NeurIPS 2025: Training Untrainable Networks via Alignment
phillip_isola · x · 2026-08-26
MIT researchers propose 'Guidance' to train traditionally untrainable networks by using inductive biases from a guide network via representational alignment. It prevents FCN overfitting, narrows the RNN-Transformer gap, and boosts plain CNN accuracy.
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