| 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 | 99 | 2019 |
| Explaining nlp models via minimal contrastive editing (mice) A Ross, A Marasović, ME Peters arXiv preprint arXiv:2012.13985, 2020 | 84 | 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 | 70 | 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 | 54 | 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 | 40 | 2019 |
| Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks Z Wu, L Qiu, A Ross, E Akyürek, B Chen, B Wang, N Kim, J Andreas, ... arXiv preprint arXiv:2307.02477, 2023 | 20 | 2023 |
| Learning Models for Actionable Recourse A Ross, H Lakkaraju, O Bastani Advances in Neural Information Processing Systems 34, 2021 | 18 | 2021 |
| Inverse Scaling: When Bigger Isn't Better IR McKenzie, A Lyzhov, M Pieler, A Parrish, A Mueller, A Prabhu, ... arXiv preprint arXiv:2306.09479, 2023 | 17 | 2023 |
| Does Self-Rationalization Improve Robustness to Spurious Correlations? A Ross, ME Peters, A Marasović arXiv preprint arXiv:2210.13575, 2022 | 6 | 2022 |
| CREST: A Joint Framework for Rationalization and Counterfactual Text Generation M Treviso, A Ross, NM Guerreiro, AFT Martins arXiv preprint arXiv:2305.17075, 2023 | 1 | 2023 |
| ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews M D'Arcy, A Ross, E Bransom, B Kuehl, J Bragg, T Hope, D Downey arXiv preprint arXiv:2306.12587, 2023 | | 2023 |
| Using Linear Approximations to Explain Complex, Blackbox Classifiers AJ Ross | | 2020 |
