VL
TIGER-AI-Lab/VLM2Vec
This repo contains the code for "VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks" [ICLR 2025]
622 59 +0/wk
GitHub
benchmark contrastive-learning embedding image-retrieval mmeb multimodal rag representation-learning video-retrieval visual-document-retrieval vlm
Trend
3
Star & Fork Trend (46 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
TIGER-AI-Lab/VLM2Vec has +0 stars this period . 7-day velocity: 0.5%.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | VLM2Vec | SmoothNLP | VisualThinker-R1-Zero | llama-cpp-agent |
|---|---|---|---|---|
| Stars | 622 | 622 | 622 | 623 |
| Forks | 59 | 111 | 23 | 69 |
| Weekly Growth | +0 | +0 | +0 | -3 |
| Language | Python | Java | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | GPL-3.0 | N/A | NOASSERTION |
Capability Radar vs SmoothNLP
VLM2Vec
SmoothNLP
Maintenance Activity 100
Last code push 1 days ago.
Community Engagement 47
Fork-to-star ratio: 9.5%. 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 95
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.