Edge ML

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7 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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  1. Towards a Cloud Fog Edge System for Smart Building

    Oct 1, 2026Christophe Cérin, Mamadou Sow, Frédéric AndrèsOn-Device TrainingEdge ML

    University Sorbonne Paris Nord LIPN, UMR CNRS 7030 INRIA DATAMOVE Paris/Grenoble, France · University Sorbonne Paris Nord LIPN, UMR CNRS 7030 Villetaneuse, France · National institute of Informatics 2 Chome-1-2 Hitotsubashi, Chiyoda City, Tokyo 101-8430, Japan

  2. EdgeCraft: Automated Model Crafting for Edge IoT

    Sep 28, 2026Genglin Wang, Kaiwei Liu, Liekang Zeng +4Edge ComputingInternet of Things

    Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China · School of Computer Science, Peking University, Beijing, China

  3. A packet-level digital hardware twin for commissioning megahertz diagnostic edge AI and plasma control system integration in tokamaks

    Sep 27, 2026Semin Joung, Abhilasha Dave, Luca Scomparin +6Edge InferenceDigital Twins

    Department of Nuclear Engineering and Engineering Physics, University of Wisconsin–Madison, Madison, WI, USA · SLAC National Accelerator Laboratory, Menlo Park, CA, USA

  4. A Rapid Pipeline for Training and Deploying ML Models on WeBe Band

    Sep 24, 2026Ehsan Kourkchi, Asmita Asmita, Houman Homayoun +1Tiny MLEdge ML

    Dep. of Electrical and Computer Engineering UC Davis, CA, USA. · dept. name of organization (of Aff.) Quandary Peak Research Los Angeles, CA, USA.

  5. Deep Learning-Based Detection of Electrical Faults and Power Quality Disturbances in Aerospace Power Systems

    Sep 9, 2026Ian C. Guzmán, Radu Babiceanu, Berker PeközTime Series ClassificationEdge ML

    Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA · Western Michigan University, Kalamazoo, MI 49008, USA

  6. The OCUDU dApp Platform: An Open Runtime and E3 Interface for Real-Time AI-RAN

    Sep 7, 2026Timothy O'Shea, Matthew Pennybacker, Andriy KharchenkoWireless CommunicationsOpen Radio Access Network

    DeepSig Inc., Arlington, VA, USA

  7. TASTE: Throughput-Aware Batch Size Tuning for On-Device Edge Learning

    Sep 7, 2026Avik Bhatnagar, Federico Nicolas Peccia, Oliver BringmannOn-Device TrainingEdge ML

    FZI Research Center for Information Technology, University of Tübingen Germany

  8. Network-Aware Forecasting on Wireless Access Points

    Sep 2, 2026Niloo Bahadori, Swadhin Pradhan, Peiman AminiEfficient Neural Network InferenceEdge Computing

    Cisco Systems

  9. Towards Stream Learning on Embedded Systems: Benchmarking the Memory Consumption of Stream Learning Methods

    Aug 31, 2026Sebastian Buschjäger, Nuwan Gunasekara, Heitor Murilo GomesEdge MLStreaming Algorithms

    Lamarr Institute, Dortmund, Germany · Lamarr Institute, Halmstad University, Sweden · Victoria University of Wellington, New Zealand

  10. MAUPITI: On-Device Prototype-Based Learning on a Smart Infrared Sensor

    Aug 7, 2026Beatrice Alessandra Motetti, Tanguy Dugas du Villard, Matteo Risso +7Prototype-Based ClassificationOn-Device Training

    Politecnico di Torino, Turin, Italy · STMicroelectronics, Cornaredo, Italy

  11. Graph Machine: Exploring Edge Mechanisms as an Inductive Bias

    Aug 7, 2026Lintai HouGraph Structure LearningNeural Algorithmic Reasoning

    Iter Labs

  12. Design-Time Optimization of Deep Neural Networks for Intermittent Learning on Microcontrollers

    Aug 4, 2026Jakob Schubert, Maximilian Kasper, Maximilian Linke +5On-Device TrainingEnergy-Efficient ML

