Papers with relation classification exhibiting

1 papers
Generative Prompt Tuning for Relation Classification (2022.findings-emnlp)

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Challenge: Existing prompt tuning methods for RC are limited by label spaces and rigid prompt restrictions.
Approach: They propose a generative prompt tuning method to reformulate relation classification as an infilling problem by adding cloze-style phrases to masked language modeling problems.
Outcome: The proposed method exploits rich semantics of entity and relation types and can predict label verbalizations with varying lengths at multiple predicted positions.

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