Yinzi Li


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A Structure-Aware Argument Encoder for Literature Discourse Analysis
Yinzi Li | Wei Chen | Zhongyu Wei | Yujun Huang | Chujun Wang | Siyuan Wang | Qi Zhang | Xuanjing Huang | Libo Wu
Proceedings of the 29th International Conference on Computational Linguistics

Existing research for argument representation learning mainly treats tokens in the sentence equally and ignores the implied structure information of argumentative context. In this paper, we propose to separate tokens into two groups, namely framing tokens and topic ones, to capture structural information of arguments. In addition, we consider high-level structure by incorporating paragraph-level position information. A novel structure-aware argument encoder is proposed for literature discourse analysis. Experimental results on both a self-constructed corpus and a public corpus show the effectiveness of our model. Resources are available at https://github.com/lemuria-wchen/SAE.