## Histogram Grid: Neuron Activation Distributions ### Overview The image presents a grid of 12 histograms, arranged in a 3x4 matrix. Each histogram visualizes the distribution of neuron activations for a specific neuron in different language models (LLaMA-2-7B, LLaMA-3-8B, and Gemma-7B). The histograms compare the activation distributions for "true answer" and "false answer" scenarios, represented by blue and red bars, respectively. ### Components/Axes * **Title:** None explicitly provided for the entire figure, but each subplot has a title indicating the neuron number and "neuron act." (neuron activation). * **X-axis:** Represents the neuron activation value. The range varies across subplots, but generally spans a range of approximately -20 to +20. * **Y-axis:** Represents the number of samples. The scale is consistent across the first two rows, ranging from 0 to 1000. The third row also ranges from 0 to 1000. * **Legend:** Located at the top of the image. * Blue: "true answer" * Red: "false answer" * **Y-axis Label:** "# Samples / LLaMA-2-7B" for the first row, "# Samples / LLaMA-3-8B" for the second row, and "# Samples / Gemma-7B" for the third row. ### Detailed Analysis Here's a breakdown of each subplot, including the neuron number, model, and a description of the distributions: **Row 1: LLaMA-2-7B** * **Plot 1:** 2021-th neuron act. * X-axis: Approximately -10 to 10. * True answer (blue): Peaks around -8, with a sharp drop-off towards 0 and a long tail to the right. Max value ~700. * False answer (red): Peaks around -5, with a broader distribution extending to the right. Max value ~300. * **Plot 2:** 149-th neuron act. * X-axis: Approximately -10 to 10. * True answer (blue): Peaks around 5, with a long tail to the left. Max value ~500. * False answer (red): Peaks around 5, with a smaller distribution. Max value ~200. * **Plot 3:** 3556-th neuron act. * X-axis: Approximately -40 to 20. * True answer (blue): Peaks around -25, with a sharp drop-off towards 0 and a long tail to the right. Max value ~900. * False answer (red): Peaks around -20, with a broader distribution extending to the right. Max value ~300. * **Plot 4:** 2672-th neuron act. * X-axis: Approximately -2.5 to 5.0. * True answer (blue): Peaks around 2.5, with a long tail to the left. Max value ~500. * False answer (red): Peaks around 2.5, with a smaller distribution. Max value ~200. **Row 2: LLaMA-3-8B** * **Plot 5:** 1917-th neuron act. * X-axis: Approximately -20 to 20. * True answer (blue): Peaks around -10, with a long tail to the right. Max value ~400. * False answer (red): Peaks around -5, with a broader distribution extending to the right. Max value ~200. * **Plot 6:** 4055-th neuron act. * X-axis: Approximately -20 to 0. * True answer (blue): Peaks around -15, with a long tail to the right. Max value ~400. * False answer (red): Peaks around -10, with a broader distribution extending to the right. Max value ~200. * **Plot 7:** 3795-th neuron act. * X-axis: Approximately -15 to 5. * True answer (blue): Peaks around -8, with a long tail to the right. Max value ~500. * False answer (red): Peaks around -5, with a broader distribution extending to the right. Max value ~200. * **Plot 8:** 3939-th neuron act. * X-axis: Approximately -10 to 10. * True answer (blue): Peaks around -5, with a long tail to the right. Max value ~400. * False answer (red): Peaks around -2, with a broader distribution extending to the right. Max value ~200. **Row 3: Gemma-7B** * **Plot 9:** 2944-th neuron act. * X-axis: Approximately -5 to 5. * True answer (blue): Peaks around -2, with a long tail to the right. Max value ~400. * False answer (red): Peaks around -1, with a broader distribution extending to the right. Max value ~200. * **Plot 10:** 96-th neuron act. * X-axis: Approximately -10 to 5. * True answer (blue): Peaks around -5, with a long tail to the right. Max value ~400. * False answer (red): Peaks around -2, with a broader distribution extending to the right. Max value ~200. * **Plot 11:** 156-th neuron act. * X-axis: Approximately -5 to 5. * True answer (blue): Peaks around 2, with a long tail to the left. Max value ~400. * False answer (red): Peaks around 3, with a broader distribution extending to the left. Max value ~200. * **Plot 12:** 23-th neuron act. * X-axis: Approximately -5 to 5. * True answer (blue): Peaks around 2, with a long tail to the left. Max value ~400. * False answer (red): Peaks around 3, with a broader distribution extending to the left. Max value ~200. ### Key Observations * The distributions of neuron activations differ significantly between "true answer" and "false answer" scenarios. * The "true