## Bar Chart: Refusal Ratio by Training Set and Testing Set ### Overview The image is a bar chart comparing the refusal ratio (%) across different training sets (UH Only, AH Only) and testing sets (Factual Asso., Asso. Hallu., Unasso. Halluc.). The chart visualizes how the training data influences the model's refusal to answer based on the type of hallucination present in the testing data. ### Components/Axes * **X-axis:** Training Set (UH Only, AH Only) * **Y-axis:** Refusal Ratio (%) with a scale from 0 to 100, incrementing by 20. * **Legend (Top-Right):** Testing set * Factual Asso. (Green) * Asso. Hallu. (Blue) * Unasso. Halluc. (Red) ### Detailed Analysis **Training Set: UH Only** * **Factual Asso. (Green):** Refusal Ratio is approximately 11%. * **Asso. Hallu. (Blue):** Refusal Ratio is approximately 14%. * **Unasso. Halluc. (Red):** Refusal Ratio is approximately 87%. **Training Set: AH Only** * **Factual Asso. (Green):** Refusal Ratio is approximately 17%. * **Asso. Hallu. (Blue):** Refusal Ratio is approximately 22%. * **Unasso. Halluc. (Red):** Refusal Ratio is approximately 53%. ### Key Observations * For both training sets, the "Unasso. Halluc." testing set has the highest refusal ratio. * The "AH Only" training set generally results in higher refusal ratios across all testing sets compared to the "UH Only" training set. * The difference in refusal ratio between "Unasso. Halluc." and the other two testing sets is much more pronounced for the "UH Only" training set. ### Interpretation The data suggests that the type of training data significantly impacts the model's refusal behavior when faced with different types of hallucinations in the testing data. Specifically, models trained on "UH Only" data are much more likely to refuse to answer when presented with "Unasso. Halluc." compared to "Factual Asso." or "Asso. Hallu.". Training on "AH Only" data seems to mitigate this effect to some extent, leading to a more balanced refusal ratio across different hallucination types. The high refusal rate for "Unasso. Halluc." could indicate that the model struggles to handle or identify this type of hallucination, leading it to refuse to answer more frequently.

# Technical Document Extraction: Refusal Ratio Analysis ## 1. Image Overview This image is a grouped bar chart illustrating the "Refusal Ratio (%)" of a system (likely a Large Language Model) across different training and testing conditions. It compares how training on specific types of data (UH vs. AH) affects the system's tendency to refuse prompts categorized by factual association and hallucination types. ## 2. Component Isolation ### A. Header/Axes * **Y-Axis Label:** Refusal Ratio (%) * **Y-Axis Scale:** 0 to 100, with major markers every 20 units (0, 20, 40, 60, 80, 100). * **X-Axis Label:** Training Set * **X-Axis Categories:** "UH Only" and "AH Only" * **Gridlines:** Horizontal dashed light-gray lines at 20, 40, 60, and 80 on the Y-axis. ### B. Legend The legend defines three categories for the **Testing set**: * **Green:** Factual Asso. * **Blue:** Asso. Hallu. * **Red/Salmon:** Unasso. Halluc. ## 3. Data Extraction and Trend Analysis ### Trend Verification 1. **Unasso. Halluc. (Red):** This series shows the highest refusal ratios in both training scenarios but drops significantly when moving from "UH Only" training to "AH Only" training. 2. **Asso. Hallu. (Blue):** This series shows a moderate increase in refusal ratio when moving from "UH Only" to "AH Only" training. 3. **Factual Asso. (Green):** This series shows the lowest refusal ratios overall, with a slight increase when moving from "UH Only" to "AH Only" training. ### Data Table (Reconstructed) Values are estimated based on the Y-axis scale and gridlines. | Training Set (X-Axis) | Factual Asso. (Green) | Asso. Hallu. (Blue) | Unasso. Halluc. (Red) | | :--- | :--- | :--- | :--- | | **UH Only** | ~11% | ~14% | ~87% | | **AH Only** | ~16% | ~22% | ~53% | ## 4. Detailed Observations * **Dominant Category:** The "Unasso. Halluc." (Unassociated Hallucination) testing set consistently triggers the highest refusal ratio regardless of the training set. * **Impact of Training:** * Training on **"UH Only"** (Unassociated Hallucination) results in an extremely high refusal rate for unassociated hallucinations (~87%) but very low refusal for factual associations (~11%). * Training on **"AH Only"** (Associated Hallucination) leads to a more balanced, though still skewed, refusal profile. It reduces the refusal of unassociated hallucinations to ~53% while slightly increasing the refusal of factual associations and associated hallucinations. * **Cross-Reference Check:** The red bar in the "UH Only" group nearly reaches the 90% mark, while the red bar in the "AH Only" group sits just above the 50% midline between the 40 and 60 gridlines, confirming the data points align with the visual representation.

