A. Feder Cooper

52 papers A* 8A 1C 1Journal 34Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming. CoRR Alexandra Chouldechova, A. Feder Cooper, Solon Barocas, Abhinav Palia, Dan Vann, Hanna M. Wallach
2026	J	`jnl`	Estimating near-verbatim extraction risk in language models with decoding-constrained beam search. CoRR A. Feder Cooper, Mark A. Lemley, Christopher De Sa, Lea Duesterwald, Allison Casasola, Jamie Hayes, Katherine Lee, Daniel E. Ho, Percy Liang
2026	J	`jnl`	Extracting books from production language models. CoRR Ahmed M. Ahmed, A. Feder Cooper, Sanmi Koyejo, Percy Liang
2026	J	`jnl`	Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies. CoRR Miles Brundage, Noemi Dreksler, Aidan Homewood, Sean McGregor, Patricia Paskov, Conrad Stosz, Girish Sastry, A. Feder Cooper, George Balston, Steven Adler, Stephen Casper, Markus Anderljung, Grace W. Lindsay, Sören Mindermann, Vasilios Mavroudis, Ben Bucknall, Charlotte Stix, Jonas Freund, Lorenzo Pacchiardi, José Hernández-Orallo, Matteo Pistillo, Michael Chen, Chris Painter, Dean W. Ball, Cullen O'Keefe, Gabriel Weil, Ben Harack, Graeme Finley, Ryan Hassan, Scott Emmons, Charles Foster, Anka Reuel, Bri Treece, Yoshua Bengio, Daniel Reti, Rishi Bommasani, Cristian Trout, Ali Shahin Shamsabadi, Rajiv Dattani, Adrian Weller, Robert Trager, Jaime Sevilla, Lauren Wagner, Lisa Soder, Ketan Ramakrishnan, Henry Papadatos, Malcolm Murray, Ryan Tovcimak
2025	J	`jnl`	Extracting memorized pieces of (copyrighted) books from open-weight language models. CoRR A. Feder Cooper, Aaron Gokaslan, Amy Cyphert, Christopher De Sa, Mark A. Lemley, Daniel E. Ho, Percy Liang
2025	—	`conf`	Measuring memorization in language models via probabilistic extraction. NAACL (Long Papers) Jamie Hayes, Marika Swanberg, Harsh Chaudhari, Itay Yona, Ilia Shumailov, Milad Nasr, Christopher A. Choquette-Choo, Katherine Lee, A. Feder Cooper
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	A*	`conf`	Scalable Extraction of Training Data from Aligned, Production Language Models. ICLR Milad Nasr, Javier Rando, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Florian Tramèr, Katherine Lee
2025	J	`jnl`	Strong Membership Inference Attacks on Massive Datasets and (Moderately) Large Language Models. CoRR Jamie Hayes, Ilia Shumailov, Christopher A. Choquette-Choo, Matthew Jagielski, Georgios Kaissis, Katherine Lee, Milad Nasr, Sahra Ghalebikesabi, Niloofar Mireshghallah, Meenatchi Sundaram Mutu Selva Annamalai, Igor Shilov, Matthieu Meeus, Yves-Alexandre de Montjoye, Franziska Boenisch, Adam Dziedzic, A. Feder Cooper
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 Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text. CoRR Nikhil Kandpal, Brian Lester, Colin Raffel, Sebastian Majstorovic, Stella Biderman, Baber Abbasi, Luca Soldaini, Enrico Shippole, A. Feder Cooper, Aviya Skowron, John Kirchenbauer, Shayne Longpre, Lintang Sutawika, Alon Albalak, Zhenlin Xu, Guilherme Penedo, Loubna Ben Allal, Elie Bakouch, John David Pressman, Honglu Fan, Dashiell Stander, Guangyu Song, Aaron Gokaslan, Tom Goldstein, Brian R. Bartoldson, Bhavya Kailkhura, Tyler Murray
2024	J	`jnl`	A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts. CoRR Alexandra Chouldechova, Chad Atalla, Solon Barocas, A. Feder Cooper, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Nicholas Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Matthew Vogel, Hannah Washington, Hanna M. Wallach
2024	A*	`conf`	Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification. AAAI A. Feder Cooper, Katherine Lee, Madiha Zahrah Choksi, Solon Barocas, Christopher De Sa, James Grimmelmann, Jon M. Kleinberg, Siddhartha Sen, Baobao Zhang
2024	J	`jnl`	Between Randomness and Arbitrariness: Some Lessons for Reliable Machine Learning at Scale. CoRR A. Feder Cooper
2024	A*	`conf`	Common Canvas: Open Diffusion Models Trained on Creative-Commons Images. CVPR Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov
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`	Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice. CoRR A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando A. Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, Amy Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna M. Wallach, Nicolas Papernot, Katherine Lee
2024	J	`jnl`	On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AI. CoRR Daniel McDuff, Tim Korjakow, Scott Cambo, Jesse Josua Benjamin, Jenny Lee, Yacine Jernite, Carlos Muñoz Ferrandis, Aaron Gokaslan, Alek Tarkowski, Joseph Lindley, A. Feder Cooper, Danish Contractor
2024	A*	`conf`	Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI. ICML Daniel McDuff, Tim Korjakow, Scott Cambo, Jesse Josua Benjamin, Jenny Lee, Yacine Jernite, Carlos Muñoz Ferrandis, Aaron Gokaslan, Alek Tarkowski, Joseph Lindley, A. Feder Cooper, Danish Contractor
2024	J	`jnl`	Stealing Part of a Production Language Model. CoRR Nicholas Carlini, Daniel Paleka, Krishnamurthy (Dj) Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr
2024	A*	`conf`	Stealing part of a production language model. ICML Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr
2024	—	`conf`	Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain (The Short Version). CSLAW Katherine Lee, A. Feder Cooper, James Grimmelmann
2024	J	`jnl`	The Files are in the Computer: Copyright, Memorization, and Generative AI. CoRR A. Feder Cooper, James Grimmelmann
2023	A*	`conf`	CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training. NeurIPS A. Feder Cooper, Wentao Guo, Khiem Pham, Tiancheng Yuan, Charlie Ruan, Yucheng Lu, Christopher De Sa
2023	J	`jnl`	CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images. CoRR Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov
2023	J	`jnl`	Report of the 1st Workshop on Generative AI and Law. CoRR A. Feder Cooper, Katherine Lee, James Grimmelmann, Daphne Ippolito, Christopher Callison-Burch, Christopher A. Choquette-Choo, Niloofar Mireshghallah, Miles Brundage, David Mimno, Madiha Zahrah Choksi, Jack M. Balkin, Nicholas Carlini, Christopher De Sa, Jonathan Frankle, Deep Ganguli, Bryant Gipson, Andres Guadamuz, Swee Leng Harris, Abigail Z. Jacobs, Elizabeth Joh, Gautam Kamath, Mark A. Lemley, Cass Matthews, Christine McLeavey, Corynne McSherry, Milad Nasr, Paul Ohm, Adam Roberts, Tom Rubin, Pamela Samuelson, Ludwig Schubert, Kristen Vaccaro, Luis Villa, Felix Wu, Elana Zeide
2023	J	`jnl`	Scalable Extraction of Training Data from (Production) Language Models. CoRR Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, Katherine Lee
2023	J	`jnl`	Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain. CoRR Katherine Lee, A. Feder Cooper, James Grimmelmann
2023	J	`jnl`	Variance, Self-Consistency, and Arbitrariness in Fair Classification. CoRR A. Feder Cooper, Solon Barocas, Christopher De Sa, Siddhartha Sen
2022	—	`conf`	Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning. FAccT A. Feder Cooper, Emanuel Moss, Benjamin Laufer, Helen Nissenbaum
2022	J	`jnl`	Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning. CoRR A. Feder Cooper, Benjamin Laufer, Emanuel Moss, Helen Nissenbaum
2022	J	`jnl`	Fast or Accurate? Governing Conflicting Goals in Highly Autonomous Vehicles. CoRR A. Feder Cooper, Karen Levy
2022	—	`conf`	Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects. FAccT Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon M. Kleinberg, Hoda Heidari
2022	J	`jnl`	Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects. CoRR Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon M. Kleinberg, Hoda Heidari
2022	J	`jnl`	Making the Unaccountable Internet: The Changing Meaning of Accounting in the Design of the Early Internet. CoRR A. Feder Cooper, Gili Vidan
2022	—	`conf`	Making the Unaccountable Internet: The Changing Meaning of Accounting in the Early ARPANET. FAccT A. Feder Cooper, Gili Vidan
2022	J	`jnl`	Non-Determinism and the Lawlessness of ML Code. CoRR A. Feder Cooper, Jonathan Frankle, Christopher De Sa
2022	—	`conf`	Non-Determinism and the Lawlessness of Machine Learning Code. CSLAW A. Feder Cooper, Jonathan Frankle, Christopher De Sa
2021	—	`conf`	Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems. EAAMO A. Feder Cooper, Karen Levy, Christopher De Sa
2021	C	`conf`	Emergent Unfairness in Algorithmic Fairness-Accuracy Trade-Off Research. AIES A. Feder Cooper, Ellen Abrams, Na Na
2021	J	`jnl`	Emergent Unfairness: Normative Assumptions and Contradictions in Algorithmic Fairness-Accuracy Trade-Off Research. CoRR A. Feder Cooper, Ellen Abrams
2021	A*	`conf`	Hyperparameter Optimization Is Deceiving Us, and How to Stop It. NeurIPS A. Feder Cooper, Yucheng Lu, Jessica Forde, Christopher De Sa
2021	J	`jnl`	Hyperparameter Optimization Is Deceiving Us, and How to Stop It. CoRR A. Feder Cooper, Yucheng Lu, Christopher De Sa
2021	J	`jnl`	Model Selection's Disparate Impact in Real-World Deep Learning Applications. CoRR Jessica Zosa Forde, A. Feder Cooper, Kweku Kwegyir-Aggrey, Chris De Sa, Michael Littman
2021	J	`jnl`	Tecnologica cosa: Modeling Storyteller Personalities in Boccaccio's Decameron. CoRR A. Feder Cooper, Maria Antoniak, Christopher De Sa, Marilyn Migiel, David Mimno
2020	A	`conf`	AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC. AISTATS Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	J	`jnl`	AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC. CoRR Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	A*	`conf`	Asymptotically Optimal Exact Minibatch Metropolis-Hastings. NeurIPS Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	J	`jnl`	Asymptotically Optimal Exact Minibatch Metropolis-Hastings. CoRR Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	J	`jnl`	Regulating Accuracy-Efficiency Trade-Offs in Distributed Machine Learning Systems. CoRR A. Feder Cooper, Karen Levy, Christopher De Sa
2020	J	`jnl`	Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research. CoRR A. Feder Cooper