Efficient Adaptation

Efficient adaptation focuses on modifying pre-trained models for new tasks or domains while minimizing computational cost and data requirements. Current research emphasizes parameter-efficient fine-tuning techniques, such as low-rank adaptations (LoRAs), adapters, and prompt tuning, often incorporating elements like hierarchical structures, quantization, and memory mechanisms to enhance efficiency and generalization. These advancements are significant for deploying large models in resource-constrained environments and accelerating progress in diverse fields, including Earth observation, wildlife monitoring, and medical image analysis, by enabling rapid adaptation to specialized tasks.