Lino Giger

LinoGiger

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liked a dataset about 3 hours ago
Rapidata/1k-ranked-videos-coherence
liked a dataset about 10 hours ago
Rapidata/text-2-video-human-preferences-veo3
liked a dataset about 10 hours ago
Rapidata/Imagen4_t2i_human_preference
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LinoGiger's activity

reacted to jasoncorkill's post with πŸ”₯ about 2 months ago
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3282
πŸš€ We tried something new!

We just published a dataset using a new (for us) preference modality: direct ranking based on aesthetic preference. We ranked a couple of thousand images from most to least preferred, all sampled from the Open Image Preferences v1 dataset by the amazing @data-is-better-together team.

πŸ“Š Check it out here:
Rapidata/2k-ranked-images-open-image-preferences-v1

We're really curious to hear your thoughts!
Is this kind of ranking interesting or useful to you? Let us know! πŸ’¬

If it is, please consider leaving a ❀️ and if we hit 30 ❀️s, we’ll go ahead and rank the full 17k image dataset!
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reacted to jasoncorkill's post with πŸ”₯πŸš€ about 2 months ago
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2383
πŸš€ 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 [email protected] to see how we can help.

Lumina-Image 2.0: A Unified and Efficient Image Generative Framework (2503.21758)
reacted to jasoncorkill's post with πŸ”₯ 2 months ago
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πŸ”₯ It's out! We published the dataset for our evaluation of @OpenAI 's new 4o image generation model.

Rapidata/OpenAI-4o_t2i_human_preference

Yesterday we published the first large evaluation of the new model, showing that it absolutely leaves the competition in the dust. We have now made the results and data available here! Please check it out and ❀️ !