Differentially Private Federated Variational Inference. - Mrinank Sharma; Michael J. Hutchinson; Siddharth Swaroop; Antti Honkela; Richard E. Turner (CoRR, 2019)

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)

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)

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)

Do Bayesian Neural Networks Need To Be Fully Stochastic? - Mrinank Sharma; Sebastian Farquhar; Eric T. Nalisnick; Tom Rainforth (AISTATS, 2023)

Understanding and Controlling a Maze-Solving Policy Network. - Ulisse Mini; Peli Grietzer; Mrinank Sharma; Austin Meek; Monte MacDiarmid; Alexander Matt Turner (CoRR, 2023)

Towards Understanding Sycophancy in Language Models. - Mrinank Sharma; Meg Tong; Tomasz Korbak; David Duvenaud; Amanda Askell; Samuel R. Bowman; Newton Cheng; Esin Durmus; Zac Hatfield-Dodds; Scott R. Johnston; Shauna Kravec; Timothy Maxwell; et al. (CoRR, 2023)

Towards Understanding Sycophancy in Language Models. - Mrinank Sharma; Meg Tong; Tomasz Korbak; David Duvenaud; Amanda Askell; Samuel R. Bowman; Esin Durmus; Zac Hatfield-Dodds; Scott R. Johnston; Shauna Kravec; Timothy Maxwell; Sam McCandlish; et al. (ICLR, 2024)

Many-shot Jailbreaking. - Cem Anil; Esin Durmus; Nina Panickssery; Mrinank Sharma; Joe Benton; Sandipan Kundu; Joshua Batson; Meg Tong; Jesse Mu; Daniel Ford; Francesco Mosconi; Rajashree Agrawal; et al. (NeurIPS, 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)

When Do Universal Image Jailbreaks Transfer Between Vision-Language Models? - Rylan Schaeffer; Dan Valentine; Luke Bailey; James Chua; Cristóbal Eyzaguirre; Zane Durante; Joe Benton; Brando Miranda; Henry Sleight; John Hughes; Rajashree Agrawal; Mrinank Sharma; et al. (CoRR, 2024)

PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning. - Tingchen Fu; Mrinank Sharma; Philip Torr 001; Shay B. Cohen; David Krueger 001; Fazl Barez (CoRR, 2024)

Rapid Response: Mitigating LLM Jailbreaks with a Few Examples. - Alwin Peng; Julian Michael; Henry Sleight; Ethan Perez; Mrinank Sharma (CoRR, 2024)

Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach. - Tony T. Wang 001; John Hughes; Henry Sleight; Rylan Schaeffer; Rajashree Agrawal; Fazl Barez; Mrinank Sharma; Jesse Mu; Nir Shavit; Ethan Perez (CoRR, 2024)

Best-of-N Jailbreaking. - John Hughes; Sara Price; Aengus Lynch; Rylan Schaeffer; Fazl Barez; Sanmi Koyejo; Henry Sleight; Erik Jones; Ethan Perez; Mrinank Sharma (CoRR, 2024)

Incorporating Unlabelled Data into Bayesian Neural Networks. - Mrinank Sharma; Tom Rainforth; Yee Whye Teh; Vincent Fortuin (Trans. Mach. Learn. Res., 2024)

Failures to Find Transferable Image Jailbreaks Between Vision-Language Models. - Rylan Schaeffer; Dan Valentine; Luke Bailey; James Chua; Cristóbal Eyzaguirre; Zane Durante; Joe Benton; Brando Miranda; Henry Sleight; Tony Tong Wang; John Hughes; Rajashree Agrawal; et al. (ICLR, 2025)

Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats. - Jiaxin Wen; Vivek Hebbar; Caleb Larson; Aryan Bhatt; Ansh Radhakrishnan; Mrinank Sharma; Henry Sleight; Shi Feng 005; He He 001; Ethan Perez; Buck Shlegeris; Akbir Khan (ICLR, 2025)

Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming. - Mrinank Sharma; Meg Tong; Jesse Mu; Jerry Wei; Jorrit Kruthoff; Scott Goodfriend; Euan Ong; Alwin Peng; Raj Agarwal; Cem Anil; Amanda Askell; Nathan Bailey; et al. (CoRR, 2025)

Forecasting Rare Language Model Behaviors. - Erik Jones; Meg Tong; Jesse Mu; Mohammed Mahfoud; Jan Leike; Roger B. Grosse; Jared Kaplan; William Fithian; Ethan Perez; Mrinank Sharma (CoRR, 2025)