Hi @luozhongze 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv (https://arxiv.org/abs/2606.04483) and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://arxiv.org/abs/2606.04483
The paper page lets people discuss about your paper and lets them find artifacts about it (your code and dataset 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 that the code and data are coming soon. It鈥檇 be great to host them on the Hugging Face Hub once they are released, to improve their visibility and make it easier for the community to access them. We can add tags so that people find them when filtering models and datasets, and link them to the paper page.
For the dataset, we support many formats (including WebDataset for large image/video datasets). You can also use the dataset viewer to let people preview examples directly in the browser.
For the code, you can also build a demo Space to showcase the method. ZeroGPU gives on-demand GPU-backed compute for demo Spaces.
Let me know if you're interested and need any guidance. We'd be happy to help with the upload process.
Kind regards,
Niels
Hi @luozhongze 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv (https://arxiv.org/abs/2606.04483) and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://arxiv.org/abs/2606.04483
The paper page lets people discuss about your paper and lets them find artifacts about it (your code and dataset 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 that the code and data are coming soon. It鈥檇 be great to host them on the Hugging Face Hub once they are released, to improve their visibility and make it easier for the community to access them. We can add tags so that people find them when filtering models and datasets, and link them to the paper page.
For the dataset, we support many formats (including WebDataset for large image/video datasets). You can also use the dataset viewer to let people preview examples directly in the browser.
For the code, you can also build a demo Space to showcase the method. ZeroGPU gives on-demand GPU-backed compute for demo Spaces.
Let me know if you're interested and need any guidance. We'd be happy to help with the upload process.
Kind regards,
Niels