Abstract: The authors have recently proposed a paradigm that can potentially provide for considerably better interactivity compared to existing practices and can adapt immediately to interactive ...

Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...

[2025.09.25]: 🔥🔥🔥 We released a toolkit that tests the impact of numerical precision and enables deterministic LLM inference. This helps eliminate the training–inference mismatch in reinforcement ...

Abstract: Quantization is a critical technique employed across various research fields for compressing deep neural networks (DNNs) to facilitate deployment within resource-limited environments. This ...