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Mads Kuhlmann-Joergensen
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🚀 Rapidata: Setting the Standard for Model Evaluation
Rapidata is proud to announce our first independent appearance in academic research, featured in the Lumina-Image 2.0 paper. This marks the beginning of our journey to become the standard for testing text-to-image and generative models. Our expertise in large-scale human annotations allows researchers to refine their models with accurate, real-world feedback.
As we continue to establish ourselves as a key player in model evaluation, we’re here to support researchers with high-quality annotations at scale. Reach out to info@rapidata.ai to see how we can help.
https://huggingface.co/papers/2503.21758
reacted
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jasoncorkill's
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🚀 Rapidata: Setting the Standard for Model Evaluation
Rapidata is proud to announce our first independent appearance in academic research, featured in the Lumina-Image 2.0 paper. This marks the beginning of our journey to become the standard for testing text-to-image and generative models. Our expertise in large-scale human annotations allows researchers to refine their models with accurate, real-world feedback.
As we continue to establish ourselves as a key player in model evaluation, we’re here to support researchers with high-quality annotations at scale. Reach out to info@rapidata.ai to see how we can help.
https://huggingface.co/papers/2503.21758
reacted
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jasoncorkill's
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2 days ago
🚀 Rapidata: Setting the Standard for Model Evaluation
Rapidata is proud to announce our first independent appearance in academic research, featured in the Lumina-Image 2.0 paper. This marks the beginning of our journey to become the standard for testing text-to-image and generative models. Our expertise in large-scale human annotations allows researchers to refine their models with accurate, real-world feedback.
As we continue to establish ourselves as a key player in model evaluation, we’re here to support researchers with high-quality annotations at scale. Reach out to info@rapidata.ai to see how we can help.
https://huggingface.co/papers/2503.21758
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Crowd-sourced Open Preference Dataset for Text-to-Image Generation
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