Contextualized embeddings from ELMo and BERT improve argument classification by 7.4-20.8 points and clustering by 7.8-12.3 points over baselines on multiple datasets.
In Proceedings of the 2013 Confer- ence of the North American Chapter of the Associ- ation for Computational Linguistics: Human Lan- guage T echnologies, pages 1120–1130
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Classification and Clustering of Arguments with Contextualized Word Embeddings
Contextualized embeddings from ELMo and BERT improve argument classification by 7.4-20.8 points and clustering by 7.8-12.3 points over baselines on multiple datasets.