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Models/CoPrompt

CoPrompt

Reported on 14 benchmarks across 1 task · 1 paper · 11 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing14 results

Prompt EngineeringonStanford Cars
Harmonic mean· 2023-06-01
75.66
best: 83.13 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonOxford 102 Flower
Harmonic mean· 2023-06-01
85.71
best: 90.24 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonEuroSAT
Harmonic mean· 2023-06-01
85.84
best: 91.94 (MMRL++)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonOxford-IIIT Pet Dataset
Harmonic mean· 2023-06-01
96.87
best: 97.15 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonDTD
Harmonic mean· 2023-06-01
72.79
best: 77.94 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonUCF101
Harmonic mean· 2023-06-01
83.07
best: 86.1 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonFood-101
Harmonic mean· 2023-06-01
91.4
best: 93.05 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonCaltech-101
Harmonic mean· 2023-06-01
96.55
best: 97.77 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonImageNet
Harmonic mean· 2023-06-01
74.33
best: 77.62 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonFGVC-Aircraft
Harmonic mean· 2023-06-01
39.76
best: 45.17 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonSUN397
Harmonic mean· 2023-06-01
81.31
best: 82.6 (PromptKD)
SOTA
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonImageNet-R
Top-1 accuracy %· 2023-06-01
77.51
best: 77.9 (POMP)
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonImageNet-S
Top-1 accuracy %· 2023-06-01
49.43
best: 49.8 (POMP)
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195
Prompt EngineeringonImageNet-A
Top-1 accuracy %· 2023-06-01
50.5
best: 51.6 (POMP)
Consistency-guided Prompt Learning for Vision-Language Models arXiv:2306.01195