Hi @najmulhasan-code 🤗
I'm Niels and work as part of the community science team at Hugging Face. I discovered your work on Arxiv regarding the coordination failures of LLMs in simultaneous settings, and I saw your paper was recently featured on the Hugging Face paper pages: https://huggingface.co/papers/2602.13255.
The paper page lets people discuss your paper and find related artifacts about it. I noticed you've released DPBench as an open-source benchmark on GitHub. Would you like to host the benchmark data and prompt templates on https://huggingface.co/datasets?
Hosting on Hugging Face will give your work more visibility and enable better discoverability within the AI community. It would also allow researchers to easily explore and load your evaluation prompts using the datasets library:
from datasets import load_dataset
dataset = load_dataset("your-hf-org-or-username/dpbench")If you're interested, you can find a guide for uploading datasets here: https://huggingface.co/docs/datasets/loading. Additionally, the dataset viewer would allow people to quickly browse through the benchmark's prompts and conditions directly in the browser.
After uploading, we can also link the dataset to the paper page (read here) so people can discover your work more easily. You can also claim the paper as yours on Hugging Face, which will show it on your public profile.
Let me know if you're interested or need any guidance!
Kind regards,
Niels
Hi @najmulhasan-code 🤗
I'm Niels and work as part of the community science team at Hugging Face. I discovered your work on Arxiv regarding the coordination failures of LLMs in simultaneous settings, and I saw your paper was recently featured on the Hugging Face paper pages: https://huggingface.co/papers/2602.13255.
The paper page lets people discuss your paper and find related artifacts about it. I noticed you've released DPBench as an open-source benchmark on GitHub. Would you like to host the benchmark data and prompt templates on https://huggingface.co/datasets?
Hosting on Hugging Face will give your work more visibility and enable better discoverability within the AI community. It would also allow researchers to easily explore and load your evaluation prompts using the
datasetslibrary:If you're interested, you can find a guide for uploading datasets here: https://huggingface.co/docs/datasets/loading. Additionally, the dataset viewer would allow people to quickly browse through the benchmark's prompts and conditions directly in the browser.
After uploading, we can also link the dataset to the paper page (read here) so people can discover your work more easily. You can also claim the paper as yours on Hugging Face, which will show it on your public profile.
Let me know if you're interested or need any guidance!
Kind regards,
Niels