95 citations · 102 across the 6 of their papers we have counts for
3 papers · 1 filter
Safety by Measurement: A Systematic Literature Review of AI Safety Evaluation Methods
Markov Grey, Charbel-Raphaël Segerie
As frontier AI systems advance toward transformative capabilities, we need a parallel transformation in how we measure and evaluate these systems to ensure safety and inform govern…
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Stephen Casper, Xander Davies, Claudia Shi +29
Reinforcement learning from human feedback (RLHF) is a technique for training AI systems to align with human goals. RLHF has emerged as the central method used to finetune state-of…
Continuous Homeostatic Reinforcement Learning for Self-Regulated Autonomous Agents
Hugo Laurençon, Charbel-Raphaël Ségerie, Johann Lussange +1
Homeostasis is a prevalent process by which living beings maintain their internal milieu around optimal levels. Multiple lines of evidence suggest that living beings learn to act t…