Mitchell, Margaret

VQA: Visual Question Answering

Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C. L., & Parikh, D. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsVisual Attention and Saliency Detection

Cited by 4,487

Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing

Raji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., Smith-Loud, J., Theron, D., & Barnes, P. (2020) · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 2,245

Mitigating Unwanted Biases with Adversarial Learning

Zhang, B. H., Lemoine, B., & Mitchell, M. (2018) · Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIPrivacy-Preserving Technologies in Data

Cited by 1,387

VQA: Visual Question Answering: www.visualqa.org

Agrawal, A., Lu, J., Antol, S., Mitchell, M., Zitnick, C. L., Parikh, D., & Batra, D. (2017) · International Journal of Computer Vision

Multimodal Machine Learning ApplicationsVisual Attention and Saliency Detection

Cited by 570

Spoken Language Derived Measures for Detecting Mild Cognitive Impairment

Roark, B., Mitchell, M., Hosom, J.-P., Hollingshead, K., & Kaye, J. (2011) · IEEE Transactions on Audio, Speech, and Language Processing

Dementia and Cognitive Impairment ResearchEmotion and Mood Recognition

Cited by 355

Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus

Dodge, J., Sap, M., Marasović, A., Agnew, W., Ilharco, G., Groeneveld, D., Mitchell, M., & Gardner, M. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 306

Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing

Raji, I. D., Gebru, T., Mitchell, M., Buolamwini, J., Lee, J., & Denton, R. (2020) · Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIFace recognition and analysis

Cited by 299

50 Years of Test (Un)fairness: Lessons for Machine Learning

Hutchinson, B., & Mitchell, M. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIDiscrimination and Equality Law

Cited by 297

Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure

Hutchinson, B., Smart, A., Hanna, A., Denton, R., Greer, C., Kjartansson, O., Barnes, P., & Mitchell, M. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 279

Generating Natural Questions About an Image

Mostafazadeh, N., Misra, I., Devlin, J., Mitchell, M., He, X., & Vanderwende, L. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 270

Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing

Raji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., Smith-Loud, J., Theron, D., & Barnes, P. (2020) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 179

Quantifying the Language of Schizophrenia in Social Media

Mitchell, M., Hollingshead, K., & Coppersmith, G. (2015) · Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality

Mental Health via WritingSentiment Analysis and Opinion Mining

Cited by 172

Perturbation Sensitivity Analysis to Detect Unintended Model Biases

Prabhakaran, V., Hutchinson, B., & Mitchell, M. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 115

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

Laurençon, H., Saulnier, L., Wang, T., Akiki, C., del Moral, A. V., Scao, T. L., Von Werra, L., Mou, C., Ponferrada, E. G., Nguyen, H., et al. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 93

Data Governance in the Age of Large-Scale Data-Driven Language Technology

Jernite, Y., Nguyen, H., Biderman, S., Rogers, A., Masoud, M., Danchev, V., Tan, S., Luccioni, A. S., Subramani, N., Johnson, I., et al. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 75

Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing

Raji, I. D., Gebru, T., Mitchell, M., Buolamwini, J., Lee, J., & Denton, E. (2020) · arXiv

Ethics and Social Impacts of AIFace recognition and analysis

Cited by 69

A Survey of Current Datasets for Vision and Language Research

Ferraro, F., Mostafazadeh, N., Huang, T.-H., Vanderwende, L., Devlin, J., Galley, M., & Mitchell, M. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

Multimodal Machine Learning ApplicationsNatural Language Processing Techniques

Cited by 68

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Penedo, G., Kydlíček, H., allal, L. B., Lozhkov, A., Mitchell, M., Raffel, C., Von Werra, L., & Wolf, T. (2024) · arXiv

Topic ModelingComputational and Text Analysis Methods

Cited by 53

The Stack: 3 TB of permissively licensed source code

Kocetkov, D., Li, R., Allal, L. B., Li, J., Mou, C., Ferrandis, C. M., Jernite, Y., Mitchell, M., Hughes, S., Wolf, T., et al. (2022) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 42

Fully Autonomous AI Agents Should Not be Developed

Mitchell, M., Ghosh, A., Luccioni, A. S., & Pistilli, G. (2025) · arXiv

Ethics and Social Impacts of AISafety Systems Engineering in Autonomy

Cited by 11