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Collaborative Inference

In collaborative inference, a single inference task is performed by multiple models distributed on two or more (typically resource-constrained IoT) devices

Papers

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Showing 51–68 of 68 papers

TitleStatusHype
Towards Intelligent Edge Sensing for ISCC Network: Joint Multi-Tier DNN Partitioning and Beamforming Design—0
Towards Receiver-Agnostic and Collaborative Radio Frequency Fingerprint Identification—0
Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models—0
Jupiter: Fast and Resource-Efficient Collaborative Inference of Generative LLMs on Edge Devices—0
Limited Communications Distributed Optimization via Deep Unfolded Distributed ADMM—0
MoE^2: Optimizing Collaborative Inference for Edge Large Language Models—0
PATROL: Privacy-Oriented Pruning for Collaborative Inference Against Model Inversion Attacks—0
PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information—0
DuetFace: Collaborative Privacy-Preserving Face Recognition via Channel Splitting in the Frequency DomainCode0
Architectural Vision for Quantum Computing in the Edge-Cloud ContinuumCode0
PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational AutoencodersCode0
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party SettingCode0
Dual Attention Networks for Multimodal Reasoning and MatchingCode0
Distributed Mixture-of-Agents for Edge Inference with Large Language ModelsCode0
Decentralized Low-Latency Collaborative Inference via Ensembles on the EdgeCode0
Private Collaborative Edge Inference via Over-the-Air ComputationCode0
CE-CoLLM: Efficient and Adaptive Large Language Models Through Cloud-Edge CollaborationCode0
Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference SystemsCode0
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