\n ## Bar Chart: Refusal Ratio by Training and Testing Set ### Overview This bar chart displays the refusal ratio (in percentage) for different testing sets (Factual Association, Associative Hallucination, and Unassociated Hallucination) trained on different training sets (UH Only and AH Only). The chart compares the performance of a system in refusing to answer questions based on the type of hallucination or factual association present in the testing data, and the type of data used for training. ### Components/Axes * **X-axis:** "Training Set" with two categories: "UH Only" and "AH Only". * **Y-axis:** "Refusal Ratio (%)" ranging from 0 to 100, with tick marks at intervals of 20. * **Legend (top-right):** "Testing set" with three categories: * "Factual Asso." (represented by green) * "Asso. Hallu." (represented by blue) * "Unasso. Halluc." (represented by red) ### Detailed Analysis The chart consists of six bars, grouped by training set. **UH Only Training Set:** * **Factual Asso. (Green):** The bar rises to approximately 10%. * **Asso. Hallu. (Blue):** The bar rises to approximately 15%. * **Unasso. Halluc. (Red):** The bar rises to approximately 90%. **AH Only Training Set:** * **Factual Asso. (Green):** The bar rises to approximately 20%. * **Asso. Hallu. (Blue):** The bar rises to approximately 20%. * **Unasso. Halluc. (Red):** The bar rises to approximately 45%. ### Key Observations * The refusal ratio is significantly higher for "Unasso. Halluc." in both training set scenarios. * Training on "UH Only" results in a much higher refusal ratio for "Unasso. Halluc." compared to training on "AH Only". * The refusal ratio for "Factual Asso." and "Asso. Hallu." is relatively low and similar across both training sets. * The "AH Only" training set shows a more balanced refusal ratio across all testing sets compared to the "UH Only" training set. ### Interpretation The data suggests that the system is much more likely to refuse to answer questions that involve unassociated hallucinations, regardless of the training data. However, the training data significantly impacts the refusal rate for unassociated hallucinations. Training solely on "UH Only" data leads to a very high refusal rate for unassociated hallucinations, indicating the model has learned to be highly cautious in such scenarios. Conversely, training on "AH Only" data results in a lower refusal rate for unassociated hallucinations, suggesting the model is more willing to attempt answering even in the presence of unassociated hallucinations. The relatively low refusal rates for "Factual Asso." and "Asso. Hallu." indicate that the system is generally comfortable answering questions that involve factual associations or associative hallucinations. The similar refusal rates across both training sets for these categories suggest that the training data has a less pronounced effect on the system's behavior in these cases. The difference in refusal rates between the training sets highlights the importance of the training data in shaping the system's response to different types of hallucinations. A system trained on a more diverse dataset (potentially including both UH and AH data) might exhibit a more nuanced and balanced refusal behavior.

## Grouped Bar Chart: Refusal Ratio by Training Set and Testing Set ### Overview The image is a grouped bar chart comparing the "Refusal Ratio (%)" of a system (likely an AI model) when tested on three different types of data, after being trained on one of two specific training sets. The chart visually demonstrates how the training data composition affects the model's tendency to refuse responses during testing. ### Components/Axes * **Chart Type:** Grouped Bar Chart. * **Y-Axis:** Labeled **"Refusal Ratio (%)"**. The scale runs from 0 to 100 in increments of 20 (0, 20, 40, 60, 80, 100). * **X-Axis:** Labeled **"Training Set"**. It contains two categorical groups: 1. **"UH Only"** (left group) 2. **"AH Only"** (right group) * **Legend:** Located in the **top-right corner** of the chart area, titled **"Testing set"**. It defines three data series by color: * **Green square:** "Factual Asso." (Factual Association) * **Blue square:** "Asso. Hallu." (Associated Hallucination) * **Red square:** "Unasso. Halluc." (Unassociated Hallucination) ### Detailed Analysis The chart presents data for two training conditions, each tested on three data types. Values are approximate visual estimates. **1. Training Set: "UH Only"** * **Factual Asso. (Green Bar):** The bar height indicates a refusal ratio of approximately **10%**. * **Asso. Hallu. (Blue Bar):** The bar height indicates a refusal ratio of approximately **15%**. * **Unasso. Halluc. (Red Bar):** This is the tallest bar in the group, indicating a very high refusal ratio of approximately **85%**. **2. Training Set: "AH Only"** * **Factual Asso. (Green Bar):** The bar height indicates a refusal ratio of approximately **18%**. * **Asso. Hallu. (Blue Bar):** The bar height indicates a refusal ratio of approximately **22%**. * **Unasso. Halluc. (Red Bar):** The bar height indicates a refusal ratio of approximately **52%**. **Trend Verification:** * For the **"UH Only"** training set, the refusal ratio shows a steep, positive trend from "Factual Asso." to "Asso. Hallu." to "Unasso. Halluc.". * For the **"AH Only"** training set, the refusal ratio also shows a positive trend across the same sequence, but the slope is less steep, and the absolute values are more moderate. ### Key Observations 1. **Dominant Effect of "Unasso. Halluc.":** Across both training sets, the "Unasso. Halluc." testing set (red bars) consistently elicits the highest refusal ratio. 