10 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.CL2018★ 2 cited
Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification
Wei Shi, Vera Demberg
Implicit discourse relation classification is one of the most difficult steps in discourse parsing. The difficulty stems from the fact that the coherence relation must be inferred…
cs.CL2018★ 4 cited
Acquiring Annotated Data with Cross-lingual Explicitation for Implicit Discourse Relation Classification
Wei Shi, Frances Yung, Vera Demberg
Implicit discourse relation classification is one of the most challenging and important tasks in discourse parsing, due to the lack of connective as strong linguistic cues. A princ…
cs.CL2016★ 10 cited
Neural Network Models for Implicit Discourse Relation Classification in English and Chinese without Surface Features
Attapol T. Rutherford, Vera Demberg, Nianwen Xue
Inferring implicit discourse relations in natural language text is the most difficult subtask in discourse parsing. Surface features achieve good performance, but they are not read…