MorphoQuant: Modality-Aware Quantization for Omni-modal Large Language Models 事件

MorphoQuant: Modality-Aware Quantization for Omni-modal Large Language Models arXiv:2606.04349v1 Announce Type: new Abstract: Conventional Post-Training Quantization (PTQ) methods struggle with 4-bit Omni-modal Large Language Models (OLLMs) due to the extreme distribution heterogeneity and disparate outlier patterns across modalities. To address this, we propose MorphoQuant, a modality-aware PTQ framework engineered to preserve cross-modal morphology and mitigate outlier loss. Specifically, we