Selected publications listed below. Full list of publications available at Google Scholar.
Note: I am in the process of changing my name. Some of my publications may still appear under my old name, Emily Denton.

“They only care to show us the wheelchair”: disability representation in text-to-image AI models
K. Mack, R. Qadri, R. Denton, S. Kane, C. Bennett
Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI), 2024.

Beyond the surface: a global-scale analysis of visual stereotypes in text-to-image generation
A. Jha, V. Prabhakaran, R. Denton, S. Laszlo, S. Dave, R. Qadri, C. Reddy, S. Dev
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024.

Power and public participation in AI
E. Corbett, R. Denton, S. Erete
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAMMO), 2023.

AI’s Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia
R. Qadri, R. Shelby, C. Bennett, R. Denton
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT*), 2023.

Interrogating the T in FAccT
E. Corbett, R. Denton
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT*), 2023.

“I wouldn’t say offensive but…”: Disability-Centered Perspectives on Large Language Models
V. Gadiraju, S. Kane, S. Dev, A. Taylor, D. Wang, R. Denton, R. Brewer
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT*), 2023.

From Human to Data to Dataset: Mapping the Traceability of Human Subjects in Computer Vision Datasets
M. Scheuerman, K. Weathington, T. Mugunthan, R. Denton, C. Fiesler
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2022.

Crowdworksheets: Accounting for individual and collective identities underlying crowdsourced dataset annotation
M. Díaz, I. Kivlichan, R. Rosen, D. Baker, R. Amironesei, V. Prabhakaran, R. Denton
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT*), 2022.

Whose ground truth? accounting for individual and collective identities underlying dataset annotation
R. Denton, M. Díaz, I. Kivlichan, V. Prabhakaran, R. Rosen
NeurIPS Workshop on Data-Centric AI, 2021.

Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research
B. Koch, R. Denton, A. Hanna, J. Foster
NeurIPS (Datasets and Benchmarks track), 2021.

Artsheets for Art Datasets
R. Srinivasan, R. Denton, J. Famularo, N. Rostamzadeh, F. Diaz, B. Coleman
NeurIPS (Datasets and Benchmarks track), 2021.

AI and the Everything in the Whole Wide World Benchmark
I Raji, E. Bender, A. Paullada, R. Denton, A. Hanna
NeurIPS (Datasets and Benchmarks track), 2021.

Whose Ground Truth? Accounting for Individual and Collective Identities Underlying Dataset Annotation
R. Denton, M Díaz, I Kivlichan, V Prabhakaran, R Rosen
NeurIPS Data-Centric AI Workshop, 2021.

On the Genealogy of Machine Learning Datasets: A Critical History of ImageNet
R. Denton, A. Hanna, R. Amironesei, A. Smart, H. Nicole
Big Data & Society, 2021.

Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development
M. Scheuerman, R. Denton, A. Hanna.
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2021.

Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure.
B. Hutchinson, A. Smart, A. Hanna, R. Denton, C. Greer, O. Kjartansson, P. Barnes, M. Mitchell
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT*), 2021.

Data and its (dis)contents: A survey of dataset development and use in machine learning research
A. Paullada, D. Raji, E. Bender, R. Denton, A. Hanna
NeurIPS Workshop on Machine LearningRetrospectives, Surveys, and Meta-analyses, 2020.

Lines of Sight
A. Hanna, R. Denton, R. Amironesei, A. Smart, H. Nicole
Logic Magazine: Commons, 2020.

Bringing the People Back In: Contesting Benchmark Machine Learning Datasets.
R. Denton, A Hanna, R Amironesei, A. Smart, H. Nicole, M. Scheuerman
ICML Workshop on Participatory Approaches to Machine Learning, 2020.

Social Biases in NLP Models as Barriers for Persons with Disabilities.
B. Hutchinson, V. Prabhakaran, R. Denton, K. Webster, Y. Zhong, S. Denuyl.
Association for Computational Linguistics (ACL), 2020.

Learning to diversify from human judgments: research directions and open challenges.
R. Denton, H. Srinivasan, D. Baker, J. Chen, A. Beutel, T. Doshi, E. Chi.
Human-Centered Approach to Fair & Responsible AI @ CHI, 2020.

Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing.
I. Raji, T. Gebru, M. Mitchell, J. Buolamwini, J. Lee, R. Denton.
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, 2020.

Diversity and Inclusion Metrics in Subset Selection.
M. Mitchell, D. Baker, N. Moorosi, R. Denton, B. Hutchinson, A. Hanna, T. Gebru, J. Morgenstern.
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, 2020.

Towards a Critical Race Methodology in Algorithmic Fairness.
A. Hanna, R. Denton, A. Smart, J. Smith-Loud.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT*), 2020.

Unintended Machine Learning Biases as Social Barriers for Persons with Disabilities.
B Hutchinson, V Prabhakaran, R Denton, K Webster, Y Zhong, S Denuyl.
SIGACCESS ASSETS AI Fairness Workshop, 2019.

Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning.
S Sukhbaatar, R Denton, A Szlam, R Fergus.
NeurIPS Deep Reinforcement Learning Workshop, 2018.

Stochastic Video Generation with a Learned Prior.
R. Denton and R. Fergus.
International Conference on Machine Learning (ICML), 2018.

Modeling Others using Oneself in Multi-Agent Reinforcement Learning.
R. Raileanu, R. Denton, A. Szlam, R. Fergus
International Conference on Machine Learning (ICML), 2018.

Unsupervised Learning of Disentangled Representations from Video.
R. Denton and V. Birodkar.
Neural Information Processing Systems (NeurIPS), 2017.

Semi-supervised learning with context-conditional generative adversarial networks.
R. Denton, S. Gross, R. Fergus.
arXiv preprint: 1611.06430, 2016.

Deep generative image models using a Laplacian pyramid of adversarial networks.
R. Denton, S. Chintala, A. Szlam, R. Fergus.
Neural Information Processing Systems (NeurIPS), 2015.

User conditional hashtag prediction for images.
R. Denton, J. Weston, M. Paluri, L. Bourdev, R. Fergus.
SIGKDD Conference on Knowledge Discovery and Data Mining, 2015.

Exploiting linear structure within convolutional networks for efficient evaluation.
R. Denton, W. Zaremba, J. Bruna, Y. LeCun, R. Fergus.
Neural Information Processing Systems (NeurIPS), 2014.

A global assessment of cancer genomic alterations in epigenetic mechanisms.
M.A. Shah, R. Denton, C.H. Arrowsmith, M. Lupien, M. Schapira.
Epigenetics & Chromatin 7 (1), 29, 2014.

ChromoHub V2: cancer genomics.
M.A. Shah, R. Denton, L. Liu, M. Schapira.
Bioinformatics, 2013.

ChromoHub: a data hub for navigators of chromatin-mediated signalling.
L. Liu, X.T. Zhen, R. Denton, B.D. Marsden, M. Schapira.
Bioinformatics 28 (16), 2205-2206, 2012.