Visual Question Answering On A Okvqa
المقاييس
DA VQA Score
MC Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | DA VQA Score | MC Accuracy |
|---|---|---|
| vilbert-pretraining-task-agnostic | 9.2 | 34.1 |
| webly-supervised-concept-expansion-for | 40.7 | 53.7 |
| promptcap-prompt-guided-task-aware-image | 59.6 | 73.2 |
| a-simple-baseline-for-knowledge-based-visual | 57.5 | - |
| vlc-bert-visual-question-answering-with | 38.05 | - |
| visual-program-distillation-distilling-tools | 68.2 | 80.4 |
| lxmert-learning-cross-modality-encoder | 25.9 | 41.6 |
| krisp-integrating-implicit-and-symbolic | 42.2 | 42.2 |
| prompting-large-language-models-with-answer | 58.5 | 75.1 |
| boosting-the-power-of-small-multimodal | - | 71 |
| pythia-v01-the-winning-entry-to-the-vqa | 21.9 | 40.1 |
| omni-smola-boosting-generalist-multimodal | 70.55 | 83.75 |
| vilbert-pretraining-task-agnostic | 25.9 | 41.5 |
| vilbert-pretraining-task-agnostic | 12.0 | 42.1 |
| hydra-a-hyper-agent-for-dynamic-compositional | - | 56.35 |