Concept Vector

Concept vectors represent abstract concepts within the high-dimensional spaces of large language models (LLMs) and other deep learning models, aiming to improve model interpretability, control, and alignment with human values. Current research focuses on refining concept vector representations, moving beyond single vectors to encompass subspaces or distributions, and leveraging these vectors for tasks like steering model behavior, generating concept measures for social science research, and improving model debugging and explanation. This work is significant for enhancing our understanding of how LLMs encode knowledge, facilitating the development of more reliable and trustworthy AI systems, and providing valuable tools for various applications including social science research and explainable AI.