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SOTA
Prompt Engineering
Prompt Engineering On Stanford Cars 1
Prompt Engineering On Stanford Cars 1
평가 지표
Harmonic mean
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Harmonic mean
Paper Title
Repository
DePT
77.79
DePT: Decoupled Prompt Tuning
-
HPT
75.57
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
PromptKD
83.13
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
PromptSRC
76.58
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
CLIP
68.65
Learning Transferable Visual Models From Natural Language Supervision
MMRL
78.06
MMRL: Multi-Modal Representation Learning for Vision-Language Models
RPO
74.69
Read-only Prompt Optimization for Vision-Language Few-shot Learning
ProMetaR
76.72
Prompt Learning via Meta-Regularization
HPT++
75.59
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
MetaPrompt
75.48
Learning Domain Invariant Prompt for Vision-Language Models
CoCoOp
72.01
Conditional Prompt Learning for Vision-Language Models
MaPLe
73.47
MaPLe: Multi-modal Prompt Learning
CoPrompt
75.66
Consistency-guided Prompt Learning for Vision-Language Models
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