How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19? - Mrinank Sharma; Sören Mindermann; Jan Markus Brauner; Gavin Leech; Anna B. Stephenson; Tomas Gavenciak; Jan Kulveit; Yee Whye Teh; Leonid Chindelevitch; Yarin Gal (NeurIPS, 2020)

On the robustness of effectiveness estimation of nonpharmaceutical interventions against COVID-19 transmission. - Mrinank Sharma; Sören Mindermann; Jan Markus Brauner; Gavin Leech; Anna B. Stephenson; Tomas Gavenciak; Jan Kulveit; Yee Whye Teh; Leonid Chindelevitch; Yarin Gal (CoRR, 2020)

Prioritized training on points that are learnable, worth learning, and not yet learned. - Sören Mindermann; Muhammed Razzak; Winnie Xu; Andreas Kirsch 002; Mrinank Sharma; Adrien Morisot; Aidan N. Gomez; Sebastian Farquhar; Jan Markus Brauner; Yarin Gal (CoRR, 2021)

DeDUCE: Generating Counterfactual Explanations Efficiently. - Benedikt Höltgen; Lisa Schut; Jan Markus Brauner; Yarin Gal (CoRR, 2021)

Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt. - Sören Mindermann; Jan Markus Brauner; Muhammed Razzak; Mrinank Sharma; Andreas Kirsch 002; Winnie Xu; Benedikt Höltgen; Aidan N. Gomez; Adrien Morisot; Sebastian Farquhar; Yarin Gal (ICML, 2022)

Mapping global dynamics of benchmark creation and saturation in artificial intelligence. - Adriano Barbosa-Silva; Simon Ott; Kathrin Blagec; Jan Brauner; Matthias Samwald (CoRR, 2022)

Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions. - Tomas Gavenciak; Joshua Teperowski Monrad; Gavin Leech; Mrinank Sharma; Sören Mindermann; Samir Bhatt; Jan Markus Brauner; Jan Kulveit (PLoS Comput. Biol., 2022)

Question Decomposition Improves the Faithfulness of Model-Generated Reasoning. - Ansh Radhakrishnan; Karina Nguyen; Anna Chen; Carol Chen; Carson Denison; Danny Hernandez; Esin Durmus; Evan Hubinger; Jackson Kernion; Kamile Lukosiute; Newton Cheng; Nicholas Joseph; et al. (CoRR, 2023)

Measuring Faithfulness in Chain-of-Thought Reasoning. - Tamera Lanham; Anna Chen; Ansh Radhakrishnan; Benoit Steiner; Carson Denison; Danny Hernandez; Dustin Li; Esin Durmus; Evan Hubinger; Jackson Kernion; Kamile Lukosiute; Karina Nguyen; et al. (CoRR, 2023)

Managing AI Risks in an Era of Rapid Progress. - Yoshua Bengio; Geoffrey E. Hinton; Andrew Yao; Dawn Song; Pieter Abbeel; Yuval Noah Harari; Ya-Qin Zhang; Lan Xue; Shai Shalev-Shwartz; Gillian K. Hadfield; Jeff Clune; Tegan Maharaj; et al. (CoRR, 2023)

How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions. - Lorenzo Pacchiardi; Alex James Chan; Sören Mindermann; Ilan Moscovitz; Alexa Y. Pan; Yarin Gal; Owain Evans; Jan Markus Brauner (ICLR, 2024)

Thousands of AI Authors on the Future of AI. - Katja Grace; Harlan Stewart; Julia Fabienne Sandkühler; Stephen Thomas; Ben Weinstein-Raun; Jan Brauner (CoRR, 2024)

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training. - Evan Hubinger; Carson Denison; Jesse Mu; Mike Lambert; Meg Tong; Monte MacDiarmid; Tamera Lanham; Daniel M. Ziegler; Tim Maxwell; Newton Cheng; Adam S. Jermyn; Amanda Askell; et al. (CoRR, 2024)