Prompt Vector

Prompt vectors are learnable parameters used to adapt large pre-trained language and vision-language models to specific tasks, offering a parameter-efficient alternative to full model fine-tuning. Current research focuses on optimizing prompt vector norms, leveraging them for multi-task learning through arithmetic operations or conditional prompting strategies, and employing them in unsupervised settings to improve model generalization across diverse domains. This approach holds significant promise for enhancing the efficiency and adaptability of large models, particularly in resource-constrained scenarios and for applications requiring rapid adaptation to new tasks or data modalities.