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Status: Unchecked ×Keyword: PANDAS ×Clear all

1 claim from 1 paper

1. Computer Science › Domain Adaptation and Few-Shot Learning

   PanDa: Prompt Transfer Meets Knowledge Distillation for Efficient Model Adaptation

   Zhong, Ding, Liu, Du and Tao · IEEE Transactions on Knowledge and Data Engineering · 2024

   The paper proposes a metric to predict prompt transferability and PanDa, a prompt-transfer method using knowledge distillation to reduce forgetting, and tests both on many datasets and model sizes.

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   1. UncheckedAcross 189 dataset pairings and 5 model sizes, PanDa beat plain prompt transfer by 2.3% on average and matched or beat full model-tuning.“Extensive and systematic experiments on 189 combinations of 21 source and 9 target datasets across 5 scales of PLMs demonstrate that: 1)our proposed metric works well to predict the prompt transferability; 2)ourPanDaconsistently outperforms the vanilla PoT approach by 2.3% average score (up to 24.1…”