Angelina Wang - RankMe

57 papers A* 6Journal 38Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Ambiguity Collapse by LLMs: A Taxonomy of Epistemic Risks. CoRR Shira Gur-Arieh, Angelina Wang, Sina Fazelpour
2026	J	`jnl`	Queer NLP: A Critical Survey on Literature Gaps, Biases and Trends. CoRR Sabine Weber, Angelina Wang, Ankush Gupta, Arjun Subramonian, Dennis Ulmer, Eshaan Tanwar, Geetanjali Aich, Hannah Devinney, Jacob Hobbs, Jennifer Mickel, Joshua Tint, Mae Sosto, Ray Groshan, Simone Astarita, Vagrant Gautam, Verena Blaschke, William Agnew, Wilson Y. Lee, Yanan Long
2026	—	`conf`	SCENEBench: An Audio Understanding Benchmark Grounded in Assistive and Industrial Use Cases. EACL (Volume 1: Long Papers) Laya Iyer, Angelina Wang, Sanmi Koyejo
2026	J	`jnl`	SCENEBench: An Audio Understanding Benchmark Grounded in Assistive and Industrial Use Cases. CoRR Laya Iyer, Angelina Wang, Sanmi Koyejo
2026	J	`jnl`	The Limits of AI Data Transparency Policy: Three Disclosure Fallacies. CoRR Judy Hanwen Shen, Ken Liu, Angelina Wang, Sarah H. Cen, Andy K. Zhang, Caroline Meinhardt, Daniel Zhang, Kevin Klyman, Rishi Bommasani, Daniel E. Ho
2026	A*	`conf`	Whose Knowledge Counts? Co-Designing Community-Centered AI Auditing Tools with Educators in Hawai'i. CHI Dora Zhao, Hannah Cha, Michael J. Ryan, Angelina Wang, Rachel Baker-Ramos, Evyn-Bree Helekahi-Kaiwi, Rebecca Diego, Josiah D. Hester, Diyi Yang
2026	J	`jnl`	Whose Knowledge Counts? Co-Designing Community-Centered AI Auditing Tools with Educators in Hawai'i. CoRR Dora Zhao, Hannah Cha, Michael J. Ryan, Angelina Wang, Rachel Baker-Ramos, Evyn-Bree Helekahi-Kaiwi, Rebecca Diego, Josiah D. Hester, Diyi Yang
2025	J	`jnl`	Bridging Prediction and Intervention Problems in Social Systems. CoRR Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Hammaad Adam, Amanda Coston, Benjamin Laufer, Ezinne Nwankwo, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson
2025	J	`jnl`	Disclosure and Evaluation as Fairness Interventions for General-Purpose AI. CoRR Vyoma Raman, Judy Hanwen Shen, Andy K. Zhang, Lindsey A. Gailmard, Rishi Bommasani, Daniel E. Ho, Angelina Wang
2025	—	`conf`	Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs. ACL (1) Angelina Wang, Michelle Phan, Daniel E. Ho, Sanmi Koyejo
2025	J	`jnl`	Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs. CoRR Angelina Wang, Michelle Phan, Daniel E. Ho, Sanmi Koyejo
2025	—	`conf`	Identities are not Interchangeable: The Problem of Overgeneralization in Fair Machine Learning. FAccT Angelina Wang
2025	J	`jnl`	Identities are not Interchangeable: The Problem of Overgeneralization in Fair Machine Learning. CoRR Angelina Wang
2025	J	`jnl`	Large language models that replace human participants can harmfully misportray and flatten identity groups. Nat. Mac. Intell. Angelina Wang, Jamie Morgenstern, John P. Dickerson
2025	J	`jnl`	Measurement to Meaning: A Validity-Centered Framework for AI Evaluation. CoRR Olawale Salaudeen, Anka Reuel, Ahmed Ahmed, Suhana Bedi, Zachary Robertson, Sudharsan Sundar, Ben Domingue, Angelina Wang, Sanmi Koyejo
2025	—	`conf`	Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Ways. FAccT Angelina Wang, Xuechunzi Bai, Solon Barocas, Su Lin Blodgett
