## Bar Chart: Prediction Flip Rate Comparison ### Overview The image presents two bar charts comparing the prediction flip rates of two versions of the Mistral-7B model (v0.1 and v0.3) across different datasets. The charts show the prediction flip rates for both Q-Anchored (exact_question) and A-Anchored (exact_question) methods. ### Components/Axes * **Titles:** * Left Chart: Mistral-7B-v0.1 * Right Chart: Mistral-7B-v0.3 * **Y-axis:** Prediction Flip Rate * Scale: 0 to 80, with tick marks at 0, 20, 40, 60, and 80. * **X-axis:** Dataset * Categories: PopQA, TriviaQA, HotpotQA, NQ * **Legend:** Located at the bottom of the image. * Q-Anchored (exact\_question): Represented by a muted red/brown color. * A-Anchored (exact\_question): Represented by a gray color. ### Detailed Analysis **Left Chart: Mistral-7B-v0.1** * **PopQA:** * Q-Anchored: Approximately 76 * A-Anchored: Approximately 42 * **TriviaQA:** * Q-Anchored: Approximately 84 * A-Anchored: Approximately 56 * **HotpotQA:** * Q-Anchored: Approximately 72 * A-Anchored: Approximately 20 * **NQ:** * Q-Anchored: Approximately 78 * A-Anchored: Approximately 58 **Right Chart: Mistral-7B-v0.3** * **PopQA:** * Q-Anchored: Approximately 76 * A-Anchored: Approximately 38 * **TriviaQA:** * Q-Anchored: Approximately 86 * A-Anchored: Approximately 56 * **HotpotQA:** * Q-Anchored: Approximately 72 * A-Anchored: Approximately 14 * **NQ:** * Q-Anchored: Approximately 78 * A-Anchored: Approximately 32 ### Key Observations * In both charts, the Q-Anchored method consistently shows a higher prediction flip rate than the A-Anchored method across all datasets. * The TriviaQA dataset generally has the highest prediction flip rate for the Q-Anchored method in both versions. * The HotpotQA dataset has the lowest prediction flip rate for the A-Anchored method in both versions. * Comparing the two versions, the A-Anchored method shows a decrease in prediction flip rate for HotpotQA and NQ in v0.3 compared to v0.1. ### Interpretation The data suggests that anchoring the question (Q-Anchored) leads to a higher prediction flip rate compared to anchoring the answer (A-Anchored) for both versions of the Mistral-7B model. This could indicate that the model is more sensitive to changes or perturbations in the question than in the answer. The decrease in prediction flip rate for the A-Anchored method in v0.3 for HotpotQA and NQ datasets might indicate an improvement in the model's robustness to answer-related perturbations for those specific datasets. The consistent high flip rate for Q-Anchored TriviaQA suggests that this dataset might be particularly challenging for the model in terms of question understanding or robustness.

\n ## Bar Chart: Prediction Flip Rate Comparison for Mistral Models ### Overview This image presents a comparative bar chart illustrating the Prediction Flip Rate for two versions of the Mistral-7B model (v0.1 and v0.3) across four different datasets: PopQA, TriviaQA, HotpotQA, and NQ. The chart compares the flip rates for questions anchored to the original question ("Q-Anchored") versus those anchored to the answer ("A-Anchored"). ### Components/Axes * **X-axis:** Dataset - PopQA, TriviaQA, HotpotQA, NQ. * **Y-axis:** Prediction Flip Rate - Scale ranges from 0 to 80. * **Two Charts:** Side-by-side bar charts, one for Mistral-7B-v0.1 and one for Mistral-7B-v0.3. * **Legend:** Located at the bottom-center of the image. * Red: Q-Anchored (exact\_question) * Gray: A-Anchored (exact\_question) * **Titles:** Each chart has a title indicating the model version: "Mistral-7B-v0.1" and "Mistral-7B-v0.3". ### Detailed Analysis **Mistral-7B-v0.1 Chart:** * **PopQA:** Q-Anchored: Approximately 72. A-Anchored: Approximately 32. * **TriviaQA:** Q-Anchored: Approximately 80. A-Anchored: Approximately 52. * **HotpotQA:** Q-Anchored: Approximately 72. A-Anchored: Approximately 24. * **NQ:** Q-Anchored: Approximately 80. A-Anchored: Approximately 32. **Mistral-7B-v0.3 Chart:** * **PopQA:** Q-Anchored: Approximately 64. A-Anchored: Approximately 36. * **TriviaQA:** Q-Anchored: Approximately 80. A-Anchored: Approximately 52. * **HotpotQA:** Q-Anchored: Approximately 68. A-Anchored: Approximately 24. * **NQ:** Q-Anchored: Approximately 76. A-Anchored: Approximately 32. **Trends:** * In both models, the Q-Anchored flip rate is consistently higher than the A-Anchored flip rate across all datasets. * For both models, the highest Q-Anchored flip rates are observed for TriviaQA and NQ datasets, reaching approximately 80. * The A-Anchored flip rates are generally lower, ranging from approximately 24 to 52. * The v0.3 model shows a slight decrease in Q-Anchored flip rates compared to v0.1 for PopQA, HotpotQA, and NQ. ### Key Observations * The difference between Q-Anchored and A-Anchored flip rates is substantial, suggesting that anchoring to the question significantly impacts prediction stability. * TriviaQA and NQ datasets consistently elicit higher flip rates for Q-Anchored questions. * HotpotQA consistently shows the lowest A-Anchored flip rate. * The v0.3 model appears to be slightly more stable than v0.1 for some datasets (PopQA, HotpotQA, NQ) based on the lower Q-Anchored flip rates. ### Interpretation The data suggests that the Mistral models are more sensitive to changes when the prediction is evaluated based on the original question (Q-Anchored) compared to when it's evaluated based on the answer (A-Anchored). This could indicate that the models rely more heavily on the question context during prediction. The higher flip rates for TriviaQA and NQ might be due to the complexity or ambiguity of the questions in these datasets. The slight decrease in Q-Anchored flip rates in v0.3 for certain datasets suggests a potential improvement in model stability with the newer version, although the difference is not drastic. The consistent lower A-Anchored flip rates across all datasets indicate that the model is more confident in its predictions when evaluated against the answer, potentially because the answer provides a stronger constraint. The difference in flip rates between Q-Anchored and A-Anchored could be a metric for evaluating the robustness of the model's reasoning process.

