Release TiViBench benchmark and VideoTPO code on Hugging Face

[NielsRogge]

Hi @HaroldChen19 🤗

Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2511.13704.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.

I saw in your GitHub repository's TODO list that you're planning to release the TiViBench dataset and VideoTPO inference code. It would be fantastic to host these artifacts on the 🤗 hub once they are ready, to improve their discoverability and visibility!
We can add tags so that people find them when filtering https://huggingface.co/datasets (for TiViBench) and https://huggingface.co/models (for VideoTPO inference code/strategy).

Uploading VideoTPO code/strategy

Once your inference code for VideoTPO is released, you can share it directly as a model repository on the Hub. See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, we could leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to any custom nn.Module if VideoTPO involves a custom model, or simply host the code.
We encourage researchers to push their code to a model repository, so that things like download stats also work. We can then also link the repository to the paper page.

Uploading TiViBench dataset

Would be awesome to make the TiViBench dataset available on 🤗 , so that people can do:

from datasets import load_dataset

dataset = load_dataset("your-hf-org-or-username/your-dataset")

See here for a guide: https://huggingface.co/docs/datasets/loading.

Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.

Let me know if you're interested/need any help regarding this, either now or when you are closer to releasing them!

Cheers,

Niels
ML Engineer @ HF 🤗