Papers with discriminative based models
Unsupervised Information Extraction: Regularizing Discriminative Approaches with Relation Distribution Losses (P19-1)
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| Challenge: | Existing unsupervised relation extraction models are either generative or discriminative . however, they are hard to train without supervision and are unstable . |
| Approach: | They propose a skewness loss and distribution distance loss to improve the performance of discriminative based models. |
| Outcome: | The proposed models surpass current state-of-the-art on three different datasets. |