Edge Inference

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Overview

Edge inference studies how to run AI models close to where data is collected, often on devices with limited memory, power, and computing capacity. Common approaches include quantization, pruning and distillation, hardware-aware model and accelerator design, and adaptive methods such as early exits, model routing, and device-edge splitting. Work spans tasks from object detection and segmentation to language and multimodal models, with evaluation on benchmarks such as COCO and MVTec as well as phones, Raspberry Pi, Jetson, microcontrollers, and FPGAs. A central challenge is balancing accuracy, latency, energy, and robustness: proxy measures such as FLOPs may not predict real-device performance, which also varies with hardware, workload contention, and sustained operation.

Latest papers

CardsList

228 papers24 papers in the last four weeks, down 4% on the four weeks before. 0.1% of all new papers.

  1. EdgeFM: Efficient Edge Inference for Vision-Language Models

    Apr 30, 2026Mengling Deng, Yuanpeng Chen, Sheng Yang +12Efficient VLM InferenceEdge Inference

    Go Further. AI · School of Data Science, Fudan University · RUYi Dynamics Co., Ltd +1

  2. Edge AI for Automotive Vulnerable Road User Safety: Deployable Detection via Knowledge Distillation

    Apr 29, 2026Akshay Karjol, Darrin M. HannaEdge InferenceAutonomous Driving Perception

    Department of Electrical and Computer Engineering, Oakland University, Rochester, MI 48309 USA

  3. EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures

    Apr 29, 2026Gustav Olaf Yunus Laitinen-Fredriksson Lundstrom-Imanov, Taner YilmazEnergy-Efficient MLEdge Inference

    Department of Economics, Stockholm University, Universitetsvägen 10 A, SE-106 91 Stockholm, Sweden · Department of Computer Engineering, Afyon Kocatepe University, 03200 Afyonkarahisar, Türkiye

  4. DenseScout: Algorithm-System Co-design for Budgeted Tiny Object Selection on Edge Platforms

    Apr 28, 2026Xiong Zhouzhi, Zimo Zeng, Yi Chen +3Small Object DetectionEdge Inference

    College of Electrical Engineering, Zhejiang University, Hangzhou, China

  5. Characterizing Vision-Language-Action Models across XPUs: Constraints and Acceleration for On-Robot Deployment

    Apr 27, 2026Kaijun Zhou, Qiwei Chen, Da Peng +3AI Accelerator InferenceEdge Inference

    School of Computer Science, Shanghai Jiao Tong University

  6. Resource-Constrained UAV-Based Weed Detection for Site-Specific Management on Edge Devices

    Apr 25, 2026Linyuan Wang, Haibo Yao, Te-Ming Tseng +4Agricultural Remote SensingWeed Detection

    Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, USA · USDA-ARS, Genetics and Sustainable Agriculture Research Unit, Mississippi State, MS, USA · Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS, USA +2

  7. Depth-Aware Rover: A Study of Edge AI and Monocular Vision for Real-World Implementation

    Apr 24, 2026Lomash Relia, Jai G Singla, Amitabh +1Metric Depth EstimationRobot Navigation

    Department of Computer Engineering Devang Patel Institute of Advanced Technology and Research Anand, India · Space Applications Centre Indian Space Research Organization Ahmedabad, India

  8. IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0

    Apr 22, 2026Mohsen Asghari Ilani, Yaser Mike BanadEdge InferenceIndustrial Inspection

    School of Management, Swansea University, Swansea, United Kingdom · School of Electrical and Computer Engineering, University of Oklahoma, Norman, 73019, U.S.A.

