Biblio

Scholman MCJ, Demberg V.  2017.  Crowdsourcing discourse interpretations: On the influence of context and the reliability of a connective insertion task. LAW XI 2017. :24-34.

Shi W, Demberg V.  2017.  Do We Need Cross Validation for Discourse Relation Classification? Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers.

Demberg V, Asr FTorabi, Scholman MCJ.  2017.  How consistent are our discourse annotations? Insights from mapping RST-DT and PDTB annotations arXiv preprint arXiv:1704.08893.

Rutherford A, Demberg V, Xue N.  2017.  A Systematic Study of Neural Discourse Models for Implicit Discourse Relation. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers.

Shi W, Yung F, Rubino R, Demberg V.  2017.  Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification. Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers).

Rehbein I, Scholman MCJ, Demberg V.  2016.  Annotating discourse relations in spoken language: A comparison of the PDTB and CCR frameworks. Proceedings of the Workshop on Identification and Annotation of Discourse Relations in Spoken Language.

Asr FTorabi, Demberg V.  2016.  But vs. Although under the microscope. CogSci.

Rutherford AT, Demberg V, Xue N.  2016.  Neural Network Models for Implicit Discourse Relation Classification in English and Chinese without Surface Features. arXiv preprint arXiv:1606.01990.

Asr FTorabi, Demberg V.  2015.  Uniform Surprisal at the Level of Discourse Relations: Negation Markers and Discourse Connective Omission. Proceedings of the 11th international conference on computational semantics.