Emily Denton

9.8k total citations · 1 hit paper
31 papers, 1.4k citations indexed

About

Emily Denton is a scholar working on Safety Research, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Emily Denton has authored 31 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Safety Research, 13 papers in Artificial Intelligence and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Emily Denton's work include Ethics and Social Impacts of AI (13 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Disability Rights and Representation (3 papers). Emily Denton is often cited by papers focused on Ethics and Social Impacts of AI (13 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Disability Rights and Representation (3 papers). Emily Denton collaborates with scholars based in United States, Canada and United Kingdom. Emily Denton's co-authors include Alex Hanna, Inioluwa Deborah Raji, Amandalynne Paullada, Emily M. Bender, Vighnesh Birodkar, Ben Hutchinson, Margaret Mitchell, Andrew Smart, Vinodkumar Prabhakaran and Razvan Amironesei and has published in prestigious journals such as Bioinformatics, Big Data & Society and Proceedings of the ACM on Human-Computer Interaction.

In The Last Decade

Emily Denton

28 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Data and its (dis)contents: A survey of dataset development and use in machine learning research

2020 287 citations Amandalynne Paullada, Inioluwa Deborah Raji et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Emily Denton United States	15	578	361	267	157	152	31	1.4k
Abeba Birhane Ireland	14	452 0.8×	430 1.2×	81 0.3×	33 0.2×	198 1.3×	26	1.2k
Sameep Mehta India	17	483 0.8×	270 0.7×	168 0.6×	30 0.2×	173 1.1×	80	1.3k
Tiezheng Yu Hong Kong	11	1.4k 2.4×	124 0.3×	204 0.8×	102 0.6×	157 1.0×	19	2.2k
Ziwei Ji Hong Kong	10	1.3k 2.2×	122 0.3×	170 0.6×	91 0.6×	142 0.9×	22	2.1k
Angelina McMillan-Major United States	3	1.3k 2.2×	532 1.5×	144 0.5×	40 0.3×	282 1.9×	4	2.4k
Etsuko Ishii Hong Kong	5	916 1.6×	107 0.3×	124 0.5×	76 0.5×	110 0.7×	11	1.6k
Nayeon Lee Hong Kong	8	947 1.6×	110 0.3×	122 0.5×	75 0.5×	223 1.5×	16	1.7k
Rita Frieske Hong Kong	2	885 1.5×	106 0.3×	114 0.4×	72 0.5×	103 0.7×	3	1.5k
Alex Hanna United States	12	351 0.6×	283 0.8×	114 0.4×	19 0.1×	180 1.2×	26	969

Countries citing papers authored by Emily Denton

Since Specialization

Citations

This map shows the geographic impact of Emily Denton's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Emily Denton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emily Denton more than expected).

Fields of papers citing papers by Emily Denton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emily Denton. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Emily Denton. The network helps show where Emily Denton may publish in the future.

Co-authorship network of co-authors of Emily Denton

This figure shows the co-authorship network connecting the top 25 collaborators of Emily Denton. A scholar is included among the top collaborators of Emily Denton based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emily Denton. Emily Denton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Denton, Emily, et al.. (2024). Beyond Fairness in Computer Vision: A Holistic Approach to Mitigating Harms and Fostering Community-Rooted Computer Vision Research. 16(3). 215–321. 2 indexed citations

2.

Madaio, Michael, et al.. (2024). Learning about Responsible AI On-The-Job: Learning Pathways, Orientations, and Aspirations. 1544–1558. 11 indexed citations

3.

Shelby, Renee, et al.. (2024). AI’s Regimes of Representation: A Community-Centered Study of Text-to-Image Models in South Asia.

4.

Prabhakaran, Vinodkumar, Emily Denton, Sarah Laszlo, et al.. (2024). ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation. 12333–12347. 5 indexed citations

5.

Kane, Shaun K., et al.. (2023). "I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models. Edinburgh Research Explorer (University of Edinburgh). 205–216. 67 indexed citations

6.

Corbett, Eric & Emily Denton. (2023). Interrogating the T in FAccT. 1624–1634. 8 indexed citations

7.

Corbett, Eric, Emily Denton, & Sheena Erete. (2023). Power and Public Participation in AI. 1–13. 15 indexed citations

8.

Shelby, Renee, et al.. (2023). AI’s Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia. arXiv (Cornell University). 506–517. 35 indexed citations

9.

Denton, Emily, David J. Fleet, Raphael Gontijo Lopes, et al.. (2022). Photorealistic Text-To-Image Diffusion Models with Deep Language Understanding. 36479–36494. 2 indexed citations

10.

Sitthi-Amorn, Anna, Emily Denton, Saman K. Hashmi, et al.. (2022). Improving Blood Product Transfusion Premedication Plan Documentation: A Single-institution Quality Improvement Effort. Pediatric Quality and Safety. 7(3). e572–e572.

11.

Denton, Emily, et al.. (2021). Artsheets for Art Datasets. Neural Information Processing Systems. 1 indexed citations

12.

Raji, Inioluwa Deborah, Emily M. Bender, Amandalynne Paullada, Emily Denton, & Alex Hanna. (2021). AI and the Everything in the Whole Wide World Benchmark. arXiv (Cornell University). 11 indexed citations

13.

Hutchinson, Ben, et al.. (2020). Social Biases in NLP Models as Barriers for Persons with Disabilities. 5491–5501. 144 indexed citations

14.

Paullada, Amandalynne, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, & Alex Hanna. (2020). Data and its (dis)contents: A survey of dataset development and use in machine learning research. arXiv (Cornell University). 287 indexed citations breakdown →

15.

Hanna, Alex & Emily Denton. (2020). CtrlZ.AI zine fair: critical perspectives. 686–686. 3 indexed citations

16.

Hanna, Alex, et al.. (2020). Algorithmically encoded identities: reframing human classification. 681–681. 1 indexed citations

17.

Denton, Emily & Vighnesh Birodkar. (2017). Unsupervised Learning of Disentangled Representations from Video. Neural Information Processing Systems. 30. 4414–4423. 115 indexed citations

18.

Denton, Emily, Jason Weston, Manohar Paluri, Lubomir Bourdev, & Rob Fergus. (2015). User Conditional Hashtag Prediction for Images. 1731–1740. 50 indexed citations

19.

Denton, Emily, et al.. (2014). A global assessment of cancer genomic alterations in epigenetic mechanisms. Epigenetics & Chromatin. 7(1). 29–29. 55 indexed citations

20.

Denton, Emily, et al.. (2013). ChromoHub V2: cancer genomics. Bioinformatics. 30(4). 590–592. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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