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홈뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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한국어
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  2. SOTA
  3. 프롬프트 엔지니어링
  4. Prompt Engineering On Fgvc Aircraft

Prompt Engineering On Fgvc Aircraft

평가 지표

Harmonic mean

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
Harmonic mean
Paper TitleRepository
MaPLe36.50MaPLe: Multi-modal Prompt Learning
MetaPrompt38.24Learning Domain Invariant Prompt for Vision-Language Models
PromptKD45.17PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
MMRL41.15MMRL: Multi-Modal Representation Learning for Vision-Language Models
CoCoOp27.74Conditional Prompt Learning for Vision-Language Models
HPT++41.33HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
RPO35.70Read-only Prompt Optimization for Vision-Language Few-shot Learning
ProMetaR40.25Prompt Learning via Meta-Regularization
CLIP31.09Learning Transferable Visual Models From Natural Language Supervision
PromptSRC40.15Self-regulating Prompts: Foundational Model Adaptation without Forgetting
DePT40.73DePT: Decoupled Prompt Tuning
CoPrompt39.76Consistency-guided Prompt Learning for Vision-Language Models
HPT40.28Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
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한국어

소개

회사 소개데이터셋 도움말

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뉴스튜토리얼데이터셋백과사전

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