Andrew Gritsevskiy

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 7

Top Topics

Transfer Learning

Bipartite Networks

Factor Graph Model

Top Venues

Nat. Mac. Intell.

Trans. Mach. Learn. Res.

Publications

Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Charlie Rogers-Smith, Jeffrey Ladish, Christian Schröder de Witt
Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits. CoRR (2024)
Andrew Gritsevskiy, Arjun Panickssery, Aaron Kirtland, Derik Kauffman, Hans Gundlach, Irina Gritsevskaya, Joe Cavanagh, Jonathan Chiang, Lydia La Roux, Michelle Hung
REBUS: A Robust Evaluation Benchmark of Understanding Symbols. CoRR (2024)
Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network. Nat. Mac. Intell. 5 (11) (2023)
Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, Ethan Perez
Inverse Scaling: When Bigger Isn't Better. CoRR (2023)
Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, Ethan Perez
Inverse Scaling: When Bigger Isn't Better. Trans. Mach. Learn. Res. 2023 (2023)
Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network. CoRR (2022)
Andrew Gritsevskiy, Maksym Korablyov
Capsule networks for low-data transfer learning. CoRR (2018)