Hi @flow0314 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv 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://huggingface.co/papers/submit.
The paper page lets people discuss about your paper and lets them find artifacts about it. I saw that you have already hosted the MLLM-4D model checkpoints on the Hub at flow666/MLLM-4D, which is great for visibility!
I noticed in your GitHub README that the datasets (MLLM4D-2M, MLLM4D-R1-30k, Cold-Start Data, and MLLM4D-Bench) are listed as "coming soon". Would you like to host these datasets on https://huggingface.co/datasets as well once they are ready?
Hosting on Hugging Face will provide your work with better discoverability and allow the community to easily load the data via the datasets library:
from datasets import load_dataset
dataset = load_dataset("GVCLab/MLLM4D-2M")Besides the ease of use, we have a dataset viewer that allows people to quickly explore rows of the data directly in the browser. After they are uploaded, we can also link them to your paper page and your models so researchers can discover all your work in one place.
Let me know if you're interested or if you need any guidance on the process!
Kind regards,
Niels
Hi @flow0314 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv 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://huggingface.co/papers/submit.
The paper page lets people discuss about your paper and lets them find artifacts about it. I saw that you have already hosted the MLLM-4D model checkpoints on the Hub at flow666/MLLM-4D, which is great for visibility!
I noticed in your GitHub README that the datasets (MLLM4D-2M, MLLM4D-R1-30k, Cold-Start Data, and MLLM4D-Bench) are listed as "coming soon". Would you like to host these datasets on https://huggingface.co/datasets as well once they are ready?
Hosting on Hugging Face will provide your work with better discoverability and allow the community to easily load the data via the
datasetslibrary:Besides the ease of use, we have a dataset viewer that allows people to quickly explore rows of the data directly in the browser. After they are uploaded, we can also link them to your paper page and your models so researchers can discover all your work in one place.
Let me know if you're interested or if you need any guidance on the process!
Kind regards,
Niels