answer" distributions tend to have sharper peaks, while the "false answer" distributions are broader. * The activation ranges vary across different neurons. * The LLaMA-2-7B model seems to have a wider range of activation values compared to LLaMA-3-8B and Gemma-7B. * The number of samples is consistent across all plots, allowing for direct comparison of the distributions. ### Interpretation The histograms provide insights into how different neurons in the language models respond to "true" and "false" answers. The distinct distributions suggest that these neurons play a role in distinguishing between correct and incorrect responses. The sharper peaks in the "true answer" distributions may indicate a more focused and specific activation pattern when the model is providing a correct answer. The broader "false answer" distributions could reflect a more diffuse or less certain activation pattern when the model is making a mistake. The differences in activation ranges and distributions across different neurons highlight the diverse roles that individual neurons play in the overall functioning of the language models. Comparing the distributions across the three models (LLaMA-2-7B, LLaMA-3-8B, and Gemma-7B) could reveal differences in their internal representations and processing strategies.

\n ## Histograms: Neuron Activation Distributions ### Overview The image presents a 3x4 grid of histograms, visualizing the distribution of neuron activations for different models (Llama-2-7B, Llama-3-8B, and Gemma-7B) and specific neurons within those models. Each histogram represents the activation values for a single neuron, with the x-axis indicating the activation value and the y-axis representing the number of samples. Two distributions are plotted on each histogram: one for "true answer" activations (in blue) and one for "false answer" activations (in red). ### Components/Axes * **Y-axis Label (all plots):** "# Samples / [Model Name]" - indicating the count of samples for each activation range, normalized by the model name. * **X-axis Label (all plots):** "[Neuron Number]-th neuron act." - indicating the activation value for the specified neuron. * **Legend (top-left plot):** * Blue: "true answer" * Red: "false answer" * **Models:** Llama-2-7B, Llama-3-8B, Gemma-7B * **Neuron Numbers:** 2021, 149, 3556, 2672, 1917, 4055, 3795, 3939, 2944, 96, 156, 23. ### Detailed Analysis or Content Details **Row 1: Llama-2-7B** * **2021-th neuron act.:** The "false answer" distribution (red) is centered around -2, with a peak at approximately 800 samples. The "true answer" distribution (blue) is centered around 0, with a peak at approximately 600 samples. Both distributions are relatively broad. * **149-th neuron act.:** The "false answer" distribution (red) is centered around 0, with a peak at approximately 900 samples. The "true answer" distribution (blue) is also centered around 0, with a peak at approximately 500 samples. Both distributions are relatively narrow. * **3556-th neuron act.:** The "false answer" distribution (red) is strongly centered around -15, with a peak at approximately 900 samples. The "true answer" distribution (blue) is centered around 2, with a peak at approximately 400 samples. The "false answer" distribution is much more concentrated. * **2672-th neuron act.:** The "true answer" distribution (blue) is centered around 2.5, with a peak at approximately 800 samples. The "false answer" distribution (red) is centered around 0, with a peak at approximately 300 samples. **Row 2: Llama-3-8B** * **1917-th neuron act.:** The "false answer" distribution (red) is centered around -5, with a peak at approximately 700 samples. The "true answer" distribution (blue) is centered around 5, with a peak at approximately 600 samples. * **4055-th neuron act.:** The "false answer" distribution (red) is centered around -10, with a peak at approximately 800 samples. The "true answer" distribution (blue) is centered around -2, with a peak at approximately 400 samples. * **3795-th neuron act.:** The "false answer" distribution (red) is centered around -2, with a peak at approximately 600 samples. The "true answer" distribution (blue) is centered around 1, with a peak at approximately 500 samples. * **3939-th neuron act.:** The "false answer" distribution (red) is centered around -5, with a peak at approximately 700 samples. The "true answer" distribution (blue) is centered around 5, with a peak at approximately 600 samples. **Row 3: Gemma-7B** * **2944-th neuron act.:** The "false answer" distribution (red) is centered around -1, with a peak at approximately 500 samples. The "true answer" distribution (blue) is centered around 1, with a peak at approximately 400 samples. * **96-th neuron act.:** The "false answer" distribution (red) is centered around -1, with a peak at approximately 400 samples. The "true answer" distribution (blue) is centered around 1, with a peak at approximately 300 samples. * **156-th neuron act.:** The "false answer" distribution (red) is centered around 0, with a peak at approximately 400 samples. The "true answer" distribution (blue) is centered around 2, with a peak at approximately 300 samples. * **23-th neuron act.:** The "false answer" distribution (red) is centered around -2, with a peak at approximately 400 samples. The "true answer" distribution (blue) is centered around 2, with a peak at approximately 300 samples. ### Key Observations * The distributions for "false answers" generally tend to be more concentrated and shifted towards negative activation values compared to "true answers." * There is significant variation in the activation distributions across different neurons within each model. * Llama-2-7B shows the most distinct separation between "true" and "false" answer distributions in some neurons (e.g., 3556-th neuron). * Gemma-7B generally exhibits less separation between the two distributions compared to Llama-2-7B and Llama-3-8B. ### Interpretation These histograms provide insights into how different neurons respond to correct and incorrect answers. The shift in distributions suggests that certain neurons are more strongly activated when the model provides a correct answer, while others might be more active when the answer is incorrect. The concentration of distributions indicates the consistency of the neuron's response. The differences between models suggest variations in their internal representations and processing mechanisms. Llama-2-7B's clearer separation might indicate a more robust encoding of correct answers in certain neurons. Gemma-7B's less distinct separation could imply a more distributed or nuanced representation. The variations across neurons within each model highlight the complexity of neural networks and the specialized roles that individual neurons might play. Analyzing these distributions can help understand the model's decision-making process and identify potential areas for improvement. The data suggests that neuron activations are not uniform across models and neurons, and that there is a correlation between activation patterns and answer correctness. Further investigation could involve analyzing the activations of specific neurons during different types of questions or tasks.

\n ## Histogram Grid: Neuron Activation Distributions by Model and Neuron Index ### Overview The image displays a 3x4 grid of histograms, each showing the distribution of activation values for a specific neuron within a specific large language model (LLM). The distributions are split into two categories: activations associated with "true answers" (blue) and "false answers" (red). The purpose is to visualize how the activation patterns of individual neurons differ based on the correctness of the model's output. ### Components/Axes * **Legend:** Located at the top center. It defines two data series: * **Blue:** "true answer" * **Red:** "false answer" * **Y-Axis (Shared per row):** Labeled "# Samples / [Model Name]". The scale is consistent within each row, ranging from 0 to 1000, with tick marks at 0, 200, 400, 600, 800, and 1000. This represents the count of samples falling into each activation bin. * **X-Axis (Per subplot):** Labeled with the specific neuron index being analyzed (e.g., "2021-th neuron act."). The numerical scale and range vary significantly between subplots. * **Row Labels (Left side):** Identify the model for each row of histograms: * **Top Row:** LLaMA-2-7B * **Middle Row:** LLaMA-3-8B * **Bottom Row:** Gemma-7B ### Detailed Analysis The grid is processed row by row, from left to right. **Row 1: LLaMA-2-7B** 1. **Top-Left (Neuron 2021):** X-axis range approx. -15 to 5. Both distributions are centered around -8. The "true answer" (blue) distribution has a much higher peak (~650 samples) compared to the "false answer" (red, ~300 samples). The distributions overlap heavily. 2. **Top-Center-Left (Neuron 149):** X-axis range approx. -10 to 15. Distributions are centered around +7. Blue peak (~500) is higher than red peak (~200). Significant overlap. 