Roboflow100-VL (RF100-VL) is a multi-domain object-detection benchmark designed to evaluate vision-language models (VLMs) on diverse, out-of-distribution concepts and imaging modalities. The benchmark aggregates 100 heterogeneous object-detection datasets (drawn from Roboflow/Roboflow Universe collections) spanning domains such as medical imagery (X-ray), thermal, aerial, industrial inspection, synthetic/game imagery, and more. The paper reports aggregate metrics (e.g., AP, latency, FLOPs) averaged across all 100 tasks and evaluates models in zero-shot, few-shot, semi-supervised, and fully supervised settings; the project provides code, dataset interfaces (PyPI package rf100vl), and a public website. Primary sources: paper (arXiv:2505.20612), project site (https://rf100-vl.org), code repository (https://github.com/roboflow/rf100-vl), and a Hugging Face mirror/hosted collection (https://hf.co/datasets/gatilin/rf100-vl).
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