  9. Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge

    Apr 21, 2026Zihao Ye, Yung-Hsiang Lu, Xiao Hu +14Edge InferenceMonocular Depth Estimation

    Purdue University, West Lafayette, IN, USA · Qualcomm, USA · Lehigh University, Bethlehem, PA, USA +3

  10. Edge AI Deployment Beyond Models: A BSP-Aware Systems Framework for Industrial Embedded Platforms

    Apr 20, 2026Pitchai Muthu MEdge InferenceEdge AI

    Embedded & IoT Software Team Lead Advantech Industrial Computing India Pvt. Ltd., India

  11. EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications

    Apr 18, 2026Seungjin Kim, Reza Jafarpourmarzouni, Christopher Neff +2Efficient Neural Network InferenceEdge Inference

    University of Wyoming · University of North Carolina at Charlotte · North Carolina A&T State University

  12. A Comparative Study of CNN Optimization Methods for Edge AI: Exploring the Role of Early Exits

    Apr 16, 2026Nekane Fernandez, Ivan Valdes, Steven Van Vaerenbergh +2Efficient InferenceEdge Inference

    Nekane Fernandez, Ivan Valdes, Idoia de la Iglesia and Julen Arratibel are with the Dept. of Connected and Distributed Intelligence, Ikerlan Technology Research Centre, Arrasate, Spain · Nekane Fernandez and Steven Van Vaerenbergh are with the Dept. of Mathematics, Statistics and Computation, Universidad de Cantabria, Santander, Spain

  13. [Emerging Ideas] Artificial Tripartite Intelligence: A Bio-Inspired, Sensor-First Architecture for Physical AI

    Apr 15, 2026You Rim Choi, Subeom Park, Hyung-Sin KimAdaptive SensingEmbodied AI

    Seoul National University, Seoul, South Korea

  14. SatReg: Regression-based Neural Architecture Search for Lightweight Satellite Image Segmentation

    Apr 11, 2026Edward Humes, Tinoosh MohseninHardware-Aware NASNeural Architecture Search

    Johns Hopkins University, Baltimore, Maryland, USA

  15. Taming Asynchronous CPU-GPU Coupling for Frequency-aware Latency Estimation on Mobile Edge

    Apr 11, 2026Jiesong Chen, Jun You, Zhidan Liu +1Edge InferenceEfficient Neural Network Inference

    Department of Computer Science, City University of Hong Kong, Hong Kong, China · INTR Thrust, System Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

  16. AsymLoc: Towards Asymmetric Feature Matching for Efficient Visual Localization

    Apr 10, 2026Mohammad Omama, Gabriele Berton, Eric Foxlin +1Visual Place RecognitionEdge Inference

    The University of Texas at Austin · Work done as a part of a summer internship at Amazon. · Amazon

  17. FaceLiVTv2: An Improved Hybrid Architecture for Efficient Mobile Face Recognition

    Apr 10, 2026Novendra Setyawan, Chi-Chia Sun, Mao-Hsiu Hsu +2Face RecognitionHybrid CNN-Transformer Architectures

    Department of Electro-Optics, National Formosa University, Taiwan · Department of Electrical Engineering University of Muhammadiyah Malang, Indonesia · Department of Electrical Engineering, National Taipei University, Taiwan +1

  18. Modality-Aware Zero-Shot Pruning and Sparse Attention for Efficient Multimodal Edge Inference

    Apr 10, 2026Yueyuan Sui, Payal Mohapatra, Doğaç Eldenk +5Efficient Multimodal InferenceNeural Network Pruning

    Northwestern University, Evanston, Illinois, USA

  19. VDPP: Video Depth Post-Processing for Speed and Scalability

    Apr 8, 2026Daewon Yoon, Injun Baek, Sangyu Han +2Video Depth EstimationDepth Estimation

    Seoul National University · Samsung Electronics

  20. Continual Visual Anomaly Detection on the Edge: Benchmark and Efficient Solutions

    Apr 7, 2026Manuel Barusco, Francesco Borsatti, David Petrovic +2Anomaly DetectionEdge Inference

