| Ghostwriter: Using an lstm for automatic rap lyric generation P Potash, A Romanov, A Rumshisky Proceedings of the 2015 Conference on Empirical Methods in Natural Language …, 2015 | 104 | 2015 |
| Semeval-2017 task 6:# hashtagwars: Learning a sense of humor P Potash, A Romanov, A Rumshisky Proceedings of the 11th International Workshop on Semantic Evaluation …, 2017 | 62 | 2017 |
| Here's my point: Joint pointer architecture for argument mining P Potash, A Romanov, A Rumshisky arXiv preprint arXiv:1612.08994, 2016 | 61 | 2016 |
| Towards debate automation: a recurrent model for predicting debate winners P Potash, A Rumshisky Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 24 | 2017 |
| Twitterhawk: A feature bucket based approach to sentiment analysis W Boag, P Potash, A Rumshisky Proceedings of the 9th International Workshop on Semantic Evaluation …, 2015 | 23 | 2015 |
| Operationalizing the legal principle of data minimization for personalization AJ Biega, P Potash, H Daumé, F Diaz, M Finck Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 18 | 2020 |
| Length, interchangeability, and external knowledge: Observations from predicting argument convincingness P Potash, R Bhattacharya, A Rumshisky Proceedings of the Eighth International Joint Conference on Natural Language …, 2017 | 12 | 2017 |
| Combining network and language indicators for tracking conflict intensity A Rumshisky, M Gronas, P Potash, M Dubov, A Romanov, S Kulshreshtha, ... International Conference on Social Informatics, 391-404, 2017 | 10 | 2017 |
| Evaluating creative language generation: The case of rap lyric ghostwriting P Potash, A Romanov, A Rumshisky arXiv preprint arXiv:1612.03205, 2016 | 8 | 2016 |
| Ranking passages for argument convincingness P Potash, A Ferguson, TJ Hazen Proceedings of the 6th Workshop on Argument Mining, 146-155, 2019 | 7 | 2019 |
| # HashtagWars: Learning a Sense of Humor P Potash, A Romanov, A Rumshisky arXiv preprint arXiv:1612.03216, 2016 | 7 | 2016 |
| Using topic modeling and text embeddings to predict deleted tweets PJ Potash, EB Bell, JJ Harrison Pacific Northwest National Lab.(PNNL), Richland, WA (United States), 2016 | 6 | 2016 |
| Simihawk at semeval-2016 task 1: A deep ensemble system for semantic textual similarity P Potash, W Boag, A Romanov, V Ramanishka, A Rumshisky Proceedings of the 10th International Workshop on Semantic Evaluation …, 2016 | 5 | 2016 |
| Recommender System Incorporating User Personality Profile through Analysis of Written Reviews. P Potash, A Rumshisky EMPIRE@ RecSys, 60-66, 2016 | 4 | 2016 |
| Here's My Point: Argumentation Mining with Pointer Networks P Potash, A Romanov, A Rumshisky | 3 | 2016 |
| Predictive model for ranking argument convincingness of text passages P Potash, TJ Hazen US Patent App. 16/785,359, 2021 | 1 | 2021 |
| Playing log (n)-questions over sentences P Potash, K Suleman arXiv preprint arXiv:1908.04660, 2019 | 1 | 2019 |
| Tracking Bias in News Sources Using Social Media: the Russia-Ukraine Maidan Crisis of 2013-2014. P Potash, A Romanov, A Rumshisky, M Gronas NLPmJ@ EMNLP, 13-18, 2017 | 1 | 2017 |
| Neural argumentation: Structure and persuasion P Potash University of Massachusetts Lowell, 2017 | 1 | 2017 |
| The Effect of Downstream Classification Tasks for Evaluating Sentence Embeddings P Potash arXiv preprint arXiv:1904.02228, 2019 | | 2019 |
