World's Best Scientists 2026 revealed!
Margaret Mitchell

Margaret Mitchell

D-Index & Metrics

Computer Science

D-Index
49
Citations
23663
World Ranking
5740
National Ranking
2609

Overview

Margaret Mitchell is affiliated with Hugging Face in the United States, contributing to research primarily within the domain of computer science. Their scholarly output spans 30 publications in this field, with a focus on several specialized subfields and topics.

The main subfields of study include artificial intelligence, safety research, computer vision and pattern recognition, information systems, and general health professions. The scientist's work commonly addresses themes such as topic modeling, ethics and social impacts of AI, natural language processing techniques, machine learning and data classification, explainable artificial intelligence (XAI), face recognition and analysis, and medical malpractice and liability issues.

Margaret Mitchell has authored or contributed to multiple research papers, including:

  • Helping Cancer Patients to Choose the Best Treatment: Towards Automated Data-Driven and Personalized Information Presentation of Cancer Treatment Options, 2024, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • BLOOM: A 176B-Parameter Open-Access Multilingual Language Model, 2022, arXiv (Cornell University)
  • Saving Face, 2020, Proceedings of the AAAI/ACM Conference on AI Ethics and Society
  • Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing, 2020, arXiv (Cornell University)
  • The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset, 2023, arXiv (Cornell University)

Their frequent co-authors include Alexandra Sasha Luccioni, Yacine Jernite, Jesse Dodge, Giada Pistilli, and Christopher Akiki. This network of collaborators reflects an active engagement with various researchers in the computational and AI research communities.

Margaret Mitchell's work has been published predominantly in venues such as arXiv (Cornell University), the Proceedings of the AAAI/ACM Conference on AI Ethics and Society, Leibniz-Zentrum für Informatik (Schloss Dagstuhl), the 2022 ACM Conference on Fairness, Accountability, and Transparency, and the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Among these venues, the largest number of publications have appeared on arXiv.

Best Publications

  • VQA: Visual Question Answering

    Stanislaw Antol;Aishwarya Agrawal;Jiasen Lu;Margaret Mitchell

  • Model Cards for Model Reporting

    Margaret Mitchell;Simone Wu;Andrew Zaldivar;Parker Barnes

  • VQA: Visual Question Answering

    Aishwarya Agrawal;Jiasen Lu;Stanislaw Antol;Margaret Mitchell

  • From captions to visual concepts and back

    Hao Fang;Saurabh Gupta;Forrest Iandola;Rupesh K. Srivastava

  • BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

    Unknown

  • Mitigating Unwanted Biases with Adversarial Learning

    Brian Hu Zhang;Blake Lemoine;Margaret Mitchell

  • A Neural Network Approach to Context-Sensitive Generation of Conversational Responses

    Alessandro Sordoni;Michel Galley;Michael Auli;Chris Brockett

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

    Inioluwa Deborah Raji;Andrew Smart;Rebecca N. White;Margaret Mitchell

  • Midge: Generating Image Descriptions From Computer Vision Detections

    Margaret Mitchell;Jesse Dodge;Amit Goyal;Kota Yamaguchi

  • VQA: Visual Question Answering

    Aishwarya Agrawal;Jiasen Lu;Stanislaw Antol;Margaret Mitchell

  • Spoken Language Derived Measures for Detecting Mild Cognitive Impairment

    B. Roark;M. Mitchell;J. Hosom;K. Hollingshead

  • Visual Storytelling

    Ting-Hao Kenneth Huang;Francis Ferraro;Nasrin Mostafazadeh;Ishan Misra

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

    Ben Hutchinson;Margaret Mitchell

  • Generating Natural Questions About an Image

    Nasrin Mostafazadeh;Ishan Misra;Jacob Devlin;Margaret Mitchell

  • CLPsych 2015 Shared Task: Depression and PTSD on Twitter

    Glen Coppersmith;Mark Dredze;Craig Harman;Kristy Hollingshead

  • Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing

    Inioluwa Deborah Raji;Timnit Gebru;Margaret Mitchell;Joy Buolamwini

  • Language Models for Image Captioning: The Quirks and What Works

    Jacob Devlin;Hao Cheng;Hao Fang;Saurabh Gupta

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

    Ben Hutchinson;Andrew Smart;Alex Hanna;Emily Denton

  • Exploring Nearest Neighbor Approaches for Image Captioning

    Jacob Devlin;Saurabh Gupta;Ross B. Girshick;Margaret Mitchell

  • Seeing through the Human Reporting Bias: Visual Classifiers from Noisy Human-Centric Labels

    Ishan Misra;C. Lawrence Zitnick;Margaret Mitchell;Ross Girshick

  • Open Domain Targeted Sentiment

    Margaret Mitchell;Jacqui Aguilar;Theresa Wilson;Benjamin Van Durme

  • Visual Storytelling

    Ting-Hao;Huang;Francis Ferraro;Nasrin Mostafazadeh

Frequent Co-Authors

C. Lawrence Zitnick
C. Lawrence Zitnick Facebook (United States)
Michel Galley
Michel Galley Microsoft (United States)
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
Xiaodong He
Xiaodong He Chinese Academy of Sciences
Devi Parikh
Devi Parikh Facebook (United States)
Ishan Misra
Ishan Misra Facebook (United States)
Dhruv Batra
Dhruv Batra Georgia Institute of Technology
Ehud Reiter
Ehud Reiter University of Aberdeen
Chris Brockett
Chris Brockett Microsoft (United States)
Michael Auli
Michael Auli Facebook (United States)

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