DLoRA: Distributed Parameter-Efficient Fine-Tuning Solution for Large Language Model

2024/04/08 by Chao Gao, Gao, Chao, Sai Qian Zhang +1 · 2 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Parallel #Speech Recognition and Synthesis #Topic Modeling #and Cluster Computing (cs.DC)

paper · pdf · doi:10.48550/arxiv.2404.05182

openalex publication_date 2024/04/08 · openalex created_date 2024/04/11 · openalex updated_date 2026/07/28

Abstract

To enhance the performance of large language models (LLM) on downstream tasks, one solution is to fine-tune certain LLM parameters and make it better align with the characteristics of the training dataset. This process is commonly known as parameter-efficient fine-tuning (PEFT). Due to the scale of LLM, PEFT operations are usually executed in the public environment (e.g., cloud server). This necessitates the sharing of sensitive user data across public environments, thereby raising potential privacy concerns. To tackle these challenges, we propose a distributed PEFT framework called DLoRA. DLoRA enables scalable PEFT operations to be performed collaboratively between the cloud and user devices. Coupled with the proposed Kill and Revive algorithm, the evaluation results demonstrate that DLoRA can significantly reduce the computation and communication workload over the user devices while achieving superior accuracy and privacy protection.

Cited by

• Private LoRA Fine-tuning of Open-Source LLMs with Homomorphic Encryption
• UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces

Related

• FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models
• FedPT: Federated Proxy-Tuning of Large Language Models on Resource-Constrained Edge Devices
• DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models
• HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
• SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models