Hi @ningyu 🤗
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/2510.17795.
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 abstract and GitHub README that the code for Executable Knowledge Graphs (xKG) will be released soon. That's fantastic news!
It'd be great to make the xKG code and any associated artifacts (such as the populated knowledge graphs themselves, which could be hosted as a dataset) available on the 🤗 hub, to improve their discoverability/visibility.
We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.
Uploading code (for the xKG framework)
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
Even if xKG is a framework, a model repository can be used to host the code, allowing for easy git clone and integration with other Hugging Face tools. If any components of xKG involve pre-trained models, the PyTorchModelHubMixin class can be leveraged.
Uploading dataset (for generated knowledge graphs)
If the Executable Knowledge Graphs themselves (or parts of them) can be provided in a structured, downloadable format, it would be awesome to make them available on 🤗 as a dataset, 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 once your code and artifacts are ready for release!
Cheers,
Niels
ML Engineer @ HF 🤗
Hi @ningyu 🤗
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/2510.17795.
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 abstract and GitHub README that the code for Executable Knowledge Graphs (xKG) will be released soon. That's fantastic news!
It'd be great to make the xKG code and any associated artifacts (such as the populated knowledge graphs themselves, which could be hosted as a dataset) available on the 🤗 hub, to improve their discoverability/visibility.
We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.
Uploading code (for the xKG framework)
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
Even if xKG is a framework, a model repository can be used to host the code, allowing for easy
git cloneand integration with other Hugging Face tools. If any components of xKG involve pre-trained models, the PyTorchModelHubMixin class can be leveraged.Uploading dataset (for generated knowledge graphs)
If the Executable Knowledge Graphs themselves (or parts of them) can be provided in a structured, downloadable format, it would be awesome to make them available on 🤗 as a dataset, so that people can do:
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 once your code and artifacts are ready for release!
Cheers,
Niels
ML Engineer @ HF 🤗