Multi-teacher distillation gathers training signals from more than one teacher, often because different teachers are strong in different domains. The process must decide which teacher examples to use and how to resolve inconsistent or overlapping guidance.
A student can combine mathematics, coding, agent, or other specialist abilities into one model. Success requires balanced data and evaluation so a dominant teacher does not erase other strengths or transfer hidden weaknesses.
ELI5
Multi-teacher distillation lets one AI student learn from several AI teachers. Each teacher can contribute examples from the area where it performs best.
For example, a student can learn mathematics from one specialist, coding from another, and agent tasks from a third. Training must balance the lessons and handle cases where teachers disagree.
