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Mads Kuhlmann-Joergensen
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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. https://huggingface.co/datasets/Rapidata/text-2-video-Rich-Human-Feedback
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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. π DM us if youβre interested! Dataset: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences-runway-alpha
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Beyond Image Preferences - Rich Human Feedback for Text-to-Image Generation
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Crowd-sourced Open Preference Dataset for Text-to-Image Generation
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