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Found 3 papers, 3 papers with code
Two Optimizers Are Better Than One: LLM Catalyst Empowers Gradient-Based Optimization for Prompt Tuning
Learning a skill generally relies on both practical experience by doer and insightful high-level guidance by instructor.
Black-Box Tuning of Vision-Language Models with Effective Gradient Approximation
Parameter-efficient fine-tuning (PEFT) methods have provided an effective way for adapting large vision-language models to specific tasks or scenarios.
Texts as Images in Prompt Tuning for Multi-Label Image Recognition
Nonetheless, visual data (e. g., images) is by default prerequisite for learning prompts in existing methods.
Contrastive Learning
Multi-label Image Recognition with Partial Labels
