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jasoncorkill 
posted an update 1 day ago
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The Sora Video Generation Aligned Words dataset contains a collection of word segments for text-to-video or other multimodal research. It is intended to help researchers and engineers explore fine-grained prompts, including those where certain words are not aligned with the video.

We hope this dataset will support your work in prompt understanding and advance progress in multimodal projects.

If you have specific questions, feel free to reach out.
Rapidata/sora-video-generation-aligned-words
jasoncorkill 
posted an update 6 days ago
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2818
Integrating human feedback is vital for evolving AI models. Boost quality, scalability, and cost-effectiveness with our crowdsourcing tool!

..Or run A/B tests and gather thousands of responses in minutes. Upload two images, ask a question, and watch the insights roll in!

Check it out here and let us know your feedback: https://app.rapidata.ai/compare
jasoncorkill 
posted an update 8 days ago
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2490
This dataset was collected in roughly 4 hours using the Rapidata Python API, showcasing how quickly large-scale annotations can be performed with the right tooling!

All that at less than the cost of a single hour of a typical ML engineer in Zurich!

The new dataset of ~22,000 human annotations evaluating AI-generated videos based on different dimensions, such as Prompt-Video Alignment, Word for Word Prompt Alignment, Style, Speed of Time flow and Quality of Physics.

Rapidata/text-2-video-Rich-Human-Feedback
jasoncorkill 
posted an update 13 days ago
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4524
Runway Gen-3 Alpha: The Style and Coherence Champion

Runway's latest video generation model, Gen-3 Alpha, is something special. It ranks #3 overall on our text-to-video human preference benchmark, but in terms of style and coherence, it outperforms even OpenAI Sora.

However, it struggles with alignment, making it less predictable for controlled outputs.

We've released a new dataset with human evaluations of Runway Gen-3 Alpha: Rapidata's text-2-video human preferences dataset. If you're working on video generation and want to see how your model compares to the biggest players, we can benchmark it for you.

🚀 DM us if you’re interested!

Dataset: Rapidata/text-2-video-human-preferences-runway-alpha
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jasoncorkill 
posted an update 26 days ago
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2675
We benchmarked @xai-org 's Aurora model, as far as we know the first public evaluation of the model at scale.

We collected 401k human annotations in over the past ~2 days for this, we have uploaded all of the annotation data here on huggingface with a fully permissive license
Rapidata/xAI_Aurora_t2i_human_preferences
jasoncorkill 
posted an update about 2 months ago
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1143
We uploaded huge human annotated preference dataset for image generation. Instead of just having people choose which model they preferer, we annotated an alignment score on a word by word basis for the prompt. rate the images on coherence, overall alignment and style preference. Those images that score badly were also given to annotators to highlight problem areas. Check it out! Rapidata/text-2-image-Rich-Human-Feedback

We also wrote a blog post for those who want a bit more detail:
https://huggingface.co/blog/RapidataAI/beyond-image-preferences
jasoncorkill 
posted an update about 2 months ago
mjaggi 
authored 5 papers over 1 year ago