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Found 5 papers, 2 papers with code
Few-Shot Relation Extraction with Hybrid Visual Evidence
The MFS-HVE semantic feature extractors are developed to extract both textual and visual features.
Multi-Label Zero-Shot Product Attribute-Value Extraction
We propose HyperPAVE, a multi-label zero-shot attribute value extraction model that leverages inductive inference in heterogeneous hypergraphs.
Knowledge-Enhanced Multi-Label Few-Shot Product Attribute-Value Extraction
Existing attribute-value extraction (AVE) models require large quantities of labeled data for training.
Prompt-based Zero-shot Relation Extraction with Semantic Knowledge Augmentation
We learn the representations of both seen and unseen relations with augmented instances and prompts.
Zero-shot Relation Classification from Side Information
We propose a zero-shot learning relation classification (ZSLRC) framework that improves on state-of-the-art by its ability to recognize novel relations that were not present in training data.
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