most citedRobust Implementation of Retrieval-Augmented Generation on Edge-based Computing-in-Memory Architectures

1 citations · 1 across the 3 of their papers we have counts for

collaborators
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2024

NVCiM-PT: An NVCiM-assisted Prompt Tuning Framework for Edge LLMs

Ruiyang Qin, Pengyu Ren, Zheyu Yan +7

Large Language Models (LLMs) deployed on edge devices, known as edge LLMs, need to continuously fine-tune their model parameters from user-generated data under limited resource con…

cs.LG2024★ 1 cited

Robust Implementation of Retrieval-Augmented Generation on Edge-based Computing-in-Memory Architectures

Ruiyang Qin, Zheyu Yan, Dewen Zeng +8

Large Language Models (LLMs) deployed on edge devices learn through fine-tuning and updating a certain portion of their parameters. Although such learning methods can be optimized…