Jenner, Erik

9 publications

ICLR 2025 Diffusion on Syntax Trees for Program Synthesis Shreyas Kapur, Erik Jenner, Stuart Russell

NeurIPSW 2024 Diffusion on Syntax Trees for Program Synthesis Shreyas Kapur, Erik Jenner, Stuart Russell

NeurIPS 2024 Evidence of Learned Look-Ahead in a Chess-Playing Neural Network Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, Stuart Russell

TMLR 2024 Foundational Challenges in Assuring Alignment and Safety of Large Language Models Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, Jose Hernandez-Orallo, Lewis Hammond, Eric J Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Chenyu Zhang, Ruiqi Zhong, Sean O hEigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schroeder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger

ICLR 2024 STARC: A General Framework for Quantifying Differences Between Reward Functions Joar Max Viktor Skalse, Lucy Farnik, Sumeet Ramesh Motwani, Erik Jenner, Adam Gleave, Alessandro Abate

NeurIPS 2024 When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback Leon Lang, Davis Foote, Stuart Russell, Anca Dragan, Erik Jenner, Scott Emmons

NeurIPSW 2022 A General Framework for Reward Function Distances Erik Jenner, Joar Max Viktor Skalse, Adam Gleave

ICLR 2022 Steerable Partial Differential Operators for Equivariant Neural Networks Erik Jenner, Maurice Weiler

ICCV 2021 Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice Erik Jenner, Enrique Fita Sanmartín, Fred A. Hamprecht