| REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets A Wang, A Narayanan, O Russakovsky European Conference on Computer Vision, 733-751, 2020 | 208 | 2020 |
| Learning Robotic Manipulation through Visual Planning and Acting A Wang, T Kurutach, K Liu, P Abbeel, A Tamar Robotics: Science and Systems (RSS), 2019 | 155 | 2019 |
| Understanding and Evaluating Racial Biases in Image Captioning D Zhao, A Wang, O Russakovsky International Conference on Computer Vision (ICCV), 2021 | 145 | 2021 |
| Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation A Wang, VV Ramaswamy, O Russakovsky ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022 | 122 | 2022 |
| Directional Bias Amplification A Wang, O Russakovsky International Conference on Machine Learning (ICML), 2021 | 79 | 2021 |
| Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy A Wang, S Kapoor, S Barocas, A Narayanan ACM Conference on Fairness, Accountability, and Transparency, 2023 | 78 | 2023 |
| Measuring Representational Harms in Image Captioning A Wang, S Barocas, K Laird, H Wallach ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022 | 52 | 2022 |
| Explicitly unbiased large language models still form biased associations X Bai, A Wang, I Sucholutsky, TL Griffiths Proceedings of the National Academy of Sciences 122 (8), e2416228122, 2025 | 46* | 2025 |
| Large language models that replace human participants can harmfully misportray and flatten identity groups A Wang, J Morgenstern, JP Dickerson Nature Machine Intelligence, 1-12, 2025 | 46* | 2025 |
| Safer Classification By Synthesis W Wang, A Wang, A Tamar, X Chen, P Abbeel NeurIPS 2017 Workshop on Aligned Artificial Intelligence, 2017 | 46 | 2017 |
| Taxonomizing and Measuring Representational Harms: A Look at Image Tagging J Katzman, A Wang, M Scheuerman, SL Blodgett, K Laird, H Wallach, ... Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 | 42 | 2023 |
| Overwriting Pretrained Bias with Finetuning Data A Wang, O Russakovsky Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 40* | 2023 |
| Manipulative tactics are the norm in political emails: Evidence from 100K emails from the 2020 US election cycle A Mathur, A Wang, C Schwemmer, M Hamin, BM Stewart, A Narayanan Big Data & Society, 2023 | 39* | 2023 |
| The Limits of Global Inclusion in AI Development A Chan, CT Okolo, Z Terner, A Wang AAAI 2021 Workshop on Reframing Diversity in AI, 2021 | 37 | 2021 |
| Gender artifacts in visual datasets N Meister, D Zhao, A Wang, VV Ramaswamy, R Fong, O Russakovsky Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 31 | 2023 |
| Measuring machine learning harms from stereotypes: requires understanding who is being harmed by which errors in what ways A Wang, X Bai, S Barocas, SL Blodgett arXiv preprint arXiv:2402.04420, 2024 | 5* | 2024 |
| Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge H Wallach, M Desai, AF Cooper, A Wang, C Atalla, S Barocas, ... arXiv preprint arXiv:2502.00561, 2025 | 2* | 2025 |
| Strategies for increasing corporate responsible AI prioritization A Wang, T Datta, JP Dickerson Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7, 1514-1526, 2024 | 2 | 2024 |
| Visions of a discipline: Analyzing introductory AI courses on YouTube S Engelmann, MZ Choksi, A Wang, C Fiesler Proceedings of the 2024 ACM Conference on Fairness, Accountability, and …, 2024 | 1 | 2024 |
| Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs A Wang, M Phan, DE Ho, S Koyejo arXiv preprint arXiv:2502.01926, 2025 | | 2025 |