QB
Q-Future/Q-Bench
①[ICLR2024 Spotlight] (GPT-4V/Gemini-Pro/Qwen-VL-Plus+16 OS MLLMs) A benchmark for multi-modality LLMs (MLLMs) on low-level vision and visual quality assessment.
283 13 +0/wk
GitHub
gpt-4 iclr image-quality-assessment large-language-models low-level-vision quality-assessment vision-language-dataset visual-large-language-models
Trend
0
Star & Fork Trend (19 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
Q-Future/Q-Bench has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | Q-Bench | rag-all-in-one | code_qa | pdfdeal |
|---|---|---|---|---|
| Stars | 283 | 283 | 283 | 285 |
| Forks | 13 | 47 | 42 | 19 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Jupyter Notebook | N/A | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | NOASSERTION | N/A | MIT | MIT |
Capability Radar vs rag-all-in-one
Q-Bench
rag-all-in-one
Maintenance Activity 0
Last code push 604 days ago.
Community Engagement 69
Fork-to-star ratio: 4.6%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 30
No clear license detected — proceed with caution.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.