| Composition in distributional models of semantics J Mitchell, M Lapata Cognitive science 34 (8), 1388-1429, 2010 | 1187 | 2010 |
| Vector-based models of semantic composition J Mitchell, M Lapata proceedings of ACL-08: HLT, 236-244, 2008 | 938 | 2008 |
| Deep problems with neural network models of human vision JS Bowers, G Malhotra, M Dujmović, ML Montero, C Tsvetkov, V Biscione, ... Behavioral and Brain Sciences 46, e385, 2023 | 129 | 2023 |
| Ucl machine reading group: Four factor framework for fact finding (hexaf) T Yoneda, J Mitchell, J Welbl, P Stenetorp, S Riedel Proceedings of the First Workshop on Fact Extraction and VERification (FEVER …, 2018 | 120 | 2018 |
| Language models based on semantic composition J Mitchell, M Lapata Proceedings of the 2009 conference on empirical methods in natural language …, 2009 | 101 | 2009 |
| Syntactic and semantic factors in processing difficulty: An integrated measure J Mitchell, M Lapata, V Demberg, F Keller ACL 2010, Proceedings of the 48th Annual Meeting of the Association for …, 2010 | 79 | 2010 |
| Behavior analysis of NLI models: Uncovering the influence of three factors on robustness VIS Carmona, J Mitchell, S Riedel arXiv preprint arXiv:1805.04212, 2018 | 50 | 2018 |
| Extrapolation in NLP J Mitchell, P Minervini, P Stenetorp, S Riedel arXiv preprint arXiv:1805.06648, 2018 | 20 | 2018 |
| Orthogonality of syntax and semantics within distributional spaces M Steedman, J Mitchell Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 17 | 2015 |
| Priorless recurrent networks learn curiously J Mitchell, J Bowers Proceedings of the 28th international conference on computational …, 2020 | 15 | 2020 |
| Jack the reader-A machine reading framework D Weissenborn, P Minervini, T Dettmers, I Augenstein, J Welbl, ... arXiv preprint arXiv:1806.08727, 2018 | 12 | 2018 |
| The SUMMA platform prototype R Liepins, U Germann, G Barzdins, A Birch, S Renals, S Weber, ... 15th EACL 2017 Software Demonstrations, 116-119, 2017 | 5 | 2017 |
| Decomposing bilexical dependencies into semantic and syntactic vectors J Mitchell Proceedings of the 1st Workshop on Representation Learning for NLP, 127-136, 2016 | 4 | 2016 |
| Harnessing the symmetry of convolutions for systematic generalisation J Mitchell, JS Bowers 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 3 | 2020 |
| Do LSTMs know about Principle C? J Mitchell, N Kazanina, C Houghton, J Bowers Conference on Cognitive Computational Neuroscience, 188-191, 2019 | 3 | 2019 |
| Clarifying status of DNNs as models of human vision JS Bowers, G Malhotra, M Dujmović, ML Montero, C Tsvetkov, V Biscione, ... Behavioral and Brain Sciences 46, 2023 | 2 | 2023 |
| Parser adaptation to the biomedical domain without re-training J Mitchell, M Steedman Proceedings of the Sixth International Workshop on Health Text Mining and …, 2015 | 2 | 2015 |
| Learning semantic representations in a bigram language model J Mitchell Proceedings of the 10th International Conference on Computational Semantics …, 2013 | 2 | 2013 |
| Generating sparse explanations for malicious Android opcode sequences using hierarchical LIME J Mitchell, N McLaughlin, J Martinez-del-Rincon Computers & Security 137, 103637, 2024 | 1 | 2024 |
| Generalisation in neural networks does not require feature overlap J Mitchell, JS Bowers arXiv preprint arXiv:2107.06872, 2021 | 1 | 2021 |
