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2020 – today
- 2024
[c3]Joar Max Viktor Skalse, Lucy Farnik, Sumeet Ramesh Motwani, Erik Jenner, Adam Gleave, Alessandro Abate:
STARC: A General Framework For Quantifying Differences Between Reward Functions. ICLR 2024- [i10]Leon Lang, Davis Foote, Stuart Russell, Anca D. Dragan, Erik Jenner, Scott Emmons:
When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning. CoRR abs/2402.17747 (2024) - [i9]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, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger:
Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR abs/2404.09932 (2024) - [i8]Shreyas Kapur, Erik Jenner, Stuart Russell:
Diffusion On Syntax Trees For Program Synthesis. CoRR abs/2405.20519 (2024) - [i7]Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, Stuart Russell:
Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. CoRR abs/2406.00877 (2024) - 2023
- [i6]Joar Skalse, Lucy Farnik, Sumeet Ramesh Motwani, Erik Jenner, Adam Gleave, Alessandro Abate:
STARC: A General Framework For Quantifying Differences Between Reward Functions. CoRR abs/2309.15257 (2023) - 2022
- [c2]Erik Jenner, Maurice Weiler:
Steerable Partial Differential Operators for Equivariant Neural Networks. ICLR 2022 - [i5]Erik Jenner, Adam Gleave:
Preprocessing Reward Functions for Interpretability. CoRR abs/2203.13553 (2022) - [i4]Erik Jenner, Herke van Hoof, Adam Gleave
:
Calculus on MDPs: Potential Shaping as a Gradient. CoRR abs/2208.09570 (2022) - [i3]Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, Stuart Russell:
imitation: Clean Imitation Learning Implementations. CoRR abs/2211.11972 (2022) - 2021
- [c1]Erik Jenner, Enrique Fita Sanmartín, Fred A. Hamprecht:
Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice. ICCV 2021: 4582-4591 - [i2]Erik Jenner, Maurice Weiler:
Steerable Partial Differential Operators for Equivariant Neural Networks. CoRR abs/2106.10163 (2021) - [i1]Erik Jenner, Enrique Fita Sanmartín, Fred A. Hamprecht:
Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice. CoRR abs/2110.02750 (2021)
Coauthor Index
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