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

Deutsch

Prompt Engineering On Sun397

Metriken

Harmonic mean

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Harmonic mean	Paper Title	Repository
ProMetaR	80.82	Prompt Learning via Meta-Regularization	-
DePT	81.06	DePT: Decoupled Prompt Tuning	-
PromptKD	82.60	PromptKD: Unsupervised Prompt Distillation for Vision-Language Models	-
CoCoOp	78.27	Conditional Prompt Learning for Vision-Language Models	-
CoPrompt	81.31	Consistency-guided Prompt Learning for Vision-Language Models	-
HPT	80.88	Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models	-
HPT++	81.11	HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling	-
PromptSRC	80.52	Self-regulating Prompts: Foundational Model Adaptation without Forgetting	-
MMRL	81.20	MMRL: Multi-Modal Representation Learning for Vision-Language Models	-
MaPLe	79.75	MaPLe: Multi-modal Prompt Learning	-
RPO	79.18	Read-only Prompt Optimization for Vision-Language Few-shot Learning	-
CLIP	72.23	Learning Transferable Visual Models From Natural Language Supervision	-
MetaPrompt	80.62	Learning Domain Invariant Prompt for Vision-Language Models	-

0 of 13 row(s) selected.

Prompt Engineering On Sun397 | SOTA | HyperAI