    University of Padova, Italy

  21. FM-CAC: Carbon-Aware Control for Battery-Buffered Edge AI via Time-Series Foundation Models

    Apr 7, 2026Kang Yang, Walid A. Hanafy, Prashant Shenoy +1Carbon-Aware ComputingEnergy-Efficient ML

    University of California, Los Angeles Los Angeles, USA · University of Massachusetts Amherst Amherst, USA

  22. PCA-Driven Adaptive Sensor Triage for Edge AI Inference

    Apr 6, 2026Ankit Hemant Lade, Sai Krishna Jasti, Nikhil Sinha +2Adaptive SamplingStreaming Algorithms

    Independent Researchers

  23. TinyNina: A Resource-Efficient Edge-AI Framework for Sustainable Air Quality Monitoring via Intra-Image Satellite Super-Resolution

    Apr 6, 2026Prasanjit Dey, Zachary Yahn, Bianca Schoen-Phelan +1Autoregressive Image Super-ResolutionAir Quality Prediction

    ADAPT Research Centre, Dublin, Ireland · School of Computer Science, Technological University Dublin, Ireland · School of Computer Science, University College Dublin, Ireland +1

  24. L-SPINE: A Low-Precision SIMD Spiking Neural Compute Engine for Resource-efficient Edge Inference

    Apr 4, 2026Sonu Kumar, Mukul Lokhande, Santosh Kumar VishvakarmaEfficient Neural Network InferenceSpiking Neural Networks

    Centre for Advanced Electronics, Indian Institute of Technology Indore, Simrol 453552, Indore, India · Dept. of Electrical Engineering, Indian Institute of Technology Indore, Simrol 453552, Indore, India

  25. Light-ResKAN: A Parameter-Sharing Lightweight KAN with Gram Polynomials for Efficient SAR Image Recognition

    Apr 2, 2026Pan Yi, Weijie Li, Xiaodong Chen +3Parameter SharingKolmogorov-Arnold Networks

    The authors are with the College of Electronic Science and Technology, National University of Defense Technology, Changsha, 410073, China.

  26. Real-Time Sensing of Inaccessible Physical Fields via an Edge-Deployable Hardware-Portable Graph Neural Operator

    Apr 2, 2026William Howes, Jason Yoo, Kazuma Kobayashi +4Graph Neural OperatorsNeural Operators

    Grainger College of Engineering, Nuclear, Plasma & Radiological Engineering Department, University of Illinois Urbana-Champaign, Urbana, IL, USA · Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi · Department of Applied Mechanics, Indian Institute of Technology Delhi, New Delhi, India +1

  27. LiteInception: A Lightweight and Interpretable Deep Learning Framework for General Aviation Fault Diagnosis

    Apr 2, 2026Zhihuan Wei, Xinhang Chen, Danyang Han +4Fault DiagnosisEdge Inference

    Hangzhou International Innovation Institute, Beihang University, Hangzhou, China · School of Reliability and Systems Engineering, Beihang University, Beijing, China · Science and Technology on Complex Aviation System Simulation Laboratory, Beijing, China +1

  28. LLM-Generated Fault Scenarios for Evaluating Perception-Driven Lane Following in Autonomous Edge Systems

    Apr 1, 2026Faezeh Pasandideh, Achim RettbergAutonomous Driving Safety EvaluationAutonomous Driving

    Department of Electrical Engineering Hamm-Lippstadt University. of Applied Sciences (HSHL) Lippstadt, Germany

  29. Storing Less, Finding More: How Novelty Filtering Improves Cross-Modal Retrieval on Edge Cameras

    Mar 31, 2026Sherif AbdelwahabCross-Modal RetrievalVideo Frame Selection

  30. Edge-Based Standing-Water Detection via FSM-Guided Tiering and Multi-Model Consensus

    Mar 31, 2026Oliver Aleksander Larsen, Mahyar T. MoghaddamComputation OffloadingEdge Inference

    SDU – University of Southern Denmark, MMMI, Odense, Denmark