Tag: AI Model Compression
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Efficient Mixed-Precision Quantization for Mixture-of-Experts
Discover a novel mixed-precision quantization method for Mixture-of-Experts models that boosts accuracy and reduces inference costs with theoretical guaran...
Hybrid QUBO Optimization for Neural Network Pruning
Discover how Hybrid QUBO optimization improves neural network pruning by combining sensitivity metrics and dynamic search for better performance and effici...
3DTurboQuant: Training-Free Quantization for 3D Models
3DTurboQuant enables near-optimal, training-free quantization for 3D reconstruction models, boosting compression with minimal quality loss.
Efficient Neural Network Compression: Prune-Quantize-Distill Pipeline
Discover an ordered pipeline combining pruning, quantization, and distillation for efficient neural network compression with low latency and high accuracy.
SoLA: Efficient LLM Compression via Sparsity & Decomposition
Discover SoLA, a training-free method using soft activation sparsity and low-rank decomposition to compress large language models efficiently without perfo...