Prompt Transferability

Prompt transferability explores how effectively prompts, short instructions guiding large language models (LLMs) or other AI models, can be reused across different tasks or models. Current research focuses on improving the transferability of prompts across various domains (e.g., image classification, text generation, dialogue summarization) and model architectures (including vision-language models and LLMs), often employing techniques like prompt tuning, knowledge distillation, and contextual injection. This research is significant because it promises to improve the efficiency and effectiveness of AI systems by reducing the need for extensive retraining on new tasks, leading to more adaptable and resource-efficient AI applications.