90 citations · 206 across the 39 of their papers we have counts for
3 papers · 1 filter
Exploiting Novel GPT-4 APIs
Kellin Pelrine, Mohammad Taufeeque, Michał Zając +2
Language model attacks typically assume one of two extreme threat models: full white-box access to model weights, or black-box access limited to a text generation API. However, rea…
STARC: A General Framework For Quantifying Differences Between Reward Functions
Joar Skalse, Lucy Farnik, Sumeet Ramesh Motwani +3
In order to solve a task using reinforcement learning, it is necessary to first formalise the goal of that task as a reward function. However, for many real-world tasks, it is very…
On The Fragility of Learned Reward Functions
Lev McKinney, Yawen Duan, David Krueger +1
Reward functions are notoriously difficult to specify, especially for tasks with complex goals. Reward learning approaches attempt to infer reward functions from human feedback and…