Edited Model

Model editing focuses on modifying pre-trained machine learning models, particularly large language models, to update or correct their knowledge without full retraining, offering a computationally efficient alternative. Current research explores various editing techniques, including those manipulating model parameters directly or altering input embeddings, aiming to improve accuracy and address issues like outdated information and susceptibility to adversarial attacks. This field is crucial for enhancing the reliability and trustworthiness of AI systems, mitigating risks associated with misinformation, and enabling more efficient knowledge updates in resource-intensive applications.