Specific Knowledge

Specific knowledge management in machine learning models, particularly large language models (LLMs), is a burgeoning research area focused on efficiently adding and removing targeted information without retraining the entire model. Current efforts utilize techniques like subspace methods to selectively manipulate knowledge representations, often within transformer-based architectures, and leverage external knowledge sources to enhance model performance and address biases. This research is crucial for improving the reliability, safety, and adaptability of AI systems across diverse applications, from medical report generation to mitigating misinformation.