Angelina Wang

Orcid: 0000-0001-9140-3523

According to our database1, Angelina Wang authored at least 23 papers between 2017 and 2024.

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Bibliography

2024
Operationalizing Responsible Machine Learning: From Equality Towards Equity
PhD thesis, 2024

Strategies for Increasing Corporate Responsible AI Prioritization.
CoRR, 2024

Measuring machine learning harms from stereotypes: requires understanding who is being harmed by which errors in what ways.
CoRR, 2024

Measuring Implicit Bias in Explicitly Unbiased Large Language Models.
CoRR, 2024

Large language models cannot replace human participants because they cannot portray identity groups.
CoRR, 2024

Visions of a Discipline: Analyzing Introductory AI Courses on YouTube.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023
Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 US election cycle.
Big Data Soc., January, 2023

Overcoming Bias in Pretrained Models by Manipulating the Finetuning Dataset.
CoRR, 2023

Overwriting Pretrained Bias with Finetuning Data.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Gender Artifacts in Visual Datasets.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Taxonomizing and Measuring Representational Harms: A Look at Image Tagging.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets.
Int. J. Comput. Vis., 2022

Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Measuring Representational Harms in Image Captioning.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
The Limits of Global Inclusion in AI Development.
CoRR, 2021

Directional Bias Amplification.
Proceedings of the 38th International Conference on Machine Learning, 2021

Understanding and Evaluating Racial Biases in Image Captioning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
ViBE: A Tool for Measuring and Mitigating Bias in Image Datasets.
CoRR, 2020

REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Learning Robotic Manipulation through Visual Planning and Acting.
CoRR, 2019

Learning Robotic Manipulation through Visual Planning and Acting.
Proceedings of the Robotics: Science and Systems XV, 2019

2017
Safer Classification by Synthesis.
CoRR, 2017


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