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Prompt Engineering On Food 101

Metrics

Harmonic mean

Results

Performance results of various models on this benchmark

Model Name	Harmonic mean	Paper Title	Repository
ProMetaR	91.34	Prompt Learning via Meta-Regularization	-
HPT++	91.09	HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling	-
PromptSRC	91.10	Self-regulating Prompts: Foundational Model Adaptation without Forgetting	-
HPT	91.01	Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models	-
MaPLe	91.38	MaPLe: Multi-modal Prompt Learning	-
MMRL	91.03	MMRL: Multi-Modal Representation Learning for Vision-Language Models	-
CoCoOp	90.99	Conditional Prompt Learning for Vision-Language Models	-
MetaPrompt	91.29	Learning Domain Invariant Prompt for Vision-Language Models	-
DePT	91.22	DePT: Decoupled Prompt Tuning	-
CoPrompt	91.40	Consistency-guided Prompt Learning for Vision-Language Models	-
PromptKD	93.05	PromptKD: Unsupervised Prompt Distillation for Vision-Language Models	-
RPO	90.58	Read-only Prompt Optimization for Vision-Language Few-shot Learning	-

0 of 12 row(s) selected.

Prompt Engineering On Food 101 | SOTA | HyperAI