Prompt Engineering On Stanford Cars 1
Metriken
Harmonic mean
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Harmonic mean |
|---|---|
| dept-decoupled-prompt-tuning | 77.79 |
| learning-hierarchical-prompt-with-structured | 75.57 |
| promptkd-unsupervised-prompt-distillation-for | 83.13 |
| self-regulating-prompts-foundational-model | 76.58 |
| learning-transferable-visual-models-from | 68.65 |
| mmrl-multi-modal-representation-learning-for | 78.06 |
| read-only-prompt-optimization-for-vision | 74.69 |
| prompt-learning-via-meta-regularization | 76.72 |
| hpt-hierarchically-prompting-vision-language | 75.59 |
| learning-domain-invariant-prompt-for-vision | 75.48 |
| conditional-prompt-learning-for-vision | 72.01 |
| maple-multi-modal-prompt-learning | 73.47 |
| consistency-guided-prompt-learning-for-vision | 75.66 |