Model Mechanism

Model mechanism research aims to understand how large language models (LLMs) and other complex systems achieve their capabilities, focusing on identifying the internal computational subgraphs, or "circuits," responsible for specific tasks. Current research investigates the consistency of these mechanisms across different model scales and training stages, exploring modular architectures that allow for reusable components and efficient adaptation to new environments. Understanding these mechanisms is crucial for improving model interpretability, efficiency, and ultimately, the design of more robust and reliable AI systems.