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A single Noise Sensitivity Exponent (NSE) dictates when learning becomes computationally intractable in high-dimensional single- and multi-index models.
Forget knowledge distillation: pre-training ColBERT from scratch on public data alone beats models distilled from stronger, closed-source single-vector baselines.
