Synthetic Scalable Oversight

We propose synthetic scalable oversight, a technique for studying scalable oversight by creating graphical abstractions of real-world problems and training tiny models inside these synthetic environments as a proxy for training LLMs at scale.We thank Oliver Richardson, Christian Szegedy, Michael Douglas, and countless others for the many conversations that inspired this work. Our code is available at https://github.com/stagiralabs/AgoraForge.Suppose you're a lab trying to train a system to perfo...