Imagen de Portada

Can LoRA Fusion Support Cross-Domain Tasks in Cloud-Edge Collaboration?

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang, Yatong, Wang, Fali, Gu, Naibin, Lin, Zheng, Liu, Zhengxiao, Yao, Dingyu, Zhang, Zhiwei, Shi, Jianxin, Wang, Weiping
Formato:	Preprint
Publicado:	2026
Materias:	Distributed, Parallel, and Cluster Computing Computation and Language
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads
por: Zuo, Jingwei, et al.
Publicado: (2026)

InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models
por: Chen, Hongyu, et al.
Publicado: (2026)

ServerlessLoRA: Minimizing Latency and Cost in Serverless Inference for LoRA-Based LLMs
por: Sui, Yifan, et al.
Publicado: (2025)

SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA
por: Liu, Jianmin, et al.
Publicado: (2025)

pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
por: Yi, Liping, et al.
Publicado: (2023)

Predictive-LoRA: A Proactive and Fragmentation-Aware Serverless Inference System for LLMs
por: Ni, Yinan, et al.
Publicado: (2025)

LoRA-C: Parameter-Efficient Fine-Tuning of Robust CNN for IoT Devices
por: Ding, Chuntao, et al.
Publicado: (2024)

S-LoRA: Serving Thousands of Concurrent LoRA Adapters
por: Sheng, Ying, et al.
Publicado: (2023)

TS-EoH: An Edge Server Task Scheduling Algorithm Based on Evolution of Heuristic
por: Yatong, Wang, et al.
Publicado: (2024)

Federated LoRA with Sparse Communication
por: Kuo, Kevin, et al.
Publicado: (2024)

CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference
por: Li, Suyi, et al.
Publicado: (2024)

FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning
por: QI, Jiaxing, et al.
Publicado: (2024)

LoRAFusion: Efficient LoRA Fine-Tuning for LLMs
por: Zhu, Zhanda, et al.
Publicado: (2025)

Stabilizing Decentralized Federated Fine-Tuning via Topology-Aware Alternating LoRA
por: Wang, Xiaoyu, et al.
Publicado: (2026)

Unlocking the Edge deployment and ondevice acceleration of multi-LoRA enabled one-for-all foundational LLM
por: Kodavanti, Sravanth, et al.
Publicado: (2026)

Co-LoRA: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients
por: Seo, Minhyuk, et al.
Publicado: (2025)

FedQuad: Adaptive Layer-wise LoRA Deployment and Activation Quantization for Federated Fine-Tuning
por: Li, Rukuo, et al.
Publicado: (2025)

ForkKV: Scaling Multi-LoRA Agent Serving via Copy-on-Write Disaggregated KV Cache
por: Wang, Shao, et al.
Publicado: (2026)

Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models
por: Cho, Yae Jee, et al.
Publicado: (2024)

A Pipelined Collaborative Speculative Decoding Framework for Efficient Edge-Cloud LLM Inference
por: Zhang, Yida, et al.
Publicado: (2026)

ML-ECS: A Collaborative Multimodal Learning Framework for Edge-Cloud Synergies
por: Liu, Yuze, et al.
Publicado: (2026)

LoRA-based Parameter-Efficient LLMs for Continuous Learning in Edge-based Malware Detection
por: Rondanini, Christian, et al.
Publicado: (2026)

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
por: Jhunjhunwala, Divyansh, et al.
Publicado: (2025)

Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA
por: Chen, Shuangyi, et al.
Publicado: (2024)

Improving LoRA in Privacy-preserving Federated Learning
por: Sun, Youbang, et al.
Publicado: (2024)

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning
por: Chen, Shuaijun, et al.
Publicado: (2024)

RBLA: Rank-Based-LoRA-Aggregation for Fine-tuning Heterogeneous Models in FLaaS
por: Chen, Shuaijun, et al.
Publicado: (2024)

EAT: QoS-Aware Edge-Collaborative AIGC Task Scheduling via Attention-Guided Diffusion Reinforcement Learning
por: Xu, Zhifei, et al.
Publicado: (2025)

JORA: JAX Tensor-Parallel LoRA Library for Retrieval Augmented Fine-Tuning
por: Tahir, Anique, et al.
Publicado: (2024)

Fed-pilot: Optimizing LoRA Allocation for Efficient Federated Fine-Tuning with Heterogeneous Clients
por: Zhang, Zikai, et al.
Publicado: (2024)

Propius: A Platform for Collaborative Machine Learning across the Edge and the Cloud
por: Ding, Eric
Publicado: (2025)

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
por: Li, Senyao, et al.
Publicado: (2025)

FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding
por: Li, Yuchen, et al.
Publicado: (2026)

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation
por: Zhang, Zikai, et al.
Publicado: (2025)

ECC-SNN: Cost-Effective Edge-Cloud Collaboration for Spiking Neural Networks
por: Yu, Di, et al.
Publicado: (2025)

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices
por: Shen, Zheyu, et al.
Publicado: (2025)

Harmonic Decomposition in Data Sketches
por: Wang, Dingyu
Publicado: (2024)

Bridge the Present and Future: A Cross-Layer Matching Game in Dynamic Cloud-Aided Mobile Edge Networks
por: Qi, Houyi, et al.
Publicado: (2023)

Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems
por: Jaiswal, Shashwat, et al.
Publicado: (2025)

Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
por: Brüel-Gabrielsson, Rickard, et al.
Publicado: (2024)