In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization
ScientificML
This paper introduces ICG-MTO, a framework that leverages numerical foundational models to improve inter-task coupling estimation in few-shot multi-task optimization scenarios, addressing negative transfer issues.
See LICENSE file multi-task optimizationnumerical foundational modelsfew-shot learning