Datasets:
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README.md
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---
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license: cc-by-4.0
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pretty_name: CausalCascade
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tags:
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- video
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- image-to-video
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# CausalCascade
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](https://huggingface.co/datasets/deepdeltalab/CausalCascade)
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[](https://github.com/SJTU-DeepDeltaLab/CausalCascade)
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The release contains **50 event-rich Blender scenes**, structured causal event graphs, **872 graph-grounded diagnostic questions**, three levels of future-event specification, and **2,832 controlled counterfactual variants**. A subset of **225 matched factual-counterfactual pairs** supports evaluation of selective responsiveness to physical interventions.
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<!-- Uncomment after replacing ARXIV_ID with the published preprint identifier.
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[Paper on arXiv](https://arxiv.org/abs/ARXIV_ID)
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## Evaluation
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The benchmark supports factual causal-cascade evaluation under three levels of future-event specification and paired counterfactual evaluation under *delete*, *move*, scale, and mass interventions. Motion-based metrics and graph-grounded diagnostic VQA provide complementary measures of physical evolution and causal-process fidelity.
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Some `.blend` source scenes and rendered media incorporate textures, HDRIs, and 3D models from [Poly Haven](https://polyhaven.com), released under [CC0 1.0](https://polyhaven.com/license). See [ATTRIBUTION.md](ATTRIBUTION.md).
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## Citation
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```bibtex
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@misc{
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title = {A Plausible Future Is Not a Causal Future: Can Video Models Generate How the World Unfolds?},
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author = {
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year = {2026},
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eprint = {
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archivePrefix = {arXiv},
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primaryClass = {
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url = {https://arxiv.org/abs/
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}
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```
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---
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license: cc-by-4.0
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pretty_name: CausalCascade
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task_categories:
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- image-to-video
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tags:
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- video
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- image-to-video
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# CausalCascade
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[](https://arxiv.org/abs/2610.15562)
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[](https://huggingface.co/papers/2610.15562)
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[](https://huggingface.co/datasets/deepdeltalab/CausalCascade)
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[](https://github.com/SJTU-DeepDeltaLab/CausalCascade)
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The release contains **50 event-rich Blender scenes**, structured causal event graphs, **872 graph-grounded diagnostic questions**, three levels of future-event specification, and **2,832 controlled counterfactual variants**. A subset of **225 matched factual-counterfactual pairs** supports evaluation of selective responsiveness to physical interventions.
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## Evaluation
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The benchmark supports factual causal-cascade evaluation under three levels of future-event specification and paired counterfactual evaluation under *delete*, *move*, scale, and mass interventions. Motion-based metrics and graph-grounded diagnostic VQA provide complementary measures of physical evolution and causal-process fidelity.
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Some `.blend` source scenes and rendered media incorporate textures, HDRIs, and 3D models from [Poly Haven](https://polyhaven.com), released under [CC0 1.0](https://polyhaven.com/license). See [ATTRIBUTION.md](ATTRIBUTION.md).
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## Citation
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If you use the CausalCascade dataset in your research, please cite:
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```bibtex
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@misc{causalcascade,
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title = {A Plausible Future Is Not a Causal Future: Can Video Models Generate How the World Unfolds?},
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author = {Jialiang Li and Zhengning Xu and Zongyang Ma and Shaobo Cui},
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year = {2026},
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eprint = {2610.15562},
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archivePrefix = {arXiv},
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primaryClass = {cs.CV},
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url = {https://arxiv.org/abs/2610.15562}
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}
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```
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