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Self-distillation is limited by requiring original training data. Prediction-only distillation changes this, allowing models to learn from teachers without needing the original labeled data. This could make model deployment easier in real-world scenarios where data is scarce or unavailable.
“arXiv:2607.15450v1 Announce Type: cross Abstract: Self-distillation (SD) is typically studied when the student is retrained on the teacher's original training inputs. In many practical deployments, however, the labeled training data are no …”
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ACTIVE
CATEGORY
Research
EVIDENCE
Not yet assessed
ENTITY
Self-Distillation, Linear Regression, Logistic Regression
DECISION
Automated · no editorial override
LAST OBSERVED
Aug 5, 2026