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Prompt Engineering On Oxford Iiit Pet Dataset

Metrics

Harmonic mean

Results

Performance results of various models on this benchmark

Model Name	Harmonic mean	Paper Title	Repository
CLIP	94.12	Learning Transferable Visual Models From Natural Language Supervision	-
HPT++	96.91	HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling	-
RPO	96.05	Read-only Prompt Optimization for Vision-Language Few-shot Learning	-
MaPLe	96.58	MaPLe: Multi-modal Prompt Learning	-
DePT	96.37	DePT: Decoupled Prompt Tuning	-
HPT	96.71	Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models	-
ProMetaR	96.49	Prompt Learning via Meta-Regularization	-
MetaPrompt	96.26	Learning Domain Invariant Prompt for Vision-Language Models	-
PromptSRC	96.30	Self-regulating Prompts: Foundational Model Adaptation without Forgetting	-
CoPrompt	96.87	Consistency-guided Prompt Learning for Vision-Language Models	-
MMRL	96.74	MMRL: Multi-Modal Representation Learning for Vision-Language Models	-
CoCoOp	96.43	Conditional Prompt Learning for Vision-Language Models	-
PromptKD	97.15	PromptKD: Unsupervised Prompt Distillation for Vision-Language Models	-

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