HyperAI초신경

홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

한국어

HyperAI초신경

Prompt Engineering On Caltech 101

평가 지표

Harmonic mean

평가 결과

이 벤치마크에서 각 모델의 성능 결과

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

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