most citedAgile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2024

Search for Efficient Large Language Models

Xuan Shen, Pu Zhao, Yifan Gong +7

Large Language Models (LLMs) have long held sway in the realms of artificial intelligence research. Numerous efficient techniques, including weight pruning, quantization, and disti…

cs.CV2024

Lotus: learning-based online thermal and latency variation management for two-stage detectors on edge devices

Yifan Gong, Yushu Wu, Zheng Zhan +5

Two-stage object detectors exhibit high accuracy and precise localization, especially for identifying small objects that are favorable for various edge applications. However, the h…

cs.CV2024

AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge

Chao Wu, Yifan Gong, Liangkai Liu +7

Object detection on the edge (Edge-OD) is in growing demand thanks to its ever-broad application prospects. However, the development of this field is rigorously restricted by the d…

cs.ET2024

SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits

Yanyue Xie, Peiyan Dong, Geng Yuan +10

Superconducting circuits, like Adiabatic Quantum-Flux-Parametron (AQFP), offer exceptional energy efficiency but face challenges in physical design due to sophisticated spacing and…

cs.LG2024

EdgeOL: Efficient in-situ Online Learning on Edge Devices

Sheng Li, Geng Yuan, Yue Dai +10

Emerging applications, such as robot-assisted eldercare and object recognition, generally employ deep learning neural networks (DNNs) and naturally require: i) handling streaming-i…

cs.LG2023★ 1 cited

Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge

Xuan Shen, Peiyan Dong, Lei Lu +5

Large Language Models (LLMs) stand out for their impressive performance in intricate language modeling tasks. However, their demanding computational and memory needs pose obstacles…