most citedEDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2024★ 1 cited

EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

Zhongzhi Yu, Zheng Wang, Yuhan Li +6

Efficient adaption of large language models (LLMs) on edge devices is essential for applications requiring continuous and privacy-preserving adaptation and inference. However, exis…

cs.DB2023

LSketch: A Label-Enabled Graph Stream Sketch Toward Time-Sensitive Queries

Yiling Zeng, Chunyao Song, Yuhan Li +1

Graph streams represent data interactions in real applications. The mining of graph streams plays an important role in network security, social network analysis, and traffic contro…