Preprint
Aug 2026
Target-Aware Calibration Data Selection for Preserving Uncertainty in Quantized Language Models
DPQ is introduced, a lightweight pre-quantization recipe family that uses full-precision predictions to construct target-aligned calibration mixtures of high-doubt examples and generic anchors that better preserve broad multiple-choice QA behavior.
Zhen Yang, Sizai Hou, Kaiwen Zheng et al.
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