Learning Meta Soft Prompt for Few-Shot Language Models
Author:
Affiliation:
1. National Yang Ming Chiao Tung University,Institute of Electrical and Computer Engineering,Hsinchu,Taiwan
2. University College London,Department of Statistical Science,London,United Kingdom
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10317071/10317095/10317500.pdf?arnumber=10317500
Reference33 articles.
1. Multisource I-Vectors Domain Adaptation Using Maximum Mean Discrepancy Based Autoencoders
2. Low-Resource Speech Synthesis with Speaker-Aware Embedding
3. Learning How to Ask: Querying LMs with Mixtures of Soft Prompts
4. The Power of Scale for Parameter-Efficient Prompt Tuning
5. Adversarial domain separation and adaptation
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Contrastive Meta Learning for Soft Prompts Using Dynamic Mixup;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
2. Mask Consistency and Contrast Regularization for Prompt-Based Learning;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
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