AM
EnnengYang/Awesome-Model-Merging-Methods-Theories-Applications
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. ACM Computing Surveys, 2026.
708 41 +1/wk
GitHub
attack-defense continual-learning diffusion-models ensemble-learning federated-learning few-shot-learning foundation-models generalization generative-model knowledge-fusion large-language-models llms
Trend
3
Star & Fork Trend (19 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
EnnengYang/Awesome-Model-Merging-Methods-Theories-Applications has +1 stars this period . 7-day velocity: 0.1%.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | Awesome-Model-Merging-Methods-Theories-Applications | searchGPT | MindChat | llmflows |
|---|---|---|---|---|
| Stars | 708 | 708 | 707 | 707 |
| Forks | 41 | 69 | 58 | 35 |
| Weekly Growth | +1 | -1 | +0 | +0 |
| Language | N/A | Python | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | N/A | MIT | GPL-3.0 | MIT |
Capability Radar vs searchGPT
Awesome-Model-Merging-Methods-Theories-Applications
searchGPT
Maintenance Activity 100
Last code push 2 days ago.
Community Engagement 29
Fork-to-star ratio: 5.8%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 48
+1 stars this period — 0.14% growth rate.
License Clarity 30
No clear license detected — proceed with caution.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.