A new hierarchical dataset and a family of fine-tuned protein language models improve T cell receptor–pHLA binding prediction ...

Traditional task-specific computational pathology models require a substantial labeled dataset for training to perform various tasks, while foundation models can be trained on large-scale, unlabeled ...

Overview:  Model distillation is a machine learning technique that transfers knowledge from a larger, more complex model to a ...