3. **Top-Center-Right (Neuron 3556):** X-axis range approx. -40 to 30. A very sharp, high peak for "true answer" (blue) centered near -30, reaching over 1000 samples. The "false answer" (red) distribution is much lower and broader, centered around -25 with a peak of ~300. This shows the strongest separation between classes in this row. 4. **Top-Right (Neuron 2672):** X-axis range approx. -3 to 6. Distributions centered around +2.5. Blue peak (~550) is higher than red peak (~200). Substantial overlap. **Row 2: LLaMA-3-8B** 1. **Middle-Left (Neuron 1917):** X-axis range approx. -20 to 20. Distributions centered around -8. Blue peak (~450) is higher than red peak (~200). Overlap is significant. 2. **Middle-Center-Left (Neuron 4055):** X-axis range approx. -20 to 0. Distributions centered around -16. Blue peak (~500) is higher than red peak (~200). Overlap is significant. 3. **Middle-Center-Right (Neuron 3795):** X-axis range approx. -15 to 5. Distributions centered around -7. Blue peak (~600) is higher than red peak (~200). Overlap is significant. 4. **Middle-Right (Neuron 3939):** X-axis range approx. -15 to 10. Distributions centered around -10. Blue peak (~650) is higher than red peak (~200). Overlap is significant. **Row 3: Gemma-7B** 1. **Bottom-Left (Neuron 2944):** X-axis range approx. -8 to 5. Distributions centered around -4. Blue peak (~450) is higher than red peak (~150). Overlap is significant. 2. **Bottom-Center-Left (Neuron 96):** X-axis range approx. -10 to 5. Distributions centered around -6. Blue peak (~350) is higher than red peak (~150). Overlap is significant. 3. **Bottom-Center-Right (Neuron 156):** X-axis range approx. -2 to 8. Distributions centered around +4. Blue peak (~400) is higher than red peak (~200). Overlap is significant. 4. **Bottom-Right (Neuron 23):** X-axis range approx. -6 to 8. Distributions centered around +4. Blue peak (~350) is higher than red peak (~200). Overlap is significant. ### Key Observations 1. **Consistent Pattern:** In all 12 histograms, the distribution for "true answer" (blue) has a higher peak (more samples concentrated around the mode) than the distribution for "false answer" (red). 2. **Overlap:** There is substantial overlap between the blue and red distributions in nearly all cases, indicating that the activation value of a single neuron is not a perfect classifier for answer correctness. 3. **Outlier - Strong Separation:** The histogram for **LLaMA-2-7B, Neuron 3556** (top row, third from left) is a notable exception. It shows a very sharp, high peak for true answers at a much lower activation value (~-30) compared to the broader, lower distribution for false answers. This suggests this specific neuron may be a particularly strong indicator for this model. 4. **Activation Range Variability:** The optimal activation range (where the peak occurs) varies widely across neurons and models, from negative values (e.g., -30 for LLaMA-2-7B Neuron 3556) to positive values (e.g., +7 for LLaMA-2-7B Neuron 149). 5. **Model Comparison:** The distributions for LLaMA-3-8B (middle row) appear slightly more consistent in shape and separation across the four sampled neurons compared to the other two models. ### Interpretation This visualization is likely from a mechanistic interpretability study aiming to understand how internal neural activations correlate with model performance. The data suggests that: * **Neurons as Features:** Individual neurons can act as features whose activation strength carries information about the correctness of the model's output. The consistent pattern of higher peaks for true answers implies these neurons are more reliably or strongly activated in correct response scenarios. * **Distributed Representation:** The significant overlap in most plots indicates that correctness is not encoded by a single neuron in an "on/off" manner. Instead, it is likely represented in a distributed fashion across many neurons, where the combined pattern of activations is more informative than any single value. * **Specialized Neurons:** The outlier case (LLaMA-2-7B, Neuron 3556) demonstrates that some neurons may become highly specialized for detecting conditions leading to correct or incorrect outputs, showing a clearer separation in their activation distributions. * **Model-Specific Internals:** The differences in activation ranges and distribution shapes between LLaMA-2, LLaMA-3, and Gemma highlight that different models develop distinct internal representations, even when performing similar tasks. This has implications for model comparison and the transfer of interpretability findings. In summary, the image provides empirical evidence that single-neuron activations are weak but consistent signals for answer correctness in LLMs, with occasional neurons showing stronger specialization. It underscores the complexity of neural network internals and the challenge of pinpointing exact causal mechanisms.

