Predictable performance is suboptimal, and what it means for model routing
This work takes a model's self-confidence, the probability it assigns to its chosen answer, as a baseline and study how much a performance predictor can improve on it, and shows that any performance predictor that outperforms a model's self-confidence can be used to improve the model's loss.
Guan-Hua Zhang, Moritz Hardt
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