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Visual Question Answering On Vqa V2 Test Std 1
Metrics
overall
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| OFA | 81.98 | OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework | |
| Florence | 80.36 | Florence: A New Foundation Model for Computer Vision | |
| LXMERT (low-magnitude pruning) | - | LXMERT Model Compression for Visual Question Answering |
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