Model Collapse Demystified: The Case of Regression Elvis Dohmatob Y unzhen Feng Julia Kempe FAIR, Meta Center for Data Science, New York University

The phenomenon of "model collapse" refers to the situation whereby as a model is trained recursively on data generated from previous generations of itself over time, its performance degrades until the model eventually becomes completely useless, i.e. the model collapses.