12 citations · 19 across the 8 of their papers we have counts for
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cs.AR2025
On-Device Qwen2.5: Efficient LLM Inference with Model Compression and Hardware Acceleration
Maoyang Xiang, Ramesh Fernando, Bo Wang
Transformer-based Large Language Models (LLMs) have significantly advanced AI capabilities but pose considerable challenges for deployment on edge devices due to high computational…
cs.AR2024★ 3 cited
Digital ASIC Design with Ongoing LLMs: Strategies and Prospects
Maoyang Xiang, Emil Goh, T. Hui Teo
The escalating complexity of modern digital systems has imposed significant challenges on integrated circuit (IC) design, necessitating tools that can simplify the IC design flow.…
cs.AR2024
From English to ASIC: Hardware Implementation with Large Language Model
Emil Goh, Maoyang Xiang, I-Chyn Wey +1
In the realm of ASIC engineering, the landscape has been significantly reshaped by the rapid development of LLM, paralleled by an increase in the complexity of modern digital circu…