Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras

Understand

MTL is a learning paradigm that effectively leverages both task-specific and shared information to address multiple related tasks simultaneously.

• In contrast to STL, MTL offers a suite of benefits that enhance both the training process and the inference efficiency.
• MTL's key advantages encompass streamlined model architecture, performance enhancement, and cross-domain generalizability.
• Over the past twenty years, MTL has become widely recognized as a flexible and effective approach in various fields, including CV, NLP, recommendation systems, disease prognosis and diagnosis, and robotics.