| Solving general arithmetic word problems S Roy, D Roth arXiv preprint arXiv:1608.01413, 2016 | 340 | 2016 |
| MAWPS: A math word problem repository R Koncel-Kedziorski, S Roy, A Amini, N Kushman, H Hajishirzi Proceedings of the 2016 conference of the north american chapter of the …, 2016 | 262 | 2016 |
| Reasoning about quantities in natural language S Roy, T Vieira, D Roth Transactions of the Association for Computational Linguistics 3, 1-13, 2015 | 163 | 2015 |
| Unit dependency graph and its application to arithmetic word problem solving S Roy, D Roth Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 111 | 2017 |
| Mapping to declarative knowledge for word problem solving S Roy, D Roth Transactions of the Association for Computational Linguistics 6, 159-172, 2018 | 99 | 2018 |
| Task-oriented dialogue as dataflow synthesis J Andreas, J Bufe, D Burkett, C Chen, J Clausman, J Crawford, K Crim, ... Transactions of the Association for Computational Linguistics 8, 556-571, 2020 | 69 | 2020 |
| Constrained language models yield few-shot semantic parsers R Shin, CH Lin, S Thomson, C Chen, S Roy, EA Platanios, A Pauls, ... arXiv preprint arXiv:2104.08768, 2021 | 50 | 2021 |
| Local learning for mining outlier subgraphs from network datasets M Gupta, A Mallya, S Roy, JHD Cho, J Han Proceedings of the 2014 SIAM International Conference on Data Mining, 73-81, 2014 | 46 | 2014 |
| Local learning for mining outlier subgraphs from network datasets M Gupta, A Mallya, S Roy, JHD Cho, J Han Proceedings of the 2014 SIAM International Conference on Data Mining, 73-81, 2014 | 46 | 2014 |
| Grounding robot plans from natural language instructions with incomplete world knowledge D Nyga, S Roy, R Paul, D Park, M Pomarlan, M Beetz, N Roy Conference on robot learning, 714-723, 2018 | 42 | 2018 |
| Equation parsing: Mapping sentences to grounded equations S Roy, S Upadhyay, D Roth arXiv preprint arXiv:1609.08824, 2016 | 36 | 2016 |
| Multimodal estimation and communication of latent semantic knowledge for robust execution of robot instructions J Arkin, D Park, S Roy, MR Walter, N Roy, TM Howard, R Paul The International Journal of Robotics Research 39 (10-11), 1279-1304, 2020 | 32 | 2020 |
| Inferring task goals and constraints using bayesian nonparametric inverse reinforcement learning D Park, M Noseworthy, R Paul, S Roy, N Roy Conference on robot learning, 1005-1014, 2020 | 28 | 2020 |
| From the editors: What grounded theory is not S Roy Academy of management journal 49 (4), 633-642, 2006 | 27 | 2006 |
| Cogcompnlp: Your swiss army knife for nlp D Khashabi, M Sammons, B Zhou, T Redman, C Christodoulopoulos, ... Proceedings of the Eleventh International Conference on Language Resources …, 2018 | 21 | 2018 |
| Task-conditioned variational autoencoders for learning movement primitives M Noseworthy, R Paul, S Roy, D Park, N Roy Conference on robot learning, 933-944, 2020 | 19 | 2020 |
| Illinois math solver: Math reasoning on the web S Roy, D Roth Proceedings of the 2016 Conference of the North American Chapter of the …, 2016 | 17 | 2016 |
| Approximating the maximum overlap of polygons under translation S Har-Peled, S Roy Algorithmica 78 (1), 147-165, 2017 | 16 | 2017 |
| Illinois CCG TAC 2015 Event Nugget, Entity Discovery and Linking, and Slot Filler Validation Systems. M Sammons, H Peng, Y Song, S Upadhyay, CT Tsai, P Reddy, S Roy, ... TAC, 2015 | 16 | 2015 |
| Benchclamp: A benchmark for evaluating language models on semantic parsing S Roy, S Thomson, T Chen, R Shin, A Pauls, J Eisner, B Van Durme arXiv preprint arXiv:2206.10668, 2022 | 12 | 2022 |
Dan RothProfessor of Computer Science, University of PennsylvaniaVerified email at seas.upenn.edu
