Multi Task Language Understanding

Multi-task Language Understanding (MTLU) refers to the capability of a single model to handle multiple natural language processing tasks simultaneously, aiming to enhance the model's generalization and cross-task transfer performance. The goal of MTLU is to optimize the model's performance across different language tasks through shared representations and knowledge transfer, thereby achieving more efficient and comprehensive language understanding. Its application value lies in reducing model training costs, improving task processing efficiency, and being suitable for complex and diverse real-world application scenarios.