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20222026
most citedQuantune: Post-training Quantization of Convolutional Neural Networks using Extreme Gradient Boosting for Fast Deployment

21 citations · 40 across the 11 of their papers we have counts for

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cs.AI2025

QuantuneV2: Compiler-Based Local Metric-Driven Mixed Precision Quantization for Practical Embedded AI Applications

Jeongseok Kim, Jemin Lee, Yongin Kwon +1

Mixed-precision quantization methods have been proposed to reduce model size while minimizing accuracy degradation. However, existing studies require retraining and do not consider…

cs.AI2024

LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs

Taeho Kim, Yanming Wang, Vatshank Chaturvedi +4

Fine-tuning pre-trained large language models (LLMs) with limited hardware presents challenges due to GPU memory constraints. Various distributed fine-tuning methods have been prop…