Papers by Ofer Sabo

1 papers
Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes (2021.tacl-1)

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Challenge: a recent study has focused on few-shot learning (FSL) for relation classification, but it requires large amounts of training data.
Approach: They propose a method for deriving more realistic few-shot test data from available datasets for supervised RC.
Outcome: The proposed method yields a challenging benchmark for FSL-RC on which state of the art models show poor performance.

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