Jason Corkill
jasoncorkill
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].
Organizations
jasoncorkill's activity
Cool dataset !
1
1
#2 opened 3 months ago
by
lhoestq
Create heritag
2
#2 opened 3 months ago
by
jerry625
Delete Videos
1
#2 opened 3 months ago
by
joshuaXX
170'000 additional annotations
2
#3 opened 4 months ago
by
jasoncorkill
Update README.md
#1 opened 4 months ago
by
jasoncorkill