Domain Specific Instruction

Domain-specific instruction focuses on adapting large language models (LLMs) and other AI models to excel in specialized fields by training them on carefully curated datasets of instructions relevant to that domain. Current research emphasizes techniques like fine-tuning with domain-specific instructions, retrieval-augmented generation, and the development of specialized benchmarks for evaluating model performance across various domains, including medicine, robotics, and chip design. This approach significantly improves model accuracy and reliability within the target domain, leading to advancements in diverse applications such as medical diagnosis, robotic control, and scientific discovery.