Beyond Reconstruction Loss in Post-Training Quantization: Balanced Fitting for Large Vision-Language Models
Post-training quantization (PTQ) enables efficient deployment of large vision-language models (LVLMs), but is typically calibrated on a small set while expected to generalize across diverse downstream tasks. Although recent PTQ methods for LVLMs incorporate sensitivity signals, they still minimize reconstruction loss w...
Min-Chan Kang, Kyeonghye Park, Seungyeon Sa et al.
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