Meta-Sel: Efficient Demonstration Selection for In-Context Learning via Supervised Meta-Learning

Meta-Sel: Efficient Demonstration Selection for In-Context Learning via Supervised Meta-Learning explores Meta-Sel optimizes in-context learning by efficiently selecting demonstrations through a lightweight meta-learning approach, enhancing accuracy for intent classification tasks.. Commercial viability score: 6/10 in Meta-Learning.