Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts

1 code implementation • 13 Mar 2024 • Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz, Ying WEI

Conventional wisdom suggests parameter-efficient fine-tuning of foundation models as the state-of-the-art method for transfer learning in vision, replacing the rich literature of alternatives such as meta-learning.

Domain Generalization Few-Shot Image Classification +2