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프롬프트 엔지니어링
Prompt Engineering On Caltech 101
Prompt Engineering On Caltech 101
평가 지표
Harmonic mean
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Harmonic mean
Paper Title
PromptKD
97.77
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
HPT++
96.96
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
MMRL
96.68
MMRL: Multi-Modal Representation Learning for Vision-Language Models
HPT
96.65
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
CoPrompt
96.55
Consistency-guided Prompt Learning for Vision-Language Models
MetaPrompt
96.32
Learning Domain Invariant Prompt for Vision-Language Models
DePT
96.28
DePT: Decoupled Prompt Tuning
ProMetaR
96.16
Prompt Learning via Meta-Regularization
RPO
96.03
Read-only Prompt Optimization for Vision-Language Few-shot Learning
MaPLe
96.02
MaPLe: Multi-modal Prompt Learning
PromptSRC
96.02
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
CoCoOp
95.84
Conditional Prompt Learning for Vision-Language Models
CLIP
95.40
Learning Transferable Visual Models From Natural Language Supervision
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