DAMO-NLP-SG / DAMO-NLP-SG/VideoLLaMA3

Verify evals on Papers with Code

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Description

Hi,

Niels here from the open-source team at Hugging Face. Congratulations on your work!

I've made the [paper](https://paperswithcode.co/paper/2501.13106) and [36 paper-native evaluations](https://paperswithcode.co/paper/2501.13106#results) available on Papers with Code.

The paper has results on [Image Understanding](https://paperswithcode.co/tasks/image-understanding), [Video Understanding](https://paperswithcode.co/tasks/video-understanding), [Document Understanding](https://paperswithcode.co/tasks/document-understanding), and 1 additional task page.

The VideoLLaMA3 results currently rank first on [two metrics on CLIP-CC-Bench](https://paperswithcode.co/benchmark/clip-cc-bench?task=video-understanding&eval=28556).

Would it be possible to verify these results and let me know if any score, model name, benchmark protocol, or openness metadata should be corrected? The imported rows are tied to the paper or its official release artifacts; comparison-table baselines were not added.

You can also edit the task, methods, project page, and GitHub URL directly from the paper page using your Hugging Face account.

If you'd like to showcase the results in your repository README, you can copy these live leaderboard badges (or use the “Copy PwC badge” button in the Results section):

[![Papers with Code: SOTA on CLIP-CC-Bench](https://paperswithcode.co/api/v1/papers/2501.13106/leaderboard-badge.svg?eval=28573&live=1)](https://paperswithcode.co/api/v1/papers/2501.13106/leaderboard-badge-link?eval=28573)

Kind regards,

Niels

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Research direction

Start with the linked Papers with Code paper page and its 36 paper-native evaluations, then compare each imported score, model name, benchmark protocol, and openness metadata with the paper or official release artifacts. Done means any discrepancies are identified and reported, or the imported results are confirmed as correct.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface
Domain
machine-learning
Issue type
Documentation
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
48/100

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