<ul data-eligibleForWebStory="false">MIT researchers explored test-time training to enhance large language models' adaptability.They found a sixfold improvement in accuracy using this method for complex tasks.Test-time training involves updating model parameters with task-specific data during deployment.Their work aims to make models more flexible for tasks requiring logical deduction.