Papers › Vilio: State-of-the-art Visio-Linguistic Models applied to Hateful Memes
Vilio: State-of-the-art Visio-Linguistic Models applied to Hateful Memes
Niklas Muennighoff
This work presents Vilio, an implementation of state-of-the-art visio-linguistic models and their application to the Hateful Memes Dataset. The implemented models have been fitted into a uniform code-base and altered to yield better performance. The goal of Vilio is to provide a user-friendly starting point for any visio-linguistic problem. An ensemble of 5 different V+L models implemented in Vilio achieves 2nd place in the Hateful Memes Challenge out of 3,300 participants. The code is available at https://github.com/Muennighoff/vilio.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Meme Classification | Hateful Memes | Vilio | Accuracy | 0.695 | #11 of 17 | Archive leaderboard | report |
| Meme Classification | Hateful Memes | Vilio | ROC-AUC | 0.825 | #11 of 17 | Archive leaderboard | report |
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