Using two class labels in text prompts to generate synthetic calibration images improves data-free post-training quantization accuracy, especially in low-bit settings.
Scaling laws of synthetic images for model training
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Enhancing Generalization in Data-free Quantization via Mixup-class Prompting
Using two class labels in text prompts to generate synthetic calibration images improves data-free post-training quantization accuracy, especially in low-bit settings.