Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Hi, I want to add our video benchmark Vinoground to the lmms-eval database. This temporal counterfactual benchmark contains 1000 short and natural video-caption pairs. The best model, GPT-4o, can only perform at 35% on one of our metrics, while humans can achieve ~90% at ease. I have been able to reproduce our results with the code provided here on LLaVA-Video-7B-Qwen2. I believe that more models should be allowed to evaluate on Vinoground to truly test their dense temporal reasoning capabilities, and hence i find lmms-eval a great platform to do so.