Andrew Gritsevskiy

According to our database, Andrew Gritsevskiy authored at least 9 papers between 2018 and 2025.

Collaborative distances:

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

2025

SynLlama: Generating Synthesizable Molecules and Their Analogs with Large Language Models.

Kunyang Sun, Dorian Bagni, Joseph M. Cavanagh, Yingze Wang, Jacob M. Sawyer, Andrew Gritsevskiy, Teresa Head-Gordon

CoRR, March, 2025

2024

SmileyLlama: Modifying Large Language Models for Directed Chemical Space Exploration.

Joseph M. Cavanagh, Kunyang Sun, Andrew Gritsevskiy, Dorian Bagni, Thomas D. Bannister, Teresa Head-Gordon

CoRR, 2024

Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits.

Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Charlie Rogers-Smith, Jeffrey Ladish, Christian Schröder de Witt

CoRR, 2024

REBUS: A Robust Evaluation Benchmark of Understanding Symbols.

Andrew Gritsevskiy, Arjun Panickssery, Aaron Kirtland, Derik Kauffman, Hans Gundlach, Irina Gritsevskaya, Joe Cavanagh, Jonathan Chiang, Lydia La Roux, Michelle Hung

CoRR, 2024

Unelicitable Backdoors via Cryptographic Transformer Circuits.

Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Christian Schröder de Witt

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network.

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

Nat. Mac. Intell., October, 2023

Inverse Scaling: When Bigger Isn't Better.

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

Trans. Mach. Learn. Res., 2023

2022

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network.

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

CoRR, 2022

2018

Capsule networks for low-data transfer learning.

Andrew Gritsevskiy, Maksym Korablyov

CoRR, 2018