Argument Mining

In this project, we investigated several approaches to argument mining, including (a) using Pointer Networks to identify links between argument constituents, (b) studying memory networks and other methods for knowledge integration in service of argument mining, and (c) integrating external signal in order to predict winners in Oxford-style debates.


P. Potash A. Romanov A. Rumshisky Here's My Point: Joint Pointer Architecture for Argument Mining. Proceedings of EMNLP 2017. Copenhagen, Denmark.

@inproceedings{potash2017here, title={Here's My Point: Joint Pointer Architecture for Argument Mining}, author={Potash, Peter and Romanov, Alexey and Rumshisky, Anna}, booktitle={Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing}, pages={1364–1373}, year={2017} }

P. Potash R. Bhattacharya A. Rumshisky Length, Interchangeability, and External Knowledge: Observations from Predicting Argument Convincingness. Proceedings of IJCNLP 2017. Taipei, Taiwan.

@inproceedings{potash_length_2017, author = “Potash, Peter and Bhattacharya, Robin and Rumshisky, Anna”, address = “Taipei, Taiwan”, title = “Length, {Interchangeability}, and {External} {Knowledge}: {Observations} from {Predicting} {Argument} {Convincingness}", booktitle = “Proceedings of the {Eighth} {International} {Joint} {Conference} on {Natural} {Language} {Processing} ({Volume} 1: {Long} {Papers})", publisher = “Asian Federation of Natural Language Processing”, year = “2017”, pages = “342–351” }

P. Potash A. Rumshisky Towards Debate Automation: a Recurrent Model for Predicting Debate Winners. Proceedings of EMNLP 2017. Copenhagen, Denmark.

@inproceedings{potash_towards_2017, author = “Potash, Peter and Rumshisky, Anna”, address = “Copenhagen, Denmark”, title = “Towards {Debate} {Automation}: a {Recurrent} {Model} for {Predicting} {Debate} {Winners}", booktitle = “Proceedings of the 2017 {Conference} on {Empirical} {Methods} in {Natural} {Language} {Processing}", publisher = “Association for Computational Linguistics”, year = “2017”, pages = “2465–2475” }