FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning. - Rishub Tamirisa; John Won; Chengjun Lu; Ron Arel; Andy Zhou (CoRR, 2023)

FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning. - Rishub Tamirisa; Chulin Xie; Wenxuan Bao; Andy Zhou; Ron Arel; Aviv Shamsian (CVPR, 2024)

The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning. - Nathaniel Li; Alexander Pan; Anjali Gopal; Summer Yue; Daniel Berrios; Alice Gatti; Justin D. Li; Ann-Kathrin Dombrowski; Shashwat Goel; Gabriel Mukobi; Nathan Helm-Burger; Rassin Lababidi; et al. (ICML, 2024)

The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning. - Nathaniel Li; Alexander Pan; Anjali Gopal; Summer Yue; Daniel Berrios; Alice Gatti; Justin D. Li; Ann-Kathrin Dombrowski; Shashwat Goel; Long Phan; Gabriel Mukobi; Nathan Helm-Burger; et al. (CoRR, 2024)

Tamper-Resistant Safeguards for Open-Weight LLMs. - Rishub Tamirisa; Bhrugu Bharathi; Long Phan; Andy Zhou; Alice Gatti; Tarun Suresh; Maxwell Lin; Justin Wang; Rowan Wang; Ron Arel; Andy Zou; Dawn Song; et al. (ICLR, 2025)

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs. - Mantas Mazeika; Xuwang Yin; Rishub Tamirisa; Jaehyuk Lim; Bruce W. Lee; Richard Ren; Long Phan; Norman Mu; Adam Khoja; Oliver Zhang; Dan Hendrycks (CoRR, 2025)