LFDe: A Lighter, Faster and More Data-Efficient Pre-training Framework for Event Extraction
Author:
Affiliation:
1. National University of Defense Technology, Changsha, China
Funder
Xiangjiang Laboratory Fund
National Natural Science Foundation of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3589334.3645318
Reference51 articles.
1. Freebase
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3. Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks
4. Few-Shot Event Detection with Prototypical Amortized Conditional Random Field
5. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of NAACL. 4171--4186.
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