Basic Concept

The field of basic concepts encompasses foundational principles and methodologies across diverse areas of artificial intelligence and machine learning, aiming to improve model efficiency, robustness, and alignment with human intentions. Current research focuses on optimizing model architectures like large language models (LLMs) and diffusion models through techniques such as low-bit quantization, reinforcement learning from human feedback (RLHF), and physics-informed neural networks (PINNs), while also addressing challenges like backdoor attacks and out-of-distribution detection. This foundational work is crucial for advancing AI capabilities and ensuring responsible development, impacting fields ranging from autonomous systems and healthcare to communication networks and cybersecurity.