[CVPR2026]🚀🚀🚀Official code for the paper "YOLO-Master: MOE-Accelerated with Specialized Transformers for Enhanced Real-time Detection." *(YOLO = You Only Look Once)* 🔥🔥🔥
C-Rank Grade: A (Welcoming) - 62/100
External PR Merge Rate: 73%
Response Time: 22h
First Timer Success: 55%
Tencent/YOLO-Master has a recorded first-timer success rate of 55.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in Tencent/YOLO-Master respond to incoming external pull requests in approximately 22.2 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 61.9 places Tencent/YOLO-Master in the A tier.
The external contributor pull request merge rate for Tencent/YOLO-Master is 72.9%, based on public PR activity from non-core contributors.
Tencent/YOLO-Master currently has 5 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Highly welcoming maintainers in Tencent/YOLO-Master. Prompt code reviews with positive guidance for new contributors.
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Hi YOLO-Master authors, Thank you for sharing this amazing work! I’ve been experimenting with the pre-trained weights for my project on small object segmentation and deeply appreciate the idea of Instance-conditional adaptive computation. However, while analyzing the expert utilization of the pre-trained weights (YOLO-Master-v0.1-N.pt) using the official script, I noticed some unusual statistics that look like a potential Routing Collapse. I am a bit confused and would like to seek your clarification. I used the official script provided at ultralytics/nn/modules/moe/analysis.py to diagnose the YOLO-Master-v0.1-N.pt model on the MS COCO 2017 val dataset (5000 images). The diagnosis report shows: Total Tokens Processed: 15,003. Since there are 3 router layers and 5001 forward passes (5000 val images + 1 warmup), this perfectly aligns with the instance-level routing design (1 token per image). Static Expert Activation: For all 5001 images, the routers exclusively selected the exact sam
非常感谢作者们的杰出工作，但阅读论文后有些疑问，希望作者能给出解答。 1.有没有尝试更多专家情况？论文中表明理论上K<<E会更好，但是实际实验最佳配置中只是E=4，K=2。 2.另外表8中的config 5，MoE权重还是1.5吗，从表格上来看感觉0.5或1.0可能会更好？是否是填写错误呢？
请问能提供同时包含了颈部的yaml配置文件吗？
This is a great project. I look forward to the weight file. When I have time, I will help you with some deployment support.
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When evaluating whether to contribute to Tencent/YOLO-Master, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of Tencent/YOLO-Master acknowledge new external contributions in approximately 22 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 72.9% were successfully merged into the primary branch.
Tencent/YOLO-Master has a recorded first-timer success rate of 55.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~22 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 61.9 places Tencent/YOLO-Master in the Welcoming tier.
The external pull request merge rate is 72.9%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, Tencent/YOLO-Master currently has 5 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for Tencent/YOLO-Master are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.