| Probing What Different NLP Tasks Teach Machines about Function Word Comprehension N Kim, R Patel, A Poliak, A Wang, P Xia, RT McCoy, I Tenney, A Ross, ... arXiv preprint arXiv:1904.11544, 2019 | 76 | 2019 |
| Explaining nlp models via minimal contrastive editing (mice) A Ross, A Marasović, ME Peters arXiv preprint arXiv:2012.13985, 2020 | 56 | 2020 |
| Competency Problems: On Finding and Removing Artifacts in Language Data M Gardner, W Merrill, J Dodge, ME Peters, A Ross, S Singh, N Smith arXiv preprint arXiv:2104.08646, 2021 | 44 | 2021 |
| Tailor: Generating and Perturbing Text with Semantic Controls A Ross, T Wu, H Peng, ME Peters, M Gardner arXiv preprint arXiv:2107.07150, 2021 | 29 | 2021 |
| How well do NLI models capture verb veridicality? A Ross, E Pavlick Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 25 | 2019 |
| Learning Models for Actionable Recourse A Ross, H Lakkaraju, O Bastani Advances in Neural Information Processing Systems 34, 2021 | 9 | 2021 |
| Using Linear Approximations to Explain Complex, Blackbox Classifiers AJ Ross | | 2020 |