## Bar Chart: Prediction Flip Rate Comparison for Mistral-7B Models ### Overview The image displays two grouped bar charts side-by-side, comparing the "Prediction Flip Rate" of two versions of the Mistral-7B language model (v0.1 and v0.3) across four question-answering datasets. The metric likely measures how often a model's prediction changes when prompted with a specific anchoring method. ### Components/Axes * **Chart Type:** Grouped Bar Chart (two subplots). * **Y-Axis (Both Charts):** Label: "Prediction Flip Rate". Scale: 0 to 80, with major gridlines at intervals of 20 (0, 20, 40, 60, 80). The unit is implied to be percentage (%). * **X-Axis (Both Charts):** Label: "Dataset". Categories (from left to right): "PopQA", "TriviaQA", "HotpotQA", "NQ". * **Legend (Bottom Center):** Two entries. * **Color:** Reddish-brown (approx. hex #B07171). **Label:** "Q-Anchored (exact_question)" * **Color:** Gray (approx. hex #999999). **Label:** "A-Anchored (exact_question)" * **Subplot Titles (Top Center):** * Left Chart: "Mistral-7B-v0.1" * Right Chart: "Mistral-7B-v0.3" ### Detailed Analysis **Mistral-7B-v0.1 (Left Chart):** * **PopQA:** * Q-Anchored (Reddish-brown): Bar height is approximately 75%. * A-Anchored (Gray): Bar height is approximately 42%. * **TriviaQA:** * Q-Anchored (Reddish-brown): Bar height is the highest in this chart, approximately 85%. * A-Anchored (Gray): Bar height is approximately 55%. * **HotpotQA:** * Q-Anchored (Reddish-brown): Bar height is approximately 72%. * A-Anchored (Gray): Bar height is the lowest in this chart, approximately 20%. * **NQ:** * Q-Anchored (Reddish-brown): Bar height is approximately 83%. * A-Anchored (Gray): Bar height is approximately 45%. **Mistral-7B-v0.3 (Right Chart):** * **PopQA:** * Q-Anchored (Reddish-brown): Bar height is approximately 77%. * A-Anchored (Gray): Bar height is approximately 38%. * **TriviaQA:** * Q-Anchored (Reddish-brown): Bar height is the highest in this chart, approximately 88%. * A-Anchored (Gray): Bar height is approximately 56%. * **HotpotQA:** * Q-Anchored (Reddish-brown): Bar height is approximately 69%. * A-Anchored (Gray): Bar height is the lowest in the entire image, approximately 15%. * **NQ:** * Q-Anchored (Reddish-brown): Bar height is approximately 79%. * A-Anchored (Gray): Bar height is approximately 34%. ### Key Observations 1. **Consistent Dominance:** In every single dataset and for both model versions, the "Q-Anchored" method results in a significantly higher Prediction Flip Rate than the "A-Anchored" method. 2. **Dataset Sensitivity:** The "HotpotQA" dataset shows the most extreme disparity between the two anchoring methods. The A-Anchored flip rate for HotpotQA is dramatically lower (~15-20%) compared to other datasets (~34-56%). 3. **Model Version Comparison:** The overall pattern is very similar between v0.1 and v0.3. However, for the A-Anchored method, the flip rates appear slightly lower in v0.3 across all datasets (e.g., NQ drops from ~45% to ~34%, HotpotQA from ~20% to ~15%). The Q-Anchored rates remain relatively stable or show minor increases. 4. **Highest Flip Rate:** The highest recorded flip rate is for TriviaQA using the Q-Anchored method in model v0.3 (~88%). ### Interpretation This chart investigates model sensitivity to prompt formulation. The "Prediction Flip Rate" likely measures how often a model's answer changes when the prompt is anchored to the exact question (Q-Anchored) versus anchored to the exact answer (A-Anchored). * **Core Finding:** Models are far more sensitive to variations or perturbations when anchored to the question itself. This suggests that the model's reasoning or retrieval process tied directly to the question phrasing is less stable. Conversely, anchoring to the answer appears to produce more consistent predictions. * **Dataset Implication:** The HotpotQA dataset, which often involves multi-hop reasoning, shows the most stable predictions under A-Anchoring. This could imply that for complex reasoning tasks, once an answer is provided as an anchor, the model's output is highly consistent, whereas question-based prompting for the same task is highly variable. * **Model Evolution:** The slight decrease in A-Anchored flip rates from v0.1 to v0.3 might indicate an improvement in model consistency when the answer is provided as context, though the fundamental sensitivity pattern remains unchanged. * **Practical Takeaway:** For applications requiring stable, reproducible outputs from this model family, providing the answer within the prompt (A-Anchoring) is a more reliable strategy than relying solely on the question (Q-Anchoring). The choice of dataset also critically impacts this stability.

