papersSEP 12 04:00 UTC
arXiv Paper Models Collapse When Multiple AI Systems Train on Each Other's Output
A new arXiv preprint examines how recursive training on AI-generated text leads to model collapse, extending prior work from a single model to settings where many models exchange and train on one another's outputs. The authors analyze how the dynamics play out across a multi-model ecosystem, where each participant learns from a shared pool of synthetic data. The work is a preprint and has not yet been peer reviewed.