Papers by Jeevesh Juneja

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Challenge:	Existing methods for argument mining are limited by the scarcity of manually annotated data and the highly domain-dependent nature of argumentation.
Approach:	They propose a novel transfer learning strategy to fine tune pretrained Transformer-based Language Models on a selectively masked language modeling task and a new prompt-based strategy for inter-component relation prediction.
Outcome:	The proposed method outperforms existing models on both within- and out-of-domain datasets while leveraging on the discourse context.