# Technical Document Extraction: Bar Chart Analysis
## Chart Overview
The image contains a comparative bar chart analyzing **mean accuracy (%)** across four tasks (**Coding, Math, Creative Writing, MC**) for two language models: **GLM-4.5-Air** and **Qwen3-30B-A3B**. The chart includes **pruning methods** (REAP, EAN, Frequency) and **merging methods** (HC-SMoE, M-SMoE), with **compression ratios** (0%, 50%, 25%) indicated by dashed lines.
---
## Key Components
### Legend
- **Location**: Right side of the chart.
- **Compression Ratios**:
- 0%: Solid gray line.
- 50%: Dark blue line.
- 25%: Light gray line.
- **Pruning Methods**:
- REAP (ours): Blue.
- EAN: Red.
- Frequency: Green.
- **Merging Methods**:
- HC-SMoE: Yellow.
- M-SMoE: Light blue.
### Axes
- **X-axis**: Tasks (Coding, Math, Creative Writing, MC).
- **Y-axis**: Mean Accuracy (%) ranging from 0% to 90%.
---
## Data Extraction
### GLM-4.5-Air
| Task | REAP (ours) | EAN | Frequency | HC-SMoE | M-SMoE |
|--------------------|-------------|-------|-----------|---------|--------|
| **Coding** | 58% | 52% | 32% | 45% | 30% |
| **Math** | 88% | 82% | 61% | 70% | 58% |
| **Creative Writing** | 82% | 79% | 60% | 78% | 40% |
| **MC** | 72% | 65% | 53% | 68% | 45% |
### Qwen3-30B-A3B
| Task | REAP (ours) | EAN | Frequency | HC-SMoE | M-SMoE |
|--------------------|-------------|-------|-----------|---------|--------|
| **Coding** | 56% | 54% | 48% | 52% | 42% |
| **Math** | 89% | 87% | 85% | 83% | 81% |
| **Creative Writing** | 81% | 77% | 75% | 73% | 70% |
| **MC** | 70% | 63% | 58% | 65% | 50% |
---
## Trends and Observations
1. **REAP (ours)** consistently achieves the highest accuracy across all tasks and models.
2. **Math** task shows the highest performance for both models, with Qwen3-30B-A3B reaching **89%** (REAP).
3. **Coding** task has the lowest accuracy for both models (GLM: 58%, Qwen3: 56%).
4. **Compression Ratios**:
- 0% (solid gray) represents baseline performance.
- 50% (dark blue) and 25% (light gray) indicate reduced accuracy compared to baseline, but exact values are not explicitly labeled in the chart.
5. **Merging Methods** (HC-SMoE, M-SMoE) generally underperform compared to pruning methods.
---
## Spatial Grounding
- **Legend Position**: Right-aligned, outside the main chart area.
- **Bar Colors**: Match legend labels exactly (e.g., REAP = blue, EAN = red).
---
## Component Isolation
### Header
- Title: Not explicitly labeled, but inferred from context as a comparison of pruning/merging methods.
### Main Chart
- **GLM-4.5-Air** (Left):
- Math task dominates with **88%** (REAP).
- Coding task is the weakest (**58%**).
- **Qwen3-30B-A3B** (Right):
- Math task peaks at **89%** (REAP).
- Creative Writing shows strong performance (**81%**).
### Footer
- No explicit footer text; compression ratios are integrated into the legend.
---
## Final Notes
- All data points align with legend color assignments.
- Dashed lines (compression ratios) suggest performance degradation but lack explicit numerical labels.
- REAP (ours) outperforms all other methods in both models.
