Vilio: State-of-the-art Visio-Linguistic Models applied to Hateful Memes
About
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.
Niklas Muennighoff• 2020
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Hateful Meme Detection | Hateful Memes (test) | AUROC0.8252 | 67 | |
| Hateful meme classification | HarM (test) | AUC83.1 | 31 | |
| Hateful Meme Detection | Hateful Memes (val) | AUROC81.56 | 22 |
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