ProMpt Adapter

Prompt adapters are lightweight modules designed to enhance pre-trained models, particularly large language and diffusion models, by incorporating additional information beyond standard text prompts. Current research focuses on adapting models to diverse domains (e.g., unseen audio styles, personalized user preferences) and modalities (e.g., incorporating image or audio prompts alongside text), often employing techniques like cross-attention mechanisms and efficient parameter-efficient fine-tuning methods such as LoRA. This work is significant because it allows for more flexible and nuanced control over model outputs, improving performance in tasks ranging from image and audio generation to personalized language processing and multimodal understanding.