## Bar Chart: Prediction Flip Rate Comparison for Mistral-7B Models (v0.1 and v0.3) ### Overview The image contains two side-by-side bar charts comparing prediction flip rates for two versions of the Mistral-7B language model (v0.1 and v0.3) across four question-answering datasets: PopQA, TriviaQA, HotpotQA, and NQ. Each dataset is evaluated using two anchoring methods: **Q-Anchored (exact_question)** (red bars) and **A-Anchored (exact_question)** (gray bars). The y-axis represents prediction flip rate (0–80%), and the x-axis lists datasets. --- ### Components/Axes - **X-Axis (Datasets)**: PopQA, TriviaQA, HotpotQA, NQ (left to right). - **Y-Axis (Prediction Flip Rate)**: Scaled from 0 to 80% in increments of 20. - **Legend**: Located at the bottom of both charts. Red = Q-Anchored (exact_question), Gray = A-Anchored (exact_question). - **Chart Titles**: - Left chart: "Mistral-7B-v0.1" - Right chart: "Mistral-7B-v0.3" --- ### Detailed Analysis #### Mistral-7B-v0.1 (Left Chart) - **Q-Anchored (red)**: - PopQA: ~75% - TriviaQA: ~82% - HotpotQA: ~72% - NQ: ~81% - **A-Anchored (gray)**: - PopQA: ~40% - TriviaQA: ~55% - HotpotQA: ~18% - NQ: ~45% #### Mistral-7B-v0.3 (Right Chart) - **Q-Anchored (red)**: - PopQA: ~76% - TriviaQA: ~85% - HotpotQA: ~65% - NQ: ~77% - **A-Anchored (gray)**: - PopQA: ~35% - TriviaQA: ~52% - HotpotQA: ~12% - NQ: ~32% --- ### Key Observations 1. **Q-Anchored Consistently Outperforms A-Anchored**: - Across all datasets and models, Q-Anchored rates are significantly higher than A-Anchored (e.g., TriviaQA v0.1: 82% vs. 55%). 2. **HotpotQA Anomaly**: - A-Anchored performance drops sharply in v0.3 (18% → 12%), while Q-Anchored also declines (72% → 65%). 3. **TriviaQA Dominance**: - TriviaQA shows the highest Q-Anchored rates for both models (82% and 85%). 4. **NQ Dataset**: - NQ has the lowest A-Anchored rates (45% and 32%) but remains the second-highest for Q-Anchored in v0.1. --- ### Interpretation - **Effectiveness of Q-Anchoring**: The consistent superiority of Q-Anchored suggests that grounding predictions on the exact question text improves accuracy, likely by reducing ambiguity. - **Model Version Impact**: - v0.3 shows reduced performance in HotpotQA for both anchoring methods, possibly due to architectural changes or dataset-specific biases. - A-Anchored degradation in HotpotQA (v0.3) may indicate overfitting or misalignment with the dataset’s structure. - **Dataset Sensitivity**: TriviaQA’s high performance implies it aligns well with the model’s training data or prompting strategy, while HotpotQA’s volatility suggests sensitivity to model updates. --- ### Spatial Grounding & Verification - **Legend Position**: Bottom center, clearly associating colors with anchoring methods. - **Bar Alignment**: Red (Q-Anchored) bars are consistently taller than gray (A-Anchored) bars across all datasets and models. - **Trend Verification**: - Q-Anchored trends upward for TriviaQA and NQ in v0.3, while HotpotQA trends downward. - A-Anchored rates decline for HotpotQA in v0.3, confirming model version impact. --- ### Conclusion The data demonstrates that Q-Anchored (exact_question) significantly enhances prediction reliability compared to A-Anchored methods. The decline in HotpotQA performance in v0.3 warrants further investigation into dataset-model compatibility. TriviaQA’s consistent high performance highlights its suitability for evaluating question-answering systems.