## Bar Chart: MetaQA 1-Hop Hit@1 Scores (Mean ± Std) for Different N and K ### Overview The chart compares the performance of a retrieval system (MetaQA) across three configurations: varying the number of hops for candidate retrieval (N = 1, 2, 3) and the number of candidates considered (K = 10, 20, 30). Scores are reported as mean Hit@1 with standard deviation error bars. ### Components/Axes - **X-axis**: "Number of Hops for Candidate Retrieval (N)" with categories 1, 2, 3. - **Y-axis**: "Hit@1 Score" scaled from 0.0 to 1.0. - **Legend**: Located at the bottom-right, mapping colors to K values: - Light blue: K=10 - Medium blue: K=20 - Dark blue: K=30 - **Bars**: Grouped by N, with three bars per category (one per K value). Error bars represent standard deviation. ### Detailed Analysis - **N=1**: - K=10: ~0.95 (±0.02) - K=20: ~0.94 (±0.02) - K=30: ~0.93 (±0.02) - **N=2**: - K=10: ~0.93 (±0.02) - K=20: ~0.92 (±0.02) - K=30: ~0.91 (±0.02) - **N=3**: - K=10: ~0.90 (±0.02) - K=20: ~0.89 (±0.02) - K=30: ~0.88 (±0.02) ### Key Observations 1. **Consistent Decline with Increasing K**: For all N values, Hit@1 scores decrease slightly as K increases (e.g., K=10 to K=30 drops ~0.05–0.07). 2. **Minimal Impact of N**: Scores remain relatively stable across N=1, 2, 3, with only minor reductions as N increases. 3. **Low Variability**: Error bars are small (~±0.02), indicating consistent performance across trials. ### Interpretation The data suggests that increasing the number of candidates (K) marginally reduces retrieval effectiveness, likely due to dilution of high-quality candidates in larger pools. However, the system maintains high performance (scores >0.88) across all configurations, indicating robustness. The minimal impact of N implies that extending the number of hops does not significantly degrade performance, possibly due to effective candidate filtering. The error bars confirm reliability, as no configuration shows statistically significant divergence.