Universal Information Extraction with Meta-Pretrained Self-Retrieval (2023.findings-acl)
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Xin Cong, Bowen Yu, Mengcheng Fang, Tingwen Liu, Haiyang Yu, Zhongkai Hu, Fei Huang, Yongbin Li, Bin Wang
| Challenge: | Existing methods for IE are task-specific, resulting in specialized and isolated approaches for different tasks. |
| Approach: | They propose a method to retrieve task-specific knowledge from pretrained language models to enhance universal IE by using a Meta-Pretraining Algorithm. |
| Outcome: | The proposed method achieves the new state-of-the-art on 4 IE tasks, 12 datasets under fully-supervised, low-resource and few-shot scenarios. |
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