2. **Training Set Impact:** The "UH Only" training set leads to a dramatically higher refusal ratio for "Unasso. Halluc." (~85%) compared to the "AH Only" training set (~52%). 3. **Factual Baseline:** The refusal ratio for "Factual Asso." is the lowest in both groups, serving as a baseline. It is slightly higher in the "AH Only" condition (~18%) than in the "UH Only" condition (~10%). 4. **Associated Hallucination Response:** The refusal ratio for "Asso. Hallu." is intermediate in both groups, sitting between the values for factual data and unassociated hallucinations. ### Interpretation This chart likely illustrates the results of an experiment on AI model safety or alignment, specifically measuring a model's propensity to "refuse" to answer certain prompts. The data suggests a strong correlation between the type of data a model is trained on and its subsequent refusal behavior. * **"UH Only" Training:** Models trained exclusively on data related to **Unassociated Hallucinations** become extremely sensitive to that specific type of prompt during testing, refusing them at a very high rate (85%). However, this specialization comes at a cost: their refusal rate for factual associations is the lowest, suggesting they may be less cautious or discerning with factual information. * **"AH Only" Training:** Models trained on **Associated Hallucinations** show a more balanced, though still elevated, refusal profile. They are less hyper-sensitive to unassociated hallucinations than the UH-only model but maintain a higher baseline refusal rate across all categories, including factual associations. This could indicate a more generalized, but potentially over-cautious, safety behavior. * **Underlying Pattern:** The consistent ordering of refusal rates (Factual < Associated Hallucination < Unassociated Hallucination) across both training regimes indicates a fundamental hierarchy in how the model categorizes and responds to these prompt types. Unassociated hallucinations are treated as the most "dangerous" or requiring the strongest refusal response. The training set primarily modulates the *intensity* of this response, especially for the most extreme category.

## Bar Chart: Refusal Ratio by Training Set and Hallucination Type ### Overview The chart compares refusal ratios (%) across three hallucination types (Factual Asso., Asso. Hallu., Unasso. Halluc.) for two training sets (UH Only, AH Only). Refusal ratios are visualized as grouped bars with distinct colors. ### Components/Axes - **X-axis (Training Set)**: Two categories - "UH Only" (left) and "AH Only" (right). - **Y-axis (Refusal Ratio %)**: Scaled from 0 to 100 in 20% increments. - **Legend**: Located in the top-right corner, mapping colors to hallucination types: - Green: Factual Asso. - Blue: Asso. Hallu. - Red: Unasso. Halluc. ### Detailed Analysis 1. **UH Only Training Set**: - **Unasso. Halluc. (Red)**: ~85% refusal ratio (tallest bar). - **Asso. Hallu. (Blue)**: ~15% refusal ratio. - **Factual Asso. (Green)**: ~10% refusal ratio. 2. **AH Only Training Set**: - **Unasso. Halluc. (Red)**: ~50% refusal ratio. - **Asso. Hallu. (Blue)**: ~20% refusal ratio. - **Factual Asso. (Green)**: ~15% refusal ratio. ### Key Observations - **Dominance of Unasso. Halluc.**: Red bars (Unasso. Halluc.) consistently show the highest refusal ratios in both training sets. - **Training Set Impact**: - UH Only achieves ~85% refusal for Unasso. Halluc., while AH Only drops to ~50%. - Factual Asso. refusal ratios are lowest across all categories (~10-15%). - **Color Consistency**: Legend colors match bar colors exactly (green=green, blue=blue, red=red). ### Interpretation The data suggests that training models exclusively on unassociated hallucinations (UH Only) significantly improves their ability to refuse unassociated hallucinations compared to training on associated hallucinations (AH Only). However, both training approaches struggle with factual associations, indicating a potential gap in handling contextually accurate but non-hallucinatory outputs. The stark contrast between UH and AH training for Unasso. Halluc. refusal (~85% vs. ~50%) highlights the importance of targeted training data composition in mitigating specific hallucination types.