LobRA: Multi-tenant Fine-tuning over Heterogeneous Data

Summary: LobRA enables multi-tenant joint fine-tuning of LoRA adapters by tackling two data heterogeneities—sequence-length variation and skew—that hurt joint FT efficiency. It runs heterogeneous FT replicas (varying resource/parallel configs) plus a skew-aware dispatcher to balance per-step workloads, cutting GPU-seconds by ~45–60.7%. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13905
Venue: VLDB
Year: 2025
Pagerank: 4.1945683e-05
Overall Rank: 10,626 | 26.08%
DOI: 10.14778/3742728.3742752

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,089	Hydraulis: Balancing Large Transformer Model Training via Co-designing Parallel Strategies and Data Assignment	2026	SIGMOD	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
411	PyTorch Distributed: Experiences on Accelerating Data Parallel Training	2020	VLDB	0.00023906921
1,956	D-Bot: Database Diagnosis System using Large Language Models	2024	VLDB	9.960627e-05
2,352	MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud	2023	VLDB	8.9766205e-05
2,902	PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel	2023	VLDB	7.93939e-05
3,114	GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization	2024	VLDB	7.5451724e-05
5,720	BAGUA: Scaling up Distributed Learning with System Relaxations	2022	VLDB	5.3527734e-05
6,377	Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism	2023	VLDB	5.0911095e-05
7,536	Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent	2023	VLDB	4.7176331e-05
8,520	mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs	2025	VLDB	4.4937074e-05

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