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

21 citations · 33 across the 8 of their papers we have counts for

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cs.AR2026

MonoMoE: An Efficient Fused Mega-kernel for Quantized MoE Decoding

Yu Gong, Kailash Budhathoki, Taeho Kim +2

Mixture-of-Experts (MoE) layers increase model capacity without proportionally increasing arithmetic, but their sparse expert computation is difficult to execute efficiently during…

cs.PF2026

KernelSight-LM: A Kernel-Level LLM Inference Simulator

Xiteng Yao, Taeho Kim, Hengzhi Pei +7

As large language models (LLMs) move into production serving, practitioners must rapidly evaluate inference performance across diverse hardware, models, and serving parameters to m…