| Gaussian LDA for Topic Models with Word Embeddings R Das, M Zaheer, C Dyer ACL, 2015 | 286 | 2015 |
| Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases with Reinforcement Learning R Das, S Dhuliawala, M Zaheer, L Vilnis, I Durugkar, A Krishnamurthy, ... ICLR, 2018 | 187* | 2018 |
| Chains of reasoning over entities, relations, and text using recurrent neural networks R Das, A Neelakantan, D Belanger, A McCallum EACL, 2017 | 164 | 2017 |
| Question answering on knowledge bases and text using universal schema and memory networks R Das, M Zaheer, S Reddy, A McCallum ACL, 2017 | 94 | 2017 |
| Multi-step retriever-reader interaction for scalable open-domain question answering R Das, S Dhuliawala, M Zaheer, A McCallum ICLR, 2019 | 82 | 2019 |
| Natural language question generation using syntax and keywords S Kalady, A Elikkottil, R Das Proceedings of QG2010: The Third Workshop on Question Generation 2, 5-14, 2010 | 77 | 2010 |
| Building dynamic knowledge graphs from text using machine reading comprehension R Das, T Munkhdalai, X Yuan, A Trischler, A McCallum ICLR, 2019 | 45 | 2019 |
| A survey on semantic parsing A Kamath, R Das AKBC, 2019 | 32 | 2019 |
| A systematic classification of knowledge, reasoning, and context within the ARC dataset M Boratko, H Padigela, D Mikkilineni, P Yuvraj, R Das, A McCallum, ... arXiv preprint arXiv:1806.00358, 2018 | 24 | 2018 |
| Weaver: Deep co-encoding of questions and documents for machine reading M Raison, PE Mazaré, R Das, A Bordes arXiv preprint arXiv:1804.10490, 2018 | 19 | 2018 |
| Multi-step entity-centric information retrieval for multi-hop question answering A Godbole, D Kavarthapu, R Das, Z Gong, A Singhal, H Zamani, M Yu, ... arXiv preprint arXiv:1909.07598, 2019 | 17* | 2019 |
| Do Multi-hop Readers Dream of Reasoning Chains? H Wang, M Yu, X Guo, R Das, W Xiong, T Gao arXiv preprint arXiv:1910.14520, 2019 | 11 | 2019 |
| Chains-of-Reasoning at TextGraphs 2019 Shared Task: Reasoning over Chains of Facts for Explainable Multi-hop Inference R Das, A Godbole, M Zaheer, S Dhuliawala, A McCallum Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural …, 2019 | 9 | 2019 |
| Optimal transport-based alignment of learned character representations for string similarity D Tam, N Monath, A Kobren, A Traylor, R Das, A McCallum arXiv preprint arXiv:1907.10165, 2019 | 7 | 2019 |
| Incorporating selectional preferences in multi-hop relation extraction R Das, A Neelakantan, D Belanger, A McCallum Proceedings of the 5th Workshop on Automated Knowledge Base Construction, 18-23, 2016 | 6 | 2016 |
| ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning M Boratko, XL Li, R Das, T O'Gorman, D Le, A McCallum EMNLP, 2020 | 3 | 2020 |
| An interface for annotating science questions M Boratko, H Padigela, D Mikkilineni, P Yuvraj, R Das, A McCallum, ... Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 3 | 2018 |
| A Simple Approach to Case-Based Reasoning in Knowledge Bases R Das, A Godbole, S Dhuliawala, M Zaheer, A McCallum AKBC, 2020 | 2 | 2020 |
| Learning String Alignments for Entity Aliases. A Traylor, N Monath, R Das, A McCallum AKBC@ NIPS, 2017 | 2 | 2017 |
| Collapsed Gibbs sampler for dirichlet process Gaussian mixture models (DPGMM) R Das Technical report, Carnegie Mellon University, United States, 2014 | 2 | 2014 |
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
