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Jason Corkill

jasoncorkill
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https://rapidata.ai

AI & ML interests

Human data annotation

Recent Activity

reacted to their post with ❤️ about 12 hours ago
🚀 Building Better Evaluations: 32K Image Annotations Now Available Today, we're releasing an expanded version: 32K images annotated with 3.7M responses from over 300K individuals which was completed in under two weeks using the Rapidata Python API. https://huggingface.co./datasets/Rapidata/text-2-image-Rich-Human-Feedback-32k A few months ago, we published one of our most liked dataset with 13K images based on the @data-is-better-together's dataset, following Google's research on "Rich Human Feedback for Text-to-Image Generation" (https://arxiv.org/abs/2312.10240). It collected over 1.5M responses from 150K+ participants. https://huggingface.co./datasets/Rapidata/text-2-image-Rich-Human-Feedback In the examples below, users highlighted words from prompts that were not correctly depicted in the generated images. Higher word scores indicate more frequent issues. If an image captured the prompt accurately, users could select [No_mistakes]. We're continuing to work on large-scale human feedback and model evaluation. If you're working on related research and need large, high-quality annotations, feel free to get in touch: [email protected].
reacted to their post with 🔥 about 12 hours ago
🚀 Building Better Evaluations: 32K Image Annotations Now Available Today, we're releasing an expanded version: 32K images annotated with 3.7M responses from over 300K individuals which was completed in under two weeks using the Rapidata Python API. https://huggingface.co./datasets/Rapidata/text-2-image-Rich-Human-Feedback-32k A few months ago, we published one of our most liked dataset with 13K images based on the @data-is-better-together's dataset, following Google's research on "Rich Human Feedback for Text-to-Image Generation" (https://arxiv.org/abs/2312.10240). It collected over 1.5M responses from 150K+ participants. https://huggingface.co./datasets/Rapidata/text-2-image-Rich-Human-Feedback In the examples below, users highlighted words from prompts that were not correctly depicted in the generated images. Higher word scores indicate more frequent issues. If an image captured the prompt accurately, users could select [No_mistakes]. We're continuing to work on large-scale human feedback and model evaluation. If you're working on related research and need large, high-quality annotations, feel free to get in touch: [email protected].
reacted to their post with 🚀 about 12 hours ago
🚀 Building Better Evaluations: 32K Image Annotations Now Available Today, we're releasing an expanded version: 32K images annotated with 3.7M responses from over 300K individuals which was completed in under two weeks using the Rapidata Python API. https://huggingface.co./datasets/Rapidata/text-2-image-Rich-Human-Feedback-32k A few months ago, we published one of our most liked dataset with 13K images based on the @data-is-better-together's dataset, following Google's research on "Rich Human Feedback for Text-to-Image Generation" (https://arxiv.org/abs/2312.10240). It collected over 1.5M responses from 150K+ participants. https://huggingface.co./datasets/Rapidata/text-2-image-Rich-Human-Feedback In the examples below, users highlighted words from prompts that were not correctly depicted in the generated images. Higher word scores indicate more frequent issues. If an image captured the prompt accurately, users could select [No_mistakes]. We're continuing to work on large-scale human feedback and model evaluation. If you're working on related research and need large, high-quality annotations, feel free to get in touch: [email protected].
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jasoncorkill's activity

liked a dataset about 13 hours ago
liked a dataset 17 days ago
liked 2 datasets 20 days ago
liked 4 datasets about 1 month ago
liked 3 datasets about 2 months ago
liked 2 datasets 2 months ago
liked 7 datasets 3 months ago