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docs(README.md): update paper link #1

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Jun 22, 2024
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docs(README.md): update paper link #1

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13 changes: 8 additions & 5 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@

<!-- [[`📕 Paper`](https://arxiv.org/abs/2307.04657)] -->
[[`🏠 Project Homepage`](https://sites.google.com/view/safe-sora)]
[[`📕 Paper`](https://arxiv.org/abs/2406.14477)]
[[`🤗 SafeSora Datasets`](https://huggingface.co/datasets/PKU-Alignment/SafeSora)]
[[`🤗 SafeSora Label`](https://huggingface.co/datasets/PKU-Alignment/SafeSora-Label)]
[[`🤗 SafeSora Evaluation`](https://huggingface.co/datasets/PKU-Alignment/SafeSora-Eval)]
Expand Down Expand Up @@ -140,11 +141,13 @@ eval_data = PromptDataset.load("path/to/config", video_dir="path/to/video_dir")
If you find the SafeSora dataset family useful in your research, please cite the following paper:

```bibtex
@article{SafeSora2024,
title = {SafeSora: Towards Safety Alignment of Text2Video Generation via a Human Preference Dataset},
author = {Josef Dai and Tianle Chen and Xuyao Wang and Ziran Yang and Taiye Chen and Jiaming Ji and Yaodong Yang},
url = {https://github.com/calico-1226/safe-sora},
year = {2024}
@misc{dai2024safesora,
title={SafeSora: Towards Safety Alignment of Text2Video Generation via a Human Preference Dataset},
author={Josef Dai and Tianle Chen and Xuyao Wang and Ziran Yang and Taiye Chen and Jiaming Ji and Yaodong Yang},
year={2024},
eprint={2406.14477},
archivePrefix={arXiv},
primaryClass={id='cs.CV' full_name='Computer Vision and Pattern Recognition' is_active=True alt_name=None in_archive='cs' is_general=False description='Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.'}
}
```

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1 change: 1 addition & 0 deletions pyproject.toml
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Expand Up @@ -38,6 +38,7 @@ dependencies = [
"transformers",
"datasets",
"tokenizers",
"av",
]
dynamic = ["version"]

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9 changes: 1 addition & 8 deletions safe_sora/datasets/base.py
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Expand Up @@ -40,9 +40,7 @@

def is_complete(data_dict: dict) -> bool:
"""Check if a dictionary is complete, i.e., all values are not None."""
for key, value in data_dict.items():
if key == 'info':
continue
for _, value in data_dict.items():
if isinstance(value, dict) and not is_complete(value):
return False
if value is None:
Expand Down Expand Up @@ -153,7 +151,6 @@ class VideoSample(TypedDict):
is_safe: NotRequired[bool]
video_labels: NotRequired[HarmLabel]
generated_from: NotRequired[str]
info: NotRequired[dict]


def format_video_sample_from_dict(data: dict, contain_labels: bool = False) -> VideoSample:
Expand Down Expand Up @@ -183,7 +180,6 @@ def format_video_sample_from_dict(data: dict, contain_labels: bool = False) -> V
is_safe=data.get('is_safe'),
video_labels=video_labels,
generated_from=data.get('generated_from'),
info=data.get('info', {}),
)

return VideoSample(
Expand All @@ -195,7 +191,6 @@ def format_video_sample_from_dict(data: dict, contain_labels: bool = False) -> V
video_path=data.get('video_path'),
is_safe=data.get('is_safe'),
generated_from=data.get('generated_from'),
info=data.get('info', {}),
)


Expand Down Expand Up @@ -236,7 +231,6 @@ class VideoPairSample(TypedDict):
helpfulness: NotRequired[Literal['video_0', 'video_1']]
harmlessness: NotRequired[Literal['video_0', 'video_1']]
sub_preferences: NotRequired[SubPreference]
info: NotRequired[dict[str, str]]


def format_video_pair_sample_from_dict(data: dict) -> VideoPairSample:
Expand Down Expand Up @@ -270,7 +264,6 @@ def format_video_pair_sample_from_dict(data: dict) -> VideoPairSample:
helpfulness=data.get('helpfulness'),
harmlessness=data.get('harmlessness'),
sub_preferences=sub_preferences,
info=data.get('info', {}),
)


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