Rapidata/camera-movement
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Jason Corkill
jasoncorkill
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Human data annotation
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Researchers shouldn’t have to limit experiments because human feedback is too expensive/slow to collect.
So, @RapidataAI is offering up to $50,000 in human annotation credits per research project (can be more for selected topics).
Learn more on our website, and apply via email, we'll do our best to get back to you within 2 days :).
So, @RapidataAI is offering up to $50,000 in human annotation credits per research project (can be more for selected topics).
Learn more on our website, and apply via email, we'll do our best to get back to you within 2 days :).
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Thanks for your AI break down. We share the raw results on purpose as we also share the raw question, the table would be inconsistent if we reversed it there. For the ELO updates this was reversed.
If you go to benchmark.ai/svg you can see the per axis aggregation.
posted an update about 1 month ago
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Most public benchmarks collapse model performance into one broad preference signal.
That makes it hard to understand which capabilities differentiate between models. It's also almost impossible to inspect the evidence behind it. So @RapidataAI is releasing Benchmark.AI.
We started with an SVG generation benchmark including 42 models, 500 prompts, 1.9M+ human judgements, 300K+ match-ups.
We evaluate models separately on Preference, Alignment and Coherence, while making the prompts, outputs, match-ups and methodology public.
Full dataset: Rapidata/svg-benchmark
Full benchmark: https://www.benchmark.ai/svg
Methodology feedback and benchmark suggestions very welcome!
That makes it hard to understand which capabilities differentiate between models. It's also almost impossible to inspect the evidence behind it. So @RapidataAI is releasing Benchmark.AI.
We started with an SVG generation benchmark including 42 models, 500 prompts, 1.9M+ human judgements, 300K+ match-ups.
We evaluate models separately on Preference, Alignment and Coherence, while making the prompts, outputs, match-ups and methodology public.
Full dataset: Rapidata/svg-benchmark
Full benchmark: https://www.benchmark.ai/svg
Methodology feedback and benchmark suggestions very welcome!
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Are you an AI Researcher, Enthusiast, Founder or else and live in or close by to Zürich? Drop in for an Aperol Spritz and Euromaxx on our Balcony on the 14th of August.
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What is the License of data?
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#3 opened 8 months ago
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qinrongcui
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Do you remember https://thispersondoesnotexist.com/ ? It was one of the first cases where the future of generative media really hit us. Humans are incredibly good at recognizing and analyzing faces, so they are a very good litmus test for any generative image model.
But none of the current benchmarks measure the ability of models to generate humans independently. So we built our own. We measure the models ability to generate a diverse set of human faces and using over 20'000 human annotations we ranked all of the major models on their ability to generate faces. Find the full ranking here:
https://app.rapidata.ai/mri/benchmarks/68af24ae74482280b62f7596
We have release the full underlying data publicly here on huggingface: Rapidata/Face_Generation_Benchmark
But none of the current benchmarks measure the ability of models to generate humans independently. So we built our own. We measure the models ability to generate a diverse set of human faces and using over 20'000 human annotations we ranked all of the major models on their ability to generate faces. Find the full ranking here:
https://app.rapidata.ai/mri/benchmarks/68af24ae74482280b62f7596
We have release the full underlying data publicly here on huggingface: Rapidata/Face_Generation_Benchmark
updated a
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