Prompt Pool

Prompt pools are collections of learned prompts used to guide deep learning models, addressing challenges in continual learning and efficient adaptation to new tasks or data. Current research focuses on optimizing prompt pool architectures (e.g., Gaussian Mixture Models) and incorporating them into various frameworks, including diffusion models and vision transformers, to improve performance and mitigate catastrophic forgetting. This approach offers a parameter-efficient alternative to full model retraining, impacting fields like image restoration, document retrieval, and dialog systems by enabling more efficient and adaptable AI systems.