HyperAI
الرئيسية
الأخبار
أحدث الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
العربية
HyperAI
Toggle sidebar
البحث في الموقع...
⌘
K
الرئيسية
SOTA
Prompt Engineering
Prompt Engineering On Caltech 101
Prompt Engineering On Caltech 101
المقاييس
Harmonic mean
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Harmonic mean
Paper Title
Repository
ProMetaR
96.16
Prompt Learning via Meta-Regularization
HPT++
96.96
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
MaPLe
96.02
MaPLe: Multi-modal Prompt Learning
CoCoOp
95.84
Conditional Prompt Learning for Vision-Language Models
PromptSRC
96.02
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
HPT
96.65
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
CLIP
95.40
Learning Transferable Visual Models From Natural Language Supervision
CoPrompt
96.55
Consistency-guided Prompt Learning for Vision-Language Models
MetaPrompt
96.32
Learning Domain Invariant Prompt for Vision-Language Models
RPO
96.03
Read-only Prompt Optimization for Vision-Language Few-shot Learning
PromptKD
97.77
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
MMRL
96.68
MMRL: Multi-Modal Representation Learning for Vision-Language Models
DePT
96.28
DePT: Decoupled Prompt Tuning
-
0 of 13 row(s) selected.
Previous
Next