Papers Collaborative Inference
“Collaborative Inference” 태그가 달린 논문 68편 · 필터 해제
Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models
Stable Diffusion Models (SDMs) have shown remarkable proficiency in image synthesis. However, their broad application is impeded by their large model sizes and intensive computational requirements, which typically requir…
Collaborative InferenceDiversityImage GenerationPrivate Collaborative Edge Inference via Over-the-Air Computation
We consider collaborative inference at the wireless edge, where each client's model is trained independently on its local dataset. Clients are queried in parallel to make an accurate decision collaboratively. In addition…
Collaborative InferenceGlobal-Local Collaborative Inference with LLM for Lidar-Based Open-Vocabulary Detection
Open-Vocabulary Detection (OVD) is the task of detecting all interesting objects in a given scene without predefined object classes. Extensive work has been done to deal with the OVD for 2D RGB images, but the exploratio…
Collaborative InferenceLanguage ModellingLarge Language ModelObject+1LiveMind: Low-latency Large Language Models with Simultaneous Inference
In this paper, we introduce LiveMind, a novel low-latency inference framework for large language model (LLM) inference which enables LLMs to perform inferences with incomplete user input. By reallocating computational pr…
Collaborative InferenceLanguage ModelingLanguage ModellingLarge Language Model+1Galaxy: A Resource-Efficient Collaborative Edge AI System for In-situ Transformer Inference
Transformer-based models have unlocked a plethora of powerful intelligent applications at the edge, such as voice assistant in smart home. Traditional deployment approaches offload the inference workloads to the remote c…
Collaborative InferenceFederated Learning for Collaborative Inference Systems: The Case of Early Exit Networks
As Internet of Things (IoT) technology advances, end devices like sensors and smartphones are progressively equipped with AI models tailored to their local memory and computational constraints. Local inference reduces co…
Collaborative InferenceFederated LearningGSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration
Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of medicine, while GFMs exhibit superior gen…
Collaborative InferenceIn-Context LearningInstruction FollowingMedical Diagnosis+5Attention-aware Semantic Communications for Collaborative Inference
We propose a communication-efficient collaborative inference framework in the domain of edge inference, focusing on the efficient use of vision transformer (ViT) models. The partitioning strategy of conventional collabor…
Collaborative InferenceEmergency Computing: An Adaptive Collaborative Inference Method Based on Hierarchical Reinforcement Learning
In achieving effective emergency response, the timely acquisition of environmental information, seamless command data transmission, and prompt decision-making are crucial. This necessitates the establishment of a resilie…
Collaborative InferenceDecision MakingHierarchical Reinforcement LearningEnsembler: Protect Collaborative Inference Privacy from Model Inversion Attack via Selective Ensemble
For collaborative inference through a cloud computing platform, it is sometimes essential for the client to shield its sensitive information from the cloud provider. In this paper, we introduce Ensembler, an extensible f…
Cloud ComputingCollaborative InferenceTowards Efficient Object Re-Identification with A Novel Cloud-Edge Collaborative Framework
Object re-identification (ReID) is committed to searching for objects of the same identity across cameras, and its real-world deployment is gradually increasing. Current ReID methods assume that the deployed system follo…
Collaborative InferenceObjectSynergy: Towards On-Body AI via Tiny AI Accelerator Collaboration on Wearables
The advent of tiny artificial intelligence (AI) accelerators enables AI to run at the extreme edge, offering reduced latency, lower power cost, and improved privacy. When integrated into wearable devices, these accelerat…
Collaborative InferenceAdaptive Early Exiting for Collaborative Inference over Noisy Wireless Channels
Collaborative inference systems are one of the emerging solutions for deploying deep neural networks (DNNs) at the wireless network edge. Their main idea is to divide a DNN into two parts, where the first is shallow enou…
Collaborative Inferenceimage-classificationImage ClassificationSemantics-Driven Cloud-Edge Collaborative Inference
With the proliferation of video data in smart city applications like intelligent transportation, efficient video analytics has become crucial but also challenging. This paper proposes a semantics-driven cloud-edge collab…
Collaborative InferenceLicense Plate RecognitionDeepAdaIn-Net: Deep Adaptive Device-Edge Collaborative Inference for Augmented Reality
The object inference for augmented reality (AR) requires a precise object localization within user's physical environment and the adaptability to dynamic communication conditions. Deep learning (DL) is advantageous in ca…
Collaborative InferenceFeature CompressionObjectObject LocalizationLimited Communications Distributed Optimization via Deep Unfolded Distributed ADMM
Distributed optimization is a fundamental framework for collaborative inference and decision making in decentralized multi-agent systems. The operation is modeled as the joint minimization of a shared objective which typ…
Collaborative InferenceDecision MakingDistributed OptimizationDeViT: Decomposing Vision Transformers for Collaborative Inference in Edge Devices
Recent years have witnessed the great success of vision transformer (ViT), which has achieved state-of-the-art performance on multiple computer vision benchmarks. However, ViT models suffer from vast amounts of parameter…
Collaborative InferenceGPUKnowledge DistillationRoulette: A Semantic Privacy-Preserving Device-Edge Collaborative Inference Framework for Deep Learning Classification Tasks
Deep learning classifiers are crucial in the age of artificial intelligence. The device-edge-based collaborative inference has been widely adopted as an efficient framework for promoting its applications in IoT and 5G/6G…
Collaborative InferencePrivacy PreservingTransfer LearningPATROL: Privacy-Oriented Pruning for Collaborative Inference Against Model Inversion Attacks
Collaborative inference has been a promising solution to enable resource-constrained edge devices to perform inference using state-of-the-art deep neural networks (DNNs). In collaborative inference, the edge device first…
Collaborative InferenceVehicle Re-IdentificationEnergy-efficient Wearable-to-Mobile Offload of ML Inference for PPG-based Heart-Rate Estimation
Modern smartwatches often include photoplethysmographic (PPG) sensors to measure heartbeats or blood pressure through complex algorithms that fuse PPG data with other signals. In this work, we propose a collaborative inf…
Collaborative InferenceHeart rate estimation