Model collapse hasn't been completely solved, but a recent paper suggested a method to delay it.

The authors are transparent about the framework's current limitations. The primary challenge is catastrophic forgetting; as the model sequentially integrates new edits, its performance on earlier tasks degrades (Figure 6). While SEAL can perform multiple updates without a complete collapse, robustly preserving knowledge remains an open problem for this line of research.