《Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data》閱讀筆記
文章目錄 一、Argument Feature 基本假設 常用的 argument feature 問題 二、Learn Argument Compatibility from Unlabled Data 2.1 Overview 預訓練階段 Fine-tune階段 2.2 Model 三、Experiment Result Case Study 一、Argument Feature 基本假設 如
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相關文章
- 1. 閱讀筆記 Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data
- 2. 《Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution》閱讀筆記
- 3. 《Segmentation Approach for Coreference Resolution Task》閱讀筆記
- 4. 《Precision Event Coreference Resolution Using Neural Network Classifiers》閱讀筆記
- 5. Reinforcement Learning for Relation Classification from Noisy Data閱讀筆記
- 6. 論文閱讀：AutoAugment: Learning Augmentation Strategies from Data
- 7. Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data 論文閱讀筆記
- 8. 論文閱讀筆記《Low-Shot Learning from Imaginary Data》
- 9. 《Knowledge Base Completion By Learning...》閱讀筆記
- 10. Context Encoders: Feature Learning by Inpainting 閱讀筆記