Copertina

Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Lin, Zheng, Qu, Guanqiao, Chen, Qiyuan, Chen, Xianhao, Chen, Zhe, Huang, Kaibin
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Mobile Edge Intelligence for Large Language Models: A Contemporary Survey
di: Qu, Guanqiao, et al.
Pubblicazione: (2024)

Split Learning in 6G Edge Networks
di: Lin, Zheng, et al.
Pubblicazione: (2023)

TrimCaching: Parameter-sharing AI Model Caching in Wireless Edge Networks
di: Qu, Guanqiao, et al.
Pubblicazione: (2024)

AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks
di: Lin, Zheng, et al.
Pubblicazione: (2024)

PartialLoading: User Scheduling and Bandwidth Allocation for Parameter-sharing Edge Inference
di: Qu, Guanqiao, et al.
Pubblicazione: (2025)

Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models
di: Fang, Zihan, et al.
Pubblicazione: (2024)

HO-SFL: Hybrid-Order Split Federated Learning with Backprop-Free Clients and Dimension-Free Aggregation
di: Chen, Qiyuan, et al.
Pubblicazione: (2026)

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
di: Lin, Zheng, et al.
Pubblicazione: (2025)

HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
di: Lin, Zheng, et al.
Pubblicazione: (2025)

Collaborative Performance Prediction for Large Language Models
di: Zhang, Qiyuan, et al.
Pubblicazione: (2024)

VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
di: Wang, Haozhe, et al.
Pubblicazione: (2025)

SlimCaching: Edge Caching of Mixture-of-Experts for Distributed Inference
di: Chen, Qian, et al.
Pubblicazione: (2025)

Revisiting Outage for Edge Inference Systems
di: Wang, Zhanwei, et al.
Pubblicazione: (2025)

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities
di: Hao, Zhiwei, et al.
Pubblicazione: (2025)

FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks
di: Lin, Zheng, et al.
Pubblicazione: (2023)

PersRM-R1: Enhance Personalized Reward Modeling with Reinforcement Learning
di: Li, Mengdi, et al.
Pubblicazione: (2025)

Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities
di: He, Wenchong, et al.
Pubblicazione: (2023)

Cross-Table Pretraining towards a Universal Function Space for Heterogeneous Tabular Data
di: Chen, Jintai, et al.
Pubblicazione: (2024)

Aggregation Alignment for Federated Learning with Mixture-of-Experts under Data Heterogeneity
di: Fang, Zihan, et al.
Pubblicazione: (2026)

A Survey of Large Language Models for Data Challenges in Graphs
di: Li, Mengran, et al.
Pubblicazione: (2025)

FedMeld: A Model-dispersal Federated Learning Framework for Space-ground Integrated Networks
di: Chen, Qian, et al.
Pubblicazione: (2024)

Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing
di: Azimi-Abarghouyi, Seyed Mohammad, et al.
Pubblicazione: (2025)

Vision-Language Model Selection and Reuse for Downstream Adaptation
di: Tan, Hao-Zhe, et al.
Pubblicazione: (2025)

Harnessing Large Language Models for Mental Health: Opportunities, Challenges, and Ethical Considerations
di: Pandey, Hari Mohan
Pubblicazione: (2024)

TrimCaching: Parameter-sharing Edge Caching for AI Model Downloading
di: Qu, Guanqiao, et al.
Pubblicazione: (2024)

Enabling Near-realtime Remote Sensing via Satellite-Ground Collaboration of Large Vision-Language Models
di: Li, Zihan, et al.
Pubblicazione: (2025)

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation
di: Zhang, Yuxin, et al.
Pubblicazione: (2025)

DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach
di: Chen, Qin, et al.
Pubblicazione: (2025)

DPFNAS: Differential Privacy-Enhanced Federated Neural Architecture Search for 6G Edge Intelligence
di: Lv, Yang, et al.
Pubblicazione: (2025)

GPTQT: Quantize Large Language Models Twice to Push the Efficiency
di: Guo, Yipin, et al.
Pubblicazione: (2024)

SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework
di: Zhang, Yuxin, et al.
Pubblicazione: (2024)

Model-Distributed Inference for Large Language Models at the Edge
di: Macario, Davide, et al.
Pubblicazione: (2025)

Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks
di: Pan, Guangjin, et al.
Pubblicazione: (2025)

EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation
di: Zhang, Shu-Hao, et al.
Pubblicazione: (2026)

Channel-Adaptive Edge AI: Maximizing Inference Throughput by Adapting Computational Complexity to Channel States
di: Zhang, Jierui, et al.
Pubblicazione: (2026)

Activation Sparsity Opportunities for Compressing General Large Language Models
di: Dhar, Nobel, et al.
Pubblicazione: (2024)

Understanding Hardness of Vision-Language Compositionality from A Token-level Causal Lens
di: Chen, Ziliang, et al.
Pubblicazione: (2025)

ML For Hardware Design Interpretability: Challenges and Opportunities
di: Baartmans, Raymond, et al.
Pubblicazione: (2025)

Are Large Language Models In-Context Graph Learners?
di: Li, Jintang, et al.
Pubblicazione: (2025)

Foundation Models for CPS-IoT: Opportunities and Challenges
di: Baris, Ozan, et al.
Pubblicazione: (2025)