Papers with clustering-based open relation extraction

1 papers
When Phrases Meet Probabilities: Enabling Open Relation Extraction with Cooperating Large Language Models (2024.acl-long)

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Challenge: Existing clustering-based open relation extraction methods use pre-trained language models . embeddings from language models are high-dimensional and anisotropic, so there is a gap .
Approach: They propose a framework that makes two LLMs work collaboratively to achieve clustering.
Outcome: The proposed framework outperforms existing methods by 1.4%3.13% on different datasets.

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