Baracaldo, Nathalie

13 publications

ICLR 2026 GneissWeb: Preparing High Quality Data for LLMs at Scale Hajar Emami Gohari, Swanand Ravindra Kadhe, Yousaf Shah, Constantin M Adam, Abdulhamid Adebayo, Praneet Adusumilli, Farhan Ahmed, Nathalie Baracaldo, Santosh Subhashrao Borse, Yuan-Chi Chang, Xuan-Hong Dang, Nirmit Desai, Revital Eres, Ran Iwamoto, Alexei A. Karve, Yan Koyfman, Wei-Han Lee, Changchang Liu, Boris Lublinsky, Takuya Ohko, Pablo Pesce, Maroun Touma, Shiqiang Wang, Shalisha Witherspooon, Herbert Woisetschläger, David Wood, Kun-Lung Wu, Issei Yoshida, Syed Zawad, Petros Zerfos, Yi Zhou, Bishwaranjan Bhattacharjee

ICML 2025 Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu

ICLR 2025 MAP: Multi-Human-Value Alignment Palette Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar

ICLRW 2024 Data Forging Is Harder than You Think Mohamed Suliman, Swanand Kadhe, Anisa Halimi, Douglas Leith, Nathalie Baracaldo, Ambrish Rawat

AISTATS 2024 Enhancing In-Context Learning via Linear Probe Calibration Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen

ICMLW 2024 Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs Swanand Kadhe, Farhan Ahmed, Dennis Wei, Nathalie Baracaldo, Inkit Padhi

NeurIPS 2024 WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu

NeurIPSW 2023 FairSISA: Ensemble Post-Processing to Improve Fairness of Unlearning in LLMs Swanand Kadhe, Anisa Halimi, Ambrish Rawat, Nathalie Baracaldo

NeurIPSW 2023 Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks Shuli Jiang, Swanand Kadhe, Yi Zhou, Ling Cai, Nathalie Baracaldo

ICML 2023 LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson

ICLR 2023 Single-Shot General Hyper-Parameter Optimization for Federated Learning Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

NeurIPSW 2022 Benchmarking the Effect of Poisoning Defenses on the Security and Bias of the Final Model Nathalie Baracaldo, Kevin Eykholt, Farhan Ahmed, Yi Zhou, Shriti Priya, Taesung Lee, Swanand Kadhe, Yusong Tan, Sridevi Polavaram, Sterling Suggs, Yuyang Gao, David Slater

AAAI 2021 Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan