KL divergence correlates with benchmark scores over wide quantization ranges but loses all predictive power in the near-baseline silent zone because it tracks disagreement volume rather than direction.
Divergent Token Metrics: Measuring degradation to prune away LLM components -- and optimize quantization
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Displacement Is Not Direction: Evaluating Fidelity Metrics for Quantized LLM Deployment
KL divergence correlates with benchmark scores over wide quantization ranges but loses all predictive power in the near-baseline silent zone because it tracks disagreement volume rather than direction.