metadata
dataset_info:
- config_name: articulatedChain
features:
- name: query_id
dtype: string
- name: case_id
dtype: string
- name: raw_text
dtype: string
- name: parsed_text
dtype: string
- name: video
dtype: video
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- config_name: blockTower3D
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- config_name: cantileverBeamTransient
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- config_name: dropWeightImpactSMC
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- config_name: flexibleCrankSlider
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- config_name: gearPair3D
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- config_name: harmonicResponseFRF
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- config_name: j2PlasticBeam
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- config_name: lemaitreDamageBar
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- config_name: massSpringDamper
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- config_name: pendulum
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- config_name: reissnerShellModal
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- config_name: rigidCollision
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- config_name: rollingSlidingTransition
features:
- name: query_id
dtype: string
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dtype: string
- name: raw_text
dtype: string
- name: parsed_text
dtype: string
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dtype: video
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num_examples: 100
download_size: 25533691
dataset_size: 25533691
- config_name: rubberBlockCompression
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- name: query_id
dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: video
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- config_name: sphereDrop3D
features:
- name: query_id
dtype: string
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dtype: string
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dtype: string
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- config_name: stackStability
features:
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dtype: string
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dtype: string
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dtype: string
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dtype: video
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- config_name: stressWavePropagation
features:
- name: query_id
dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: video
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- config_name: unbalancedRotor3D
features:
- name: query_id
dtype: string
- name: case_id
dtype: string
- name: raw_text
dtype: string
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dtype: string
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- name: test
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dataset_size: 325992878
World Embedding Dynamics Retrieval
World Embedding Dynamics Retrieval is the dynamics retrieval split of the World Embedding Benchmark. It contains 1,900 simulation videos from 19 physics families. The family shards are loaded together as the default configuration.
Usage
from datasets import load_dataset
dataset = load_dataset(
"World-Representation-Lab/World-Embedding-Dynamics-Retrieval",
split="test",
)
Fields
query_id: unique text-query identifier.case_id: simulation case identifier.raw_text: structured physical description.parsed_text: natural-language retrieval caption.video: simulation video.
The benchmark uses parsed_text for text-video retrieval.
Citation
@misc{liu2026worldembeddingbenchmark,
title = {World Embedding Benchmark},
author = {Yiqi Liu and Ruifeng Yuan and Yang Wang and Long Li and Fengyu Cai and Hou Pong Chan and Jialin Yu and Hao Zhang and Chenghua Lin and Chenghao Xiao},
year = {2026},
eprint = {2610.03632},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2610.03632}
}