2025	—	`conf`	Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge. ICML (Position Papers) Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas J. Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2025	J	`jnl`	Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge. CoRR Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2025	J	`jnl`	Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor. CoRR Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn, Angelina Wang, Fernando Diaz, Flávio du Pin Calmon, Margaret Mitchell, Michael D. Ekstrand, Reuben Binns, Solon Barocas
2025	J	`jnl`	The California Report on Frontier AI Policy. CoRR Rishi Bommasani, Scott R. Singer, Ruth E. Appel, Sarah H. Cen, A. Feder Cooper, Elena Cryst, Lindsey A. Gailmard, Ian Klaus, Meredith M. Lee, Inioluwa Deborah Raji, Anka Reuel, Drew Spence, Alexander Wan, Angelina Wang, Daniel Zhang, Daniel E. Ho, Percy Liang, Dawn Song, Joseph E. Gonzalez, Jonathan Zittrain, Jennifer Tour Chayes, Mariano-Florentino Cuellar, Li Fei-Fei
2025	J	`jnl`	The Inadequacy of Offline LLM Evaluations: A Need to Account for Personalization in Model Behavior. CoRR Angelina Wang, Daniel E. Ho, Sanmi Koyejo
2025	J	`jnl`	The inadequacy of offline large language model evaluations: A need to account for personalization in model behavior. Patterns Angelina Wang, Daniel E. Ho, Sanmi Koyejo
2025	J	`jnl`	Toward an Evaluation Science for Generative AI Systems. CoRR Laura Weidinger, Inioluwa Deborah Raji, Hanna M. Wallach, Margaret Mitchell, Angelina Wang, Olawale Salaudeen, Rishi Bommasani, Deep Ganguli, Sanmi Koyejo, William Isaac
2025	J	`jnl`	Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations. CoRR Anka Reuel, Avijit Ghosh, Jenny Chim, Andrew Tran, Yanan Long, Jennifer Mickel, Usman Gohar, Srishti Yadav, Pawan Sasanka Ammanamanchi, Mowafak Allaham, Hossein A. Rahmani, Mubashara Akhtar, Felix Friedrich, Robert Scholz, Michael Alexander Riegler, Jan Batzner, Eliya Habba, Arushi Saxena, Anastassia Kornilova, Kevin Wei, Prajna Soni, Yohan Mathew, Kevin Klyman, Jeba Sania, Subramanyam Sahoo, Olivia Beyer Bruvik, Pouya Sadeghi, Sujata S. Goswami, Angelina Wang, Yacine Jernite, Zeerak Talat, Stella Biderman, Mykel J. Kochenderfer, Sanmi Koyejo, Irene Solaiman
2024	J	`jnl`	Benchmark suites instead of leaderboards for evaluating AI fairness. Patterns Angelina Wang, Aaron Hertzmann, Olga Russakovsky
2024	J	`jnl`	Evaluating Generative AI Systems is a Social Science Measurement Challenge. CoRR Hanna M. Wallach, Meera A. Desai, Nicholas Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alexandra Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2024	J	`jnl`	Large language models cannot replace human participants because they cannot portray identity groups. CoRR Angelina Wang, Jamie Morgenstern, John P. Dickerson
2024	J	`jnl`	Measuring Implicit Bias in Explicitly Unbiased Large Language Models. CoRR Xuechunzi Bai, Angelina Wang, Ilia Sucholutsky, Thomas L. Griffiths
2024	J	`jnl`	Measuring machine learning harms from stereotypes: requires understanding who is being harmed by which errors in what ways. CoRR Angelina Wang, Xuechunzi Bai, Solon Barocas, Su Lin Blodgett
2024	—	`—`	Operationalizing Responsible Machine Learning: From Equality Towards Equity Angelina Wang
2024	—	`conf`	Strategies for Increasing Corporate Responsible AI Prioritization. AIES (1) Angelina Wang, Teresa Datta, John P. Dickerson
2024	J	`jnl`	Strategies for Increasing Corporate Responsible AI Prioritization. CoRR Angelina Wang, Teresa Datta, John P. Dickerson
