFT prior at ~52% and RL prior at ~51.5%. ### Interpretation This chart likely visualizes the training progress of two different AI model initialization or training strategies ("priors") on a task where success is measured by a "Pass@3" rate (e.g., solving a problem correctly in at least 3 out of 3 attempts). * **What the data suggests:** The Reinforcement Learning (RL) prior appears to provide a stronger starting point and leads to a higher maximum performance ceiling compared to the Supervised Fine-Tuning (SFT) prior. However, both methods are effective at improving the model's capability over time. * **Relationship between elements:** The "Steps" axis represents training iterations. The upward trend in "Pass Rate" for both lines confirms that training is effective. The volatility suggests the training process is noisy or the evaluation metric is sensitive to small model changes. * **Notable patterns/anomalies:** The significant dips (e.g., SFT at step ~220, RL at step ~170) could indicate periods of training instability, catastrophic forgetting, or challenging batches of training data. The fact that both methods recover from these dips shows robustness. The RL prior's ability to reach a higher peak suggests it may be better at escaping local optima or finding a more optimal policy for the task.

# Technical Document Extraction: Line Chart Analysis ## Chart Overview The image depicts a **line chart** comparing two data series over a sequence of steps. The chart visualizes the relationship between **Steps** (x-axis) and **Pass Rate (%)** (y-axis), with two distinct data series differentiated by color and labeled in the legend. --- ### Axis Labels and Markers - **X-Axis (Steps)**: - Title: "Steps" - Range: 0 to 300 - Increment: 50 (0, 50, 100, 150, 200, 250, 300) - **Y-Axis (Pass Rate %)**: - Title: "Pass Rate (%)" - Range: 42% to 56% - Increment: 2% (42%, 44%, 46%, 48%, 50%, 52%, 54%, 56%) --- ### Legend - **Location**: Bottom-right corner of the chart - **Entries**: 1. **Red Dots**: "SFT prior, Pass@3" 2. **Blue Dots**: "RL prior, Pass@3" --- ### Data Series Analysis #### 1. SFT Prior (Red Line) - **Initial Value**: Starts at **42%** (Step 0) - **Trend**: - Gradual upward trajectory until **Step 100** (~48%). - Sharp peak at **Step 200** (~54%). - Post-Step 200: Fluctuates between **48%–54%**, ending at **52%** (Step 300). - **Key Data Points**: - Step 0: 42% - Step 50: 46% - Step 100: 48% - Step 150: 50% - Step 200: 54% - Step 250: 50% - Step 300: 52% #### 2. RL Prior (Blue Line) - **Initial Value**: Starts at **45%** (Step 0) - **Trend**: - Steeper initial rise compared to SFT, peaking at **Step 250** (~56%). - Post-Step 250: Declines to **52%** (Step 300). - **Key Data Points**: - Step 0: 45% - Step 50: 50% - Step 100: 52% - Step 150: 54% - Step 200: 56% - Step 250: 56% - Step 300: 52% --- ### Cross-Reference Validation - **Color Consistency**: - Red data points (SFT) and blue data points (RL) align with the legend. - **Legend Placement**: Confirmed at bottom-right, ensuring clarity for both series. --- ### Observations 1. **SFT Prior** exhibits moderate growth with volatility, peaking mid-chart. 2. **RL Prior** demonstrates sharper initial growth, surpassing SFT, but declines slightly by Step 300. 3. Both series converge near **52%** at Step 300, suggesting similar performance at later steps. --- ### Conclusion The chart highlights divergent performance trends between SFT and RL priors, with RL achieving higher pass rates initially but both stabilizing near 52% by Step 300. No additional textual or tabular data is present in the image.