HyperAIHyperAI초신경
홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
전체 검색
소개
한국어
HyperAIHyperAI초신경
  1. 홈
  2. SOTA
  3. 프롬프트 엔지니어링
  4. Prompt Engineering On Ucf101

Prompt Engineering On Ucf101

평가 지표

Harmonic mean

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
Harmonic mean
Paper TitleRepository
PromptKD86.10PromptKD: Unsupervised Prompt Distillation for Vision-Language Models-
MetaPrompt81.35Learning Domain Invariant Prompt for Vision-Language Models-
MaPLe80.82MaPLe: Multi-modal Prompt Learning-
PromptSRC82.74Self-regulating Prompts: Foundational Model Adaptation without Forgetting-
HPT83.16Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models-
MMRL83.89MMRL: Multi-Modal Representation Learning for Vision-Language Models-
CoPrompt83.07Consistency-guided Prompt Learning for Vision-Language Models-
ProMetaR83.25Prompt Learning via Meta-Regularization-
CLIP73.85Learning Transferable Visual Models From Natural Language Supervision-
HPT++83.81HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling-
CoCoOp77.64Conditional Prompt Learning for Vision-Language Models-
RPO79.34Read-only Prompt Optimization for Vision-Language Few-shot Learning-
DePT82.46DePT: Decoupled Prompt Tuning-
0 of 13 row(s) selected.
HyperAI

학습, 이해, 실천, 커뮤니티와 함께 인공지능의 미래를 구축하다

한국어

소개

회사 소개데이터셋 도움말

제품

뉴스튜토리얼데이터셋백과사전

링크

TVM 한국어Apache TVMOpenBayes

© HyperAI초신경

TwitterBilibili