2024	—	`conf`	Visions of a Discipline: Analyzing Introductory AI Courses on YouTube. FAccT Severin Engelmann, Madiha Zahrah Choksi, Angelina Wang, Casey Fiesler
2024	J	`jnl`	Visions of a Discipline: Analyzing Introductory AI Courses on YouTube. CoRR Severin Engelmann, Madiha Zahrah Choksi, Angelina Wang, Casey Fiesler
2023	—	`conf`	Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy. FAccT Angelina Wang, Sayash Kapoor, Solon Barocas, Arvind Narayanan
2023	A*	`conf`	Gender Artifacts in Visual Datasets. ICCV Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
2023	J	`jnl`	Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 US election cycle. Big Data Soc. Arunesh Mathur, Angelina Wang, Carsten Schwemmer, Maia Hamin, Brandon M. Stewart, Arvind Narayanan
2023	J	`jnl`	Overcoming Bias in Pretrained Models by Manipulating the Finetuning Dataset. CoRR Angelina Wang, Olga Russakovsky
2023	A*	`conf`	Overwriting Pretrained Bias with Finetuning Data. ICCV Angelina Wang, Olga Russakovsky
2023	A*	`conf`	Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. AAAI Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas
2023	J	`jnl`	Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. CoRR Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas
2022	J	`jnl`	Gender Artifacts in Visual Datasets. CoRR Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky
2022	—	`conf`	Measuring Representational Harms in Image Captioning. FAccT Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach
2022	J	`jnl`	Measuring Representational Harms in Image Captioning. CoRR Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach
2022	J	`jnl`	REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets. Int. J. Comput. Vis. Angelina Wang, Alexander Liu, Ryan Zhang, Anat Kleiman, Leslie Kim, Dora Zhao, Iroha Shirai, Arvind Narayanan, Olga Russakovsky
2022	—	`conf`	Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation. FAccT Angelina Wang, Vikram V. Ramaswamy, Olga Russakovsky
2022	J	`jnl`	Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation. CoRR Angelina Wang, Vikram V. Ramaswamy, Olga Russakovsky
2021	A*	`conf`	Directional Bias Amplification. ICML Angelina Wang, Olga Russakovsky
2021	J	`jnl`	Directional Bias Amplification. CoRR Angelina Wang, Olga Russakovsky
2021	J	`jnl`	The Limits of Global Inclusion in AI Development. CoRR Alan Chan, Chinasa T. Okolo, Zachary Terner, Angelina Wang
2021	A*	`conf`	Understanding and Evaluating Racial Biases in Image Captioning. ICCV Dora Zhao, Angelina Wang, Olga Russakovsky
2021	J	`jnl`	Understanding and Evaluating Racial Biases in Image Captioning. CoRR Dora Zhao, Angelina Wang, Olga Russakovsky
2020	—	`conf`	REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets. ECCV (3) Angelina Wang, Arvind Narayanan, Olga Russakovsky
2020	J	`jnl`	ViBE: A Tool for Measuring and Mitigating Bias in Image Datasets. CoRR Angelina Wang, Arvind Narayanan, Olga Russakovsky
2019	—	`conf`	Learning Robotic Manipulation through Visual Planning and Acting. Robotics: Science and Systems Angelina Wang, Thanard Kurutach, Pieter Abbeel, Aviv Tamar
2019	J	`jnl`	Learning Robotic Manipulation through Visual Planning and Acting. CoRR Angelina Wang, Thanard Kurutach, Kara Liu, Pieter Abbeel, Aviv Tamar
2017	J	`jnl`	Safer Classification by Synthesis. CoRR William Wang, Angelina Wang, Aviv Tamar, Xi Chen, Pieter Abbeel