Prompt Engineering On Oxford 102 Flower
평가 지표
Harmonic mean
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Harmonic mean |
|---|---|
| learning-transferable-visual-models-from | 74.83 |
| self-regulating-prompts-foundational-model | 85.95 |
| consistency-guided-prompt-learning-for-vision | 85.71 |
| learning-hierarchical-prompt-with-structured | 87.16 |
| learning-domain-invariant-prompt-for-vision | 84.52 |
| prompt-learning-via-meta-regularization | 86.70 |
| dept-decoupled-prompt-tuning | 86.46 |
| conditional-prompt-learning-for-vision | 81.71 |
| read-only-prompt-optimization-for-vision | 84.50 |
| hpt-hierarchically-prompting-vision-language | 85.85 |
| promptkd-unsupervised-prompt-distillation-for | 90.24 |
| maple-multi-modal-prompt-learning | 82.56 |
| mmrl-multi-modal-representation-learning-for | 86.78 |