2 papers
cs.LG2026
Trainable Vector Quantization for Large Language Models
Anastasiia Prutianova, Alina Bogdanova, Mikhail Shutov +3
Vector Quantization (VQ) is a rapidly evolving technique for compressing Large Language Model (LLM) weights, reducing memory usage, and speeding up inference. However, extreme comp…
cs.LG2023
RepQ: Generalizing Quantization-Aware Training for Re-Parametrized Architectures
Anastasiia Prutianova, Alexey Zaytsev, Chung-Kuei Lee +2
Existing neural networks are memory-consuming and computationally intensive, making deploying them challenging in resource-constrained environments. However, there are various meth…