Papers with Dual Prompt Tuning

1 papers
Dual Prompt Tuning based Contrastive Learning for Hierarchical Text Classification (2024.findings-acl)

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Challenge: Existing methods focus on hierarchy-aware text feature by exploiting explicit parent-child relationships, resulting in label confusion within each layer.
Approach: They propose a dual-prompt tuning method which emphasizes discrimination among peer labels by performing contrastive learning on each hierarchical layer.
Outcome: The proposed method outperforms existing methods on benchmark datasets and is available on github.

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