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Found 3 papers, 2 papers with code
Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language Models
Relation extraction aims at inferring structured human knowledge from textual documents.
Behavioral graph fraud detection in E-commerce
Our experiments show that embedding features learned from similarity based behavioral graph have achieved significant performance increase to the baseline fraud detection model in various business scenarios.
Contrastive Learning for Unsupervised Domain Adaptation of Time Series
To the best of our knowledge, ours is the first framework to learn domain-invariant, contextual representation for UDA of time series data.
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