37 citations · 82 across the 8 of their papers we have counts for
Showing 2024Show all
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cs.AR2024★ 16 cited
LUT Tensor Core: A Software-Hardware Co-Design for LUT-Based Low-Bit LLM Inference
Zhiwen Mo, Lei Wang, Jianyu Wei +8
Large Language Model (LLM) inference becomes resource-intensive, prompting a shift toward low-bit model weights to reduce the memory footprint and improve efficiency. Such low-bit…
cs.DC2024★ 29 cited
T-MAC: CPU Renaissance via Table Lookup for Low-Bit LLM Deployment on Edge
Jianyu Wei, Shijie Cao, Ting Cao +4
The deployment of Large Language Models (LLMs) on edge devices is increasingly important to enhance on-device intelligence. Weight quantization is crucial for reducing the memory f…
cs.CL2024★ 37 cited
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Shuming Ma, Hongyu Wang, Lingxiao Ma +7
Recent research, such as BitNet, is paving the way for a new era of 1-bit Large Language Models (LLMs). In this work, we introduce a 1-bit LLM variant, namely BitNet b1.58, in whic…