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SOTA
Ingénierie des prompts
Prompt Engineering On Fgvc Aircraft
Prompt Engineering On Fgvc Aircraft
Métriques
Harmonic mean
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
Harmonic mean
Paper Title
Repository
MaPLe
36.50
MaPLe: Multi-modal Prompt Learning
-
MetaPrompt
38.24
Learning Domain Invariant Prompt for Vision-Language Models
-
PromptKD
45.17
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
-
MMRL
41.15
MMRL: Multi-Modal Representation Learning for Vision-Language Models
-
CoCoOp
27.74
Conditional Prompt Learning for Vision-Language Models
-
HPT++
41.33
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
-
RPO
35.70
Read-only Prompt Optimization for Vision-Language Few-shot Learning
-
ProMetaR
40.25
Prompt Learning via Meta-Regularization
-
CLIP
31.09
Learning Transferable Visual Models From Natural Language Supervision
-
PromptSRC
40.15
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
-
DePT
40.73
DePT: Decoupled Prompt Tuning
-
CoPrompt
39.76
Consistency-guided Prompt Learning for Vision-Language Models
-
HPT
40.28
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
-
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