Papers by Zhiwu Lu

1 papers
Visual Prompt Tuning for Few-Shot Text Classification (2022.coling-1)

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Challenge: Existing work on pretraining models for text classification uses image encoders instead of visual prompts.
Approach: They propose a method to deploy large-scale pre-trained models in the prompt-tuning paradigm in few-shot learning.
Outcome: The proposed method outperforms the most recent prompt-tuning methods on five public text classification datasets.

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