Test-Time Training

Test-time training is a machine learning technique that enables models to adapt and improve during inference by learning from the data they are being tested on. This approach is particularly relevant to the tech community as it addresses the challenge of handling distribution shifts and improving model performance in real-world scenarios, making it a promising area of research for applications such as computer vision and natural language processing.