Function Generation

Function generation focuses on creating mathematical functions or code that meet specific criteria, such as exhibiting particular properties or solving defined problems. Current research emphasizes leveraging machine learning, particularly large language models (LLMs) and graph neural networks (GNNs), often combined with techniques like reinforcement learning and generative adversarial networks, to generate functional code securely and efficiently, or to approximate complex nonlinear functions with reduced computational cost. These advancements are improving software development processes by automating code generation and enhancing code security, while also offering new tools for tackling challenging problems in diverse fields like protein function prediction and optimization.