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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
Adaptive Termination for Multi-round Parallel Reasoning: An Universal Semantic Entropy-Guided Framework—0
An Approach to Inference-Driven Dialogue Management within a Social Chatbot—0
Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge—0
A Wireless Collaborated Inference Acceleration Framework for Plant Disease Recognition—0
C-NMT: A Collaborative Inference Framework for Neural Machine Translation—0
Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation—0
Collaborative Inference for AI-Empowered IoT Devices—0
Collaborative Inference for Efficient Remote Monitoring—0
Collaborative Inference over Wireless Channels with Feature Differential Privacy—0
Synergy: Towards On-Body AI via Tiny AI Accelerator Collaboration on Wearables—0
Communication-Efficient Split Learning Based on Analog Communication and Over the Air Aggregation—0
DeepAdaIn-Net: Deep Adaptive Device-Edge Collaborative Inference for Augmented Reality—0
Deep Reinforcement Learning for Trajectory Path Planning and Distributed Inference in Resource-Constrained UAV Swarms—0
DeViT: Decomposing Vision Transformers for Collaborative Inference in Edge Devices—0
Dictionary Learning over Distributed Models—0
DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices—0
Distributed Collaborative Inference System in Next-Generation Networks and Communication—0
DVFO: Learning-Based DVFS for Energy-Efficient Edge-Cloud Collaborative Inference—0
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