Startseite Neuigkeiten Neueste Forschungsarbeiten Tutorials Datensätze Wiki SOTA LLM-Modelle GPU-Rangliste Veranstaltungen

Deutsch

Prompt Engineering On Food 101

Metriken

Harmonic mean

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	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.