Papers by Yeyong Pi

1 papers
Adversarial Knowledge Stimulated Contrastive Prompting for Few-shot Language Learners (2023.findings-acl)

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Challenge: Prompt-based fine-tuning has boosted performance of Pre-trained language models on few-shot Natural Language Understanding (NLU) tasks by employing task-specific prompts.
Approach: They propose a Cloze-driven prompt framework for prompt tuning that implicitly stimulates knowledge from pre-trained language models.
Outcome: The proposed framework outperforms state-of-the-art for prompt-based fine-tuning on few-shot NLU tasks.

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