Post Training Quantization Preprocessing Method of Convolutional Neural Network via Outlier Removal
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New C-PTQ method enhances multimodal LLM quantization efficiency
Researchers have developed C-PTQ, a novel post-training quantization method designed to improve the efficiency of multimodal large language models (MLLMs). This technique addresses performance degradation caused by outl…
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New ETBQ method boosts low-bit neural network quantization accuracy
Researchers have developed a new method called Efficient Tuning Before Quantization (ETBQ) to improve the accuracy of low-bit post-training quantization (PTQ) for deep neural networks. This technique involves a pre-cond…
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Google Releases Gemma 4 Models with Quantization-Aware Training
Google has released new checkpoints for its Gemma 4 family of models, utilizing Quantization-Aware Training (QAT). This method trains the models to be more accurate when their weights are compressed to very low bit-widt…