Alice Gatti

According to our database, Alice Gatti authored at least 9 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Bo Li, Dan Hendrycks, Mantas Mazeika

CoRR, 2024

Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?

Richard Ren, Steven Basart, Adam Khoja, Alice Gatti, Long Phan, Xuwang Yin, Mantas Mazeika, Alexander Pan, Gabriel Mukobi, Ryan H. Kim, Stephen Fitz, Dan Hendrycks

CoRR, 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, Rassin Lababidi, Lennart Justen, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Adam Khoja, Zhenqi Zhao, Ariel Herbert-Voss, Cort B. Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Liu, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Russell Kaplan, Ian Steneker, David Campbell, Brad Jokubaitis, Alex Levinson, Jean Wang, William Qian, Kallol Krishna Karmakar, Steven Basart, Stephen Fitz, Mindy Levine, Ponnurangam Kumaraguru, Uday Kiran Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks

CoRR, 2024

Toward Green AI: A Methodological Survey of the Scientific Literature.

Enrico Barbierato, Alice Gatti

IEEE Access, 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, Lennart Justen, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Ariel Herbert-Voss, Cort B. Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Lin, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Ian Steneker, David Campbell, Brad Jokubaitis, Steven Basart, Stephen Fitz, Ponnurangam Kumaraguru, Kallol Krishna Karmakar, Uday Kiran Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Improving Energy Conserving Descent for Machine Learning: Theory and Practice.

Giuseppe Bruno De Luca, Alice Gatti, Eva Silverstein

CoRR, 2023

2022

Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks.

Alice Gatti, Zhixiong Hu, Tess E. Smidt, Esmond G. Ng, Pieter Ghysels

J. Mach. Learn. Res., 2022

Deep Learning and Spectral Embedding for Graph Partitioning.

Alice Gatti, Zhixiong Hu, Tess E. Smidt, Esmond G. Ng, Pieter Ghysels

Proceedings of the 2022 SIAM Conference on Parallel Processing for Scientific Computing, 2022

2021

Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning.

Alice Gatti, Zhixiong Hu, Pieter Ghysels, Esmond G. Ng, Tess E. Smidt

CoRR, 2021