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Prompt Engineering On Dtd

Metriken

Harmonic mean

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Harmonic mean	Paper Title	Repository
MetaPrompt	68.35	Learning Domain Invariant Prompt for Vision-Language Models
DePT	71.09	DePT: Decoupled Prompt Tuning	-
CLIP	56.37	Learning Transferable Visual Models From Natural Language Supervision
CoCoOp	64.85	Conditional Prompt Learning for Vision-Language Models
CoPrompt	72.79	Consistency-guided Prompt Learning for Vision-Language Models
RPO	68.61	Read-only Prompt Optimization for Vision-Language Few-shot Learning
PromptKD	77.94	PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
MMRL	73.82	MMRL: Multi-Modal Representation Learning for Vision-Language Models
MaPLe	68.16	MaPLe: Multi-modal Prompt Learning
HPT	72.16	Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
HPT++	74.23	HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
ProMetaR	72.31	Prompt Learning via Meta-Regularization
PromptSRC	71.75	Self-regulating Prompts: Foundational Model Adaptation without Forgetting

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