Split Knowledge Distillation for Large Models in IoT: Architecture, Challenges, and Solutions
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Zuguang, Wu, Wen, Wu, Shaohua, Lin, Qiaohua, Sun, Yaping, Wang, Hui |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Fast AI Model Partition for Split Learning over Edge Networks
by: Li, Zuguang, et al.
Published: (2025)
by: Li, Zuguang, et al.
Published: (2025)
Adaptive Split Learning over Energy-Constrained Wireless Edge Networks
by: Li, Zuguang, et al.
Published: (2024)
by: Li, Zuguang, et al.
Published: (2024)
Mobility-Aware Federated Learning: Multi-Armed Bandit Based Selection in Vehicular Network
by: Tu, Haoyu, et al.
Published: (2024)
by: Tu, Haoyu, et al.
Published: (2024)
Foundation Models for CPS-IoT: Opportunities and Challenges
by: Baris, Ozan, et al.
Published: (2025)
by: Baris, Ozan, et al.
Published: (2025)
Energy-Efficient Split Learning for Fine-Tuning Large Language Models in Edge Networks
by: Li, Zuguang, et al.
Published: (2024)
by: Li, Zuguang, et al.
Published: (2024)
Hetero-SplitEE: Split Learning of Neural Networks with Early Exits for Heterogeneous IoT Devices
by: Oda, Yuki, et al.
Published: (2025)
by: Oda, Yuki, et al.
Published: (2025)
Merino: Entropy-driven Design for Generative Language Models on IoT Devices
by: Zhao, Youpeng, et al.
Published: (2024)
by: Zhao, Youpeng, et al.
Published: (2024)
Generalizing Teacher Networks for Effective Knowledge Distillation Across Student Architectures
by: Binici, Kuluhan, et al.
Published: (2024)
by: Binici, Kuluhan, et al.
Published: (2024)
A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings
by: Lin, Xiachong, et al.
Published: (2024)
by: Lin, Xiachong, et al.
Published: (2024)
LLM-NEO: Parameter Efficient Knowledge Distillation for Large Language Models
by: Yang, Runming, et al.
Published: (2024)
by: Yang, Runming, et al.
Published: (2024)
DevPiolt: Operation Recommendation for IoT Devices at Xiaomi Home
by: Wang, Yuxiang, et al.
Published: (2025)
by: Wang, Yuxiang, et al.
Published: (2025)
Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation
by: Wu, Lirong, et al.
Published: (2024)
by: Wu, Lirong, et al.
Published: (2024)
Attention-based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices
by: Zhang, Lu, et al.
Published: (2025)
by: Zhang, Lu, et al.
Published: (2025)
Machine Unlearning: Solutions and Challenges
by: Xu, Jie, et al.
Published: (2023)
by: Xu, Jie, et al.
Published: (2023)
DistilCLIP-EEG: Enhancing Epileptic Seizure Detection Through Multi-modal Learning and Knowledge Distillation
by: Wang, Zexin, et al.
Published: (2025)
by: Wang, Zexin, et al.
Published: (2025)
Open Set Dandelion Network for IoT Intrusion Detection
by: Wu, Jiashu, et al.
Published: (2023)
by: Wu, Jiashu, et al.
Published: (2023)
DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
by: Han, Lixiang, et al.
Published: (2024)
by: Han, Lixiang, et al.
Published: (2024)
Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients
by: Chen, Shaoyuan, et al.
Published: (2024)
by: Chen, Shaoyuan, et al.
Published: (2024)
DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any Architecture
by: Xiang, Qianlong, et al.
Published: (2024)
by: Xiang, Qianlong, et al.
Published: (2024)
A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysis
by: Wei, Hui, et al.
Published: (2025)
by: Wei, Hui, et al.
Published: (2025)
Efficient Cross-Architecture Knowledge Transfer for Large-Scale Online User Response Prediction
by: Wu, Yucheng, et al.
Published: (2026)
by: Wu, Yucheng, et al.
Published: (2026)
Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection
by: Liu, Chen, et al.
Published: (2024)
by: Liu, Chen, et al.
