Reference

Pruning

• Learning both Weights and Connections for Efficient Neural Networks

• Pruning Filters for Efficient ConvNets

• Pruning Convolutional Neural Networks for Resource Efficient Inference

• Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning

• SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot

• A Simple and Effective Pruning Approach for Large Language Models

Quantization

• Quantizing deep convolutional networks for efficient inference: A whitepaper

• Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

• AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

• Quantization Mimic: Towards Very Tiny CNN for Object Detection