| Think you have solved question answering? try arc, the ai2 reasoning challenge P Clark, I Cowhey, O Etzioni, T Khot, A Sabharwal, C Schoenick, O Tafjord arXiv preprint arXiv:1803.05457, 2018 | 1389 | 2018 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1032 | 2022 |
| Can a suit of armor conduct electricity? a new dataset for open book question answering T Mihaylov, P Clark, T Khot, A Sabharwal arXiv preprint arXiv:1809.02789, 2018 | 997 | 2018 |
| Scitail: A textual entailment dataset from science question answering T Khot, A Sabharwal, P Clark Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 497 | 2018 |
| Towards understanding and harnessing the potential of clause learning P Beame, H Kautz, A Sabharwal Journal of artificial intelligence research 22, 319-351, 2004 | 413 | 2004 |
| Satisfiability solvers CP Gomes, H Kautz, A Sabharwal, B Selman Foundations of Artificial Intelligence 3, 89-134, 2008 | 407 | 2008 |
| Unifiedqa: Crossing format boundaries with a single qa system D Khashabi, S Min, T Khot, A Sabharwal, O Tafjord, P Clark, H Hajishirzi arXiv preprint arXiv:2005.00700, 2020 | 284 | 2020 |
| Parsing algebraic word problems into equations R Koncel-Kedziorski, H Hajishirzi, A Sabharwal, O Etzioni, SD Ang Transactions of the Association for Computational Linguistics 3, 585-597, 2015 | 281 | 2015 |
| Qasc: A dataset for question answering via sentence composition T Khot, P Clark, M Guerquin, P Jansen, A Sabharwal Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8082-8090, 2020 | 277 | 2020 |
| Decomposed prompting: A modular approach for solving complex tasks T Khot, H Trivedi, M Finlayson, Y Fu, K Richardson, P Clark, A Sabharwal arXiv preprint arXiv:2210.02406, 2022 | 271 | 2022 |
| Complexity-based prompting for multi-step reasoning Y Fu, H Peng, A Sabharwal, P Clark, T Khot The Eleventh International Conference on Learning Representations, 2022 | 266 | 2022 |
| Model counting CP Gomes, A Sabharwal, B Selman Handbook of satisfiability, 993-1014, 2021 | 250 | 2021 |
| Adversarial filters of dataset biases R Le Bras, S Swayamdipta, C Bhagavatula, R Zellers, M Peters, ... International conference on machine learning, 1078-1088, 2020 | 220 | 2020 |
| Algorithm selection and scheduling S Kadioglu, Y Malitsky, A Sabharwal, H Samulowitz, M Sellmann Principles and Practice of Constraint Programming–CP 2011: 17th …, 2011 | 217 | 2011 |
| Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions H Trivedi, N Balasubramanian, T Khot, A Sabharwal arXiv preprint arXiv:2212.10509, 2022 | 198 | 2022 |
| Model counting: A new strategy for obtaining good bounds CP Gomes, A Sabharwal, B Selman AAAI 6, 54-61, 2006 | 174 | 2006 |
| Combining retrieval, statistics, and inference to answer elementary science questions P Clark, O Etzioni, T Khot, A Sabharwal, O Tafjord, P Turney, D Khashabi Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 173 | 2016 |
| ♫ MuSiQue: Multihop Questions via Single-hop Question Composition H Trivedi, N Balasubramanian, T Khot, A Sabharwal Transactions of the Association for Computational Linguistics 10, 539-554, 2022 | 164 | 2022 |
| Taming the curse of dimensionality: Discrete integration by hashing and optimization S Ermon, C Gomes, A Sabharwal, B Selman International Conference on Machine Learning, 334-342, 2013 | 156 | 2013 |
| Specializing smaller language models towards multi-step reasoning Y Fu, H Peng, L Ou, A Sabharwal, T Khot International Conference on Machine Learning, 10421-10430, 2023 | 152 | 2023 |