## Grid of Histograms: Neuron Activity Distributions for True vs. False Answers ### Overview The image displays a 4x3 grid of histograms comparing neuron activity distributions for "true answer" (blue) and "false answer" (red) classifications. Each subplot corresponds to a specific neuron (e.g., "2021-th neuron act.") and visualizes the frequency of neuron activation values across samples. The histograms are normalized to show counts on the y-axis, with x-axis ranges varying per neuron. ### Components/Axes - **Legend**: Located at the top center, with: - **Blue**: True answer - **Red**: False answer - **X-axis**: Labeled "Neuron act." with ranges varying per subplot (e.g., -10 to 10, -40 to 20, -15 to 5). - **Y-axis**: Labeled "# Samples / LLaMA-2-7B" for the first three rows and "# Samples / Gemma-7B" for the last row. Scales range from 0 to 1000. - **Subplot Titles**: Each histogram is labeled with the neuron number (e.g., "2021-th neuron act."). ### Detailed Analysis 1. **2021-th neuron act.**: - X-axis: -10 to 10 - Blue peak: ~0 (count ~600) - Red peak: ~-5 (count ~300) 2. **149-th neuron act.**: - X-axis: -10 to 10 - Blue peak: ~0 (count ~500) - Red peak: ~-10 (count ~200) 3. **3556-th neuron act.**: - X-axis: -40 to 20 - Blue peak: ~0 (count ~800) - Red peak: ~-20 (count ~100) 4. **2672-th neuron act.**: - X-axis: -15 to 5 - Blue peak: ~-10 (count ~400) - Red peak: ~-15 (count ~150) 5. **1917-th neuron act.**: - X-axis: -5 to 5 - Blue peak: ~0 (count ~450) - Red peak: ~-5 (count ~200) 6. **4055-th neuron act.**: - X-axis: -10 to 10 - Blue peak: ~-5 (count ~550) - Red peak: ~-10 (count ~250) 7. **3795-th neuron act.**: - X-axis: -5 to 5 - Blue peak: ~5 (count ~600) - Red peak: ~0 (count ~300) 8. **2944-th neuron act.**: - X-axis: -10 to 10 - Blue peak: ~0 (count ~500) - Red peak: ~-5 (count ~250) 9. **96-th neuron act.**: - X-axis: -10 to 10 - Blue peak: ~-5 (count ~450) - Red peak: ~-10 (count ~200) 10. **156-th neuron act.**: - X-axis: -5 to 5 - Blue peak: ~5 (count ~550) - Red peak: ~0 (count ~300) 11. **3939-th neuron act.**: - X-axis: -5 to 5 - Blue peak: ~5 (count ~600) - Red peak: ~0 (count ~300) 12. **23-th neuron act.**: - X-axis: -5 to 5 - Blue peak: ~5 (count ~550) - Red peak: ~0 (count ~300) ### Key Observations - **Peak Activity**: True answers (blue) generally show higher peak counts than false answers (red) across most neurons. - **X-axis Variability**: Neuron activity ranges differ significantly (e.g., 3556-th neuron spans -40 to 20, while others are narrower). - **Model-Specific Labels**: The last row uses "Gemma-7B" instead of "LLaMA-2-7B" for the y-axis, suggesting dataset/model differences. - **Outliers**: The 3556-th neuron has the highest blue peak (~800 samples), indicating a strong signal for true answers. ### Interpretation The histograms suggest that neuron activity patterns correlate with answer correctness. True answers often exhibit higher-frequency activation at specific values (e.g., near 0 or positive ranges), while false answers show lower or shifted peaks. The 3556-th neuron’s extreme blue peak implies it may be a critical feature for distinguishing correct responses. The shift in y-axis labels from LLaMA-2-7B to Gemma-7B in the final row hints at methodological changes or dataset variations between groups. These patterns could inform neural network interpretability or model debugging efforts.