Abstraction Ability

Abstraction ability, the capacity to identify and utilize underlying principles from concrete examples, is a key area of research in artificial intelligence, particularly concerning large language models (LLMs). Current research focuses on developing benchmarks and training methods to improve LLMs' abstraction capabilities, often employing instruction tuning and techniques like concept bottleneck models to extract and utilize abstract concepts from data. These efforts aim to enhance the generalizability and robustness of AI systems across diverse tasks, ultimately leading to more sophisticated and human-like reasoning abilities in various applications.