Human Instruction

Human instruction following in AI focuses on developing models capable of accurately and reliably executing complex tasks based on diverse instructions, encompassing text, images, and audio. Current research emphasizes improving model alignment through techniques like instruction tuning and response tuning, often utilizing large language models (LLMs) and diffusion transformers, and exploring novel evaluation metrics for multi-modal, multi-turn interactions. This field is crucial for advancing human-computer interaction, enabling more intuitive and effective collaboration between humans and AI systems across various domains, from robotics and manufacturing to healthcare and education.