Published: (2024)
Driving Intelligent IoT Monitoring and Control through Cloud Computing and Machine Learning
by: Li, Hanzhe, et al.
Published: (2024)
by: Li, Hanzhe, et al.
Published: (2024)
Recommending Pre-Trained Models for IoT Devices
by: Patil, Parth V., et al.
Published: (2024)
by: Patil, Parth V., et al.
Published: (2024)
MemCollab: Cross-Model Memory Collaboration via Contrastive Trajectory Distillation
by: Chang, Yurui, et al.
Published: (2026)
by: Chang, Yurui, et al.
Published: (2026)
A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions
by: Yu, Zhiyin, et al.
Published: (2026)
by: Yu, Zhiyin, et al.
Published: (2026)
ReasoningWeekly: A General Knowledge and Verbal Reasoning Challenge for Large Language Models
by: Wu, Zixuan, et al.
Published: (2025)
by: Wu, Zixuan, et al.
Published: (2025)
DyC-STG: Dynamic Causal Spatio-Temporal Graph Network for Real-time Data Credibility Analysis in IoT
by: Cheng, Guanjie, et al.
Published: (2025)
by: Cheng, Guanjie, et al.
Published: (2025)
Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems
by: Banerjee, Sourasekhar, et al.
Published: (2026)
by: Banerjee, Sourasekhar, et al.
Published: (2026)
TinyML-Enabled IoT for Sustainable Precision Irrigation
by: Taueatsoala, Kamogelo, et al.
Published: (2026)
by: Taueatsoala, Kamogelo, et al.
Published: (2026)
(DEMO) Deep Reinforcement Learning Based Resource Allocation in Distributed IoT Systems
by: Li, Aohan, et al.
Published: (2025)
by: Li, Aohan, et al.
Published: (2025)
Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models
by: Li, Quan, et al.
Published: (2024)
by: Li, Quan, et al.
Published: (2024)
Delta Knowledge Distillation for Large Language Models
by: Cao, Yihan, et al.
Published: (2025)
by: Cao, Yihan, et al.
Published: (2025)
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
by: Kimura, Tomoyoshi, et al.
Published: (2026)
by: Kimura, Tomoyoshi, et al.
Published: (2026)
FedCCA: Client-Centric Adaptation against Data Heterogeneity in Federated Learning on IoT Devices
by: Wang, Kaile, et al.
Published: (2026)
by: Wang, Kaile, et al.
Published: (2026)
Peak-Controlled Logits Poisoning Attack in Federated Distillation
by: Tang, Yuhan, et al.
Published: (2024)
by: Tang, Yuhan, et al.
Published: (2024)
Joint Link Adaptation and Device Scheduling Approach for URLLC Industrial IoT Network: A DRL-based Method with Bayesian Optimization
by: Gao, Wei, et al.
Published: (2025)
by: Gao, Wei, et al.
Published: (2025)
IoT Malware Network Traffic Detection using Deep Learning and GraphSAGE Models
by: Prajapati, Nikesh, et al.
Published: (2025)
by: Prajapati, Nikesh, et al.
Published: (2025)
Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation
by: Wu, Yecheng, et al.
Published: (2026)
by: Wu, Yecheng, et al.
Published: (2026)
LCD: Advancing Extreme Low-Bit Clustering for Large Language Models via Knowledge Distillation
by: Liu, Fangxin, et al.
Published: (2025)
by: Liu, Fangxin, et al.
Published: (2025)
Similar Items
-
Fast AI Model Partition for Split Learning over Edge Networks
by: Li, Zuguang, et al.
Published: (2025) -
Adaptive Split Learning over Energy-Constrained Wireless Edge Networks
by: Li, Zuguang, et al.
Published: (2024) -
Mobility-Aware Federated Learning: Multi-Armed Bandit Based Selection in Vehicular Network
by: Tu, Haoyu, et al.
Published: (2024) -
Foundation Models for CPS-IoT: Opportunities and Challenges
by: Baris, Ozan, et al.
Published: (2025) -
Energy-Efficient Split Learning for Fine-Tuning Large Language Models in Edge Networks
by: Li, Zuguang, et al.
Published: (2024)