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"occupation": "Unknown",
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}
},
"votedFor": "sora2-pro_9-10-25_2_0.mp4"
},
{
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"age": "Unknown",
... | 0.213048 | 0.786952 | [
{
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"age": "Unknown",
"country": "US",
"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
"userScores": {
"global": 0.4082
}
},
"votedFor": "sora_0002_1.mp4"
},
{
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"age": "18-29",
"country":... | 0.721482 | 0.278518 | [
{
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"age": "0-17",
"country": "PL",
"gender": "Unknown",
"language": "pl",
"occupation": "Business & Finance",
"userScores": {
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},
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},
{
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"age": "0-17",... | sora2-pro_9-10-25_2_0.mp4 | sora_0002_1.mp4 | sora2-pro | sora | ||
A 'day in the life' of a cutting-edge urban dance crew rehearsing for a global competition. Showcase their intense training, creative choreography sessions, high-tech stage setups, team dynamics, and the adrenaline-filled moments of their electrifying performance under the city lights. | 0.616409 | 0.383591 | [
{
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"age": "0-17",
"country": "ES",
"gender": "Other",
"language": "es",
"occupation": "Unknown",
"userScores": {
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}
},
"votedFor": "sora2-pro_9-10-25_2_0.mp4"
},
{
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"co... | 0.466542 | 0.533458 | [
{
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"age": "Unknown",
"country": "PH",
"gender": "Unknown",
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}
},
"votedFor": "veo2_0002_0.mp4"
},
{
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"age": "Unknown",
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"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
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}
},
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},
{
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... | sora2-pro_9-10-25_2_0.mp4 | veo2_0002_0.mp4 | sora2-pro | veo2 | ||
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{
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"gender": "Female",
"language": "es",
"occupation": "Skilled Manual Trades",
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}
},
"votedFor": "veo3_0002_0.mp4"
},
{
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... | 0.533001 | 0.466999 | [
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"age": "Unknown",
"country": "ZM",
"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
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}
},
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},
{
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"age": "Unknown",
... | 0.414851 | 0.585149 | [
{
"userDetails": {
"age": "65+",
"country": "BW",
"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
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}
},
"votedFor": "sora2-pro_9-10-25_2_0.mp4"
},
{
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"age": "Unknown",
"c... | sora2-pro_9-10-25_2_0.mp4 | veo3_0002_0.mp4 | sora2-pro | veo3 | ||
A 'day in the life' of a cutting-edge urban dance crew rehearsing for a global competition. Showcase their intense training, creative choreography sessions, high-tech stage setups, team dynamics, and the adrenaline-filled moments of their electrifying performance under the city lights. | 0.485735 | 0.514265 | [
{
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"age": "Unknown",
"country": "MA",
"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
"userScores": {
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}
},
"votedFor": "sora2-pro_9-10-25_2_0.mp4"
},
{
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... | 0.296489 | 0.703511 | [
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"gender": "Unknown",
"language": "en",
"occupation": "Skilled Manual Trades",
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}
},
"votedFor": "wan2.1_0002_0.mp4"
},
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... | 0.543239 | 0.456761 | [
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"userDetails": {
"age": "Unknown",
"country": "ZW",
"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
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}
},
"votedFor": "wan2.1_0002_0.mp4"
},
{
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"country"... | sora2-pro_9-10-25_2_0.mp4 | wan2.1_0002_0.mp4 | sora2-pro | wan2.1 | ||
A 2D animated fire dancer twirls blazing ribbons under neon lights in a dynamic, colorful style, the sharp motions and vivid hues mesmerizing onlookers who cheer enthusiastically. | 0.691568 | 0.308432 | [
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"gender": "Male",
"language": "ar",
"occupation": "Unemployed",
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}
},
"votedFor": "sora2-pro_9-10-25_6_0.mp4"
},
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... | 0.284688 | 0.715312 | [
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"age": "Unknown",
"country": "NG",
"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
"userScores": {
"global": 0.4469
}
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},
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"c... | 0.660109 | 0.339891 | [
{
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"age": "Unknown",
"country": "PH",
"gender": "Unknown",
"language": "en",
"occupation": "Unknown",
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},
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},
{
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... | sora2-pro_9-10-25_6_0.mp4 | alpha_0006_3945567110.mp4 | sora2-pro | alpha |
Rapidata Video Generation Sora 2 Pro Human Preference
In this dataset, ~75k human responses from ~15k human annotators were collected to evaluate the Sora 2 Pro video generation model on our benchmark. This dataset was collected in roughtly 30 min using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking it ❤️
Overview
In this dataset, ~75k human responses from ~15k human annotators were collected to evaluate the Sora 2 Pro video generation model on our benchmark. This dataset was collected in roughtly 30 min using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation. The benchmark data is accessible on huggingface directly.
Explanation of the colums
The dataset contains paired video comparisons. Each entry includes 'video1' and 'video2' fields, which contain links to downscaled GIFs for easy viewing. The full-resolution videos can be found here
The weighted_results column contains scores ranging from 0 to 1, representing aggregated user responses. Individual user responses can be found in the detailedResults column.
Alignment
The alignment score quantifies how well an video matches its prompt. Users were asked: "Which video fits the description better?".
Examples
A bustling city marketplace from dawn to dusk, capturing vendors setting up, colorful goods being sold, diverse crowds interacting, lights illuminating as night falls, and the vibrant energy transitioning between day and night.
Sora2 Pro
Ray 2
A serene mermaid glides through vibrant coral reefs, sunlight filtering through the water. Fish of every color swim around her gracefully as she dances with the ocean currents.
Sora2 Pro
Veo 2
Coherence
The coherence score measures whether the generated video is logically consistent and free from artifacts or visual glitches. Without seeing the original prompt, users were asked: "Which video has more glitches and is more likely to be AI generated?"
Examples
Sora2 Pro
Alpha
Sora2 Pro
Marey
Preference
The preference score reflects how visually appealing participants found each video, independent of the prompt. Users were asked: "Which video do you prefer aesthetically?"
Examples
Sora2 Pro
Pika 2.2
Sora2 Pro
Veo 3
About Rapidata
Rapidata's technology makes collecting human feedback at scale faster and more accessible than ever before. Visit rapidata.ai to learn more about how we're revolutionizing human feedback collection for AI development.
Other Datasets
We run a benchmark of the major video generation models, the results can be found on our website. We rank the models according to their coherence/plausiblity, their aligment with the given prompt and style prefernce. The underlying 2M+ annotations can be found here:
- Link to the Rich Video Annotation dataset
- Link to the Coherence dataset
- Link to the Text-2-Image Alignment dataset
- Link to the Preference dataset
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