Choquette-Choo, Christopher A.

29 publications

ICML 2025 Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Christopher A. Choquette-Choo, Adam Dziedzic

ICML 2025 Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards Yangsibo Huang, Milad Nasr, Anastasios Nikolas Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang

NeurIPS 2025 Exploring the Limits of Strong Membership Inference Attacks on Large Language Models Jamie Hayes, Ilia Shumailov, Christopher A. Choquette-Choo, Matthew Jagielski, Georgios Kaissis, Milad Nasr, Meenatchi Sundaram Muthu Selva Annamalai, Niloofar Mireshghallah, Igor Shilov, Matthieu Meeus, Yves-Alexandre de Montjoye, Katherine Lee, Franziska Boenisch, Adam Dziedzic, A. Feder Cooper

ICML 2025 Language Models May Verbatim Complete Text They Were Not Explicitly Trained on Ken Liu, Christopher A. Choquette-Choo, Matthew Jagielski, Peter Kairouz, Sanmi Koyejo, Percy Liang, Nicolas Papernot

NeurIPS 2025 Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman, Matthew Jagielski, Katja Filippova, Ken Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Eleni Triantafillou, Peter Kairouz, Nicole Elyse Mitchell, Niloofar Mireshghallah, Abigail Z. Jacobs, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Ilia Shumailov, Andreas Terzis, Solon Barocas, Jennifer Wortman Vaughan, Danah Boyd, Yejin Choi, Sanmi Koyejo, Fernando Delgado, Percy Liang, Daniel E. Ho, Pamela Samuelson, Miles Brundage, David Bau, Seth Neel, Hanna Wallach, Amy B. Cyphert, Mark Lemley, Nicolas Papernot, Katherine Lee

ICLR 2025 Near-Exact Privacy Amplification for Matrix Mechanisms Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Guha Thakurta

ALT 2025 Near-Optimal Rates for O(1)-Smooth DP-SCO with a Single Epoch and Large Batches Christopher A. Choquette-Choo, Arun Ganesh, Abhradeep Guha Thakurta

ICLR 2025 Privacy Auditing of Large Language Models Ashwinee Panda, Xinyu Tang, Christopher A. Choquette-Choo, Milad Nasr, Prateek Mittal

ICLR 2025 Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien, S V Jyothir, Mohammad Aflah Khan, Jaydeep Borkar, Christopher A. Choquette-Choo, Jacob Ray Fuehne, Stella Biderman, Tracy Ke, Katherine Lee, Naomi Saphra

ICLR 2025 Scalable Extraction of Training Data from Aligned, Production Language Models Milad Nasr, Javier Rando, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Florian Tramèr, Katherine Lee

ICML 2025 Scaling Laws for Differentially Private Language Models Ryan Mckenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang

ICLR 2025 The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis

ICML 2024 Auditing Private Prediction Karan Chadha, Matthew Jagielski, Nicolas Papernot, Christopher A. Choquette-Choo, Milad Nasr

ICLR 2024 Correlated Noise Provably Beats Independent Noise for Differentially Private Learning Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta

ICLR 2024 Privacy Amplification for Matrix Mechanisms Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta

ICMLW 2024 Privacy Auditing of Large Language Models Ashwinee Panda, Xinyu Tang, Milad Nasr, Christopher A. Choquette-Choo, Prateek Mittal

ICMLW 2024 Privacy Auditing of Large Language Models Ashwinee Panda, Xinyu Tang, Milad Nasr, Christopher A. Choquette-Choo, Prateek Mittal

ICLR 2024 Teach LLMs to Phish: Stealing Private Information from Language Models Ashwinee Panda, Christopher A. Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal

NeurIPS 2023 (Amplified) Banded Matrix Factorization: A Unified Approach to Private Training Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, John Rush, Abhradeep Guha Thakurta, Zheng Xu

NeurIPS 2023 Are Aligned Neural Networks Adversarially Aligned? Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei W Koh, Daphne Ippolito, Florian Tramer, Ludwig Schmidt

NeurIPSW 2023 Correlated Noise Provably Beats Independent Noise for Differentially Private Learning Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta

ICML 2023 Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning Christopher A. Choquette-Choo, Hugh Brendan Mcmahan, J Keith Rush, Abhradeep Guha Thakurta

ICML 2023 Private Federated Learning with Autotuned Compression Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh

NeurIPS 2023 Robust and Actively Secure Serverless Collaborative Learning Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang

NeurIPS 2023 Students Parrot Their Teachers: Membership Inference on Model Distillation Matthew Jagielski, Milad Nasr, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini, Florian Tramer

NeurIPSW 2023 User Inference Attacks on Large Language Models Nikhil Kandpal, Krishna Pillutla, Alina Oprea, Peter Kairouz, Christopher A. Choquette-Choo, Zheng Xu

ICLR 2021 CaPC Learning: Confidential and Private Collaborative Learning Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang

NeurIPSW 2021 Communication Efficient Federated Learning with Secure Aggregation and Differential Privacy Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz

ICML 2021 Label-Only Membership Inference Attacks Christopher A. Choquette-Choo, Florian Tramer, Nicholas Carlini, Nicolas Papernot