Papers with Few-Shot Relation Extraction

2 papers
A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation Extraction (2022.findings-acl)

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Challenge: Existing approaches to introduce relation information into the model are limited by labeling and data scarcity.
Approach: They propose a direct addition approach to introduce relation information into a model by concatenating two views of relations and adding them to the original prototype.
Outcome: The proposed approach improves on the benchmark dataset FewRel 1.0 and shows comparable results to the state-of-the-art.
Enhancing the Prototype Network with Local-to-Global Optimization for Few-Shot Relation Extraction (2025.findings-naacl)

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Challenge: Relation Extraction (RE) is a task that aims to extract semantic relationships from unstructured text.
Approach: They propose a local optimization strategy that indirectly optimizes the prototypical networks by optimizing the other information contained within the prototypes.
Outcome: The proposed model improves on the FewRel 1.0 and FewRela 2.0 datasets.

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