Scaling Model-Generated Distillation Data Can Make Latent Teacher Traits More Recoverable
Scaling model-generated data is usually viewed as improving distillation: more examples should increase coverage, reduce noise, and produce stronger students. We show a second effect: larger datasets can make subtle teacher-specific signals easier to detect in the trained student, even when examples are off-task and ne...