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Datasets:
CaiYuanhao
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PhyGDPO

Tasks:
Text-to-Video
Languages:
English
Size:
100K<n<1M
ArXiv:
License:
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Invalid string class label Wan1.3B
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2386, in __iter__
                  example = _apply_feature_types_on_example(
                      example, self.features, token_per_repo_id=self.token_per_repo_id
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2303, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2178, in encode_example
                  return encode_nested_example(self, example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1483, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ~~~~~~~~~~~~~~~~~~~~~^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1158, in encode_example
                  example_data = self.str2int(example_data)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1095, in str2int
                  output = [self._strval2int(value) for value in values]
                            ~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1116, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label Wan1.3B

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[ECCV 2026] PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation

Dataset Description

This dataset supports the DPO training algorithm, PhyGDPO, described in our ECCV paper. It is re-implemented based on a public dataset, VidGen-1M. This dataset contains 135k text-video pairs that are rich in physics interactions and phenomena in total. Please also download VidGen-1M if you are going to use the whole dataset PhyVidGen-135K with the explicit physics extended prompts written by Gemini-2.5-pro in the json_file.zip. Besides, we also construct 17k video groups that support our reinforcement learning algorithm, PhyGDPO, based on our data construction pipeline, PhyAugPipe, as

Our Data Construction Pipeline - PhyAugPipe

Each group contains three losing video cases generated by Wan-2.1-1.3B or Wan-2.1-14B. Here is a data example:

Github Code Link

This dataset is intended to be used together with our code. Please refer to the GitHub repository below for more detailed instructions.

https://github.com/caiyuanhao1998/Open-PhyGDPO

Huggingface Model Link

We also release three models based on Wan2.1-1.3B and Wan2.1-14B in the following link:

https://huggingface.co/CaiYuanhao/PhyGDPO

Project Page Link

For more video customization results, please refer to our project page:

https://caiyuanhao1998.github.io/project/PhyGDPO/

Arxiv Paper Link

For more technical details, please refer to our ECCV 2026 paper:

https://arxiv.org/abs/2512.24551

Citation

If you find our code, data, and models useful, please consider citing our paper:

@inproceedings{phygdpo,
  title={PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation},
  author={Cai, Yuanhao and Li, Kunpeng and Jia, Menglin and Wang, Jialiang and Sun, Junzhe and Liang, Feng and Chen, Weifeng and Juefei-Xu, Felix and Wang, Chu and Thabet, Ali and Dai, Xiaoliang and Ju, Xuan and Yuille, Alan and Hou, Ji},
  booktitle={ECCV},
  year={2026}
}
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