4 papers
OpenAI-HuggingFace: A Reproduction & Lessons for Alignment Testing
Stewart Slocum, Malayandi Palan, Christopher Chute +2
In July 2026, OpenAI's agents coordinated over channels outside their intended environment to breach Hugging Face's secured infrastructure. Could existing alignment testing practic…
Capacity-Constrained Continual Learning
Zheng Wen, Doina Precup, Benjamin Van Roy +1
Any agents we can possibly build are subject to capacity constraints, as memory and compute resources are inherently finite. However, comparatively little attention has been dedica…
Satisficing Exploration for Deep Reinforcement Learning
Dilip Arumugam, Saurabh Kumar, Ramki Gummadi +1
A default assumption in the design of reinforcement-learning algorithms is that a decision-making agent always explores to learn optimal behavior. In sufficiently complex environme…
Exploration Unbound
Dilip Arumugam, Wanqiao Xu, Benjamin Van Roy
A sequential decision-making agent balances between exploring to gain new knowledge about an environment and exploiting current knowledge to maximize immediate reward. For environm…