Papers with balancing methods
Towards Realistic Low-resource Relation Extraction: A Benchmark with Empirical Baseline Study (2022.findings-emnlp)
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| Challenge: | Existing approaches to extract relational facts from text are limited in their ability to learn from limited labeled data. |
| Approach: | They propose to use prompt-based methods with few-shot labeled data to evaluate performance . data augmentation technologies and self-training are also proposed to generate more labeles in-domain data. |
| Outcome: | The proposed methods perform well in low-resource settings with 8 relation extraction datasets. |
Adaptive Hinge Balance Loss for Document-Level Relation Extraction (2023.findings-emnlp)
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| Challenge: | Document-Level Relation Extraction is a multi-label classification task . however, most entity pairs do not express any relations . |
| Approach: | They propose to use a distance between the classification threshold and predicted score to reduce the imbalance problem by balancing the easy negatives. |
| Outcome: | The proposed method is superior to other methods, the authors show . it reduces the threshold to an appropriate value, and increases quadratically with the number of entities. |