    Fraunhofer Institute for Integrated Circuits IIS, Nürnberg, Germany · Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany · Ruhr University Bochum (RUB), Bochum, Germany +2

  13. Versatile On-device Adaptation at the Edge by Unifying Few-shot, Zero-shot, Continual, and In-context Learning

    Jul 31, 2026Douwe den Blanken, Martin Lefebvre, Charlotte FrenkelZero-Shot LearningOn-Device Training

    Microelectronics Department (EEMCS Faculty), Delft University of Technology, 2628 CD Delft, Netherlands

  14. OsteoCAD: A Human-in-the-Loop Cloud-Edge Framework for Bone Tumor Segmentation

    Jul 31, 2026Maximo Rodriguez-Herrero, Dante D. Sanchez-Gallegos, Heriberto Aguirre-Meneses +3Interactive Medical Image SegmentationMedical Image Segmentation

    Department of Computer Science University Carlos III of Madrid, Leganes, Spain · Instituto Nacional de Rehabilitacion “Luis Guillermo Ibarra Ibarra”, Mexico City, Mexico · Cinvestav Tamaulipas, Cd. Victoria, Mexico

  15. Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras

    Jul 30, 2026Edoardo Ragusa, Giovanni Paolo Canuti, Simone Lugani +2Hardware-Aware NASEdge ML

    DITEN, University of Genoa, Genova, Italy

  16. RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deployment

    Jul 29, 2026Hansi Karunarathna, Nirhoshan Sivaroopan, Chamara Madarasingha +2Human Activity RecognitionCost-Aware Inference

    University of Sydney, Australia · Curtin University, Australia · Colorado State University, USA

  17. Multi-primitive in-memory computing for Monte Carlo tree search

    Jul 24, 2026Tergel Molom-Ochir, Benjamin F. Morris, Yintao He +6Compute-in-MemoryEnergy-Efficient ML

    Department of Electrical and Computer Engineering, Duke University, Durham, 27708, NC, USA. · Hewlett Packard Labs, Milpitas, 95035, CA, USA.

  18. Hardware-Software Co-Design for Float16 On-Device Training on RISC-V Single-Core

    Jul 23, 2026Benjamin Hubinet, Pierre-Alain Moellic, Olivier Savry +2On-Device TrainingHardware-Software Co-Design

    CEA-Leti, Mines Saint-Etienne, Equipe Commune SAS, F-13541 Gardanne, France · Univ. Grenoble Alpes, CEA-Leti, F-38000 Grenoble, France · Mines Saint-Etienne, CEA-Leti, Centre CMP, Equipe commune SAS, F-13541 Gardanne, France

  19. Self-organizing Architecture of Receptron Units: a Hardware-Aware Framework for Edge Intelligence

    Jul 22, 2026Stefano Radice, Ludovico Casaccia, Riccaro Emanuele Beccalli +2Shallow Neural NetworksNeuromorphic Computing

    Department of Physics “Aldo Pontremoli” and CIMaINa University of Milano Milano, Italy

  20. Edge Intelligence in Civil Aviation: Paradigms, Techniques, and Applications

    Jul 22, 2026Wenbin Li, Zhongtian Liao, Bolin Liu +4Edge InferenceEdge Computing

    China Southern Digital Intelligence Technology (Guangdong) Co., Ltd. China Southern Airlines Co., Ltd. Guangzhou, China

  21. QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs

    Jul 21, 2026Victor Felipe Domingues Do Amaral, Pierre Demaj, Erwan Libessart +3On-Device TrainingZeroth-Order Optimization

    GeePs · STMicroelectronics, France · GeePs, CNRS, CentraleSup´elec, Universit´e Paris-Saclay, Sorbonne Universit´e, France

  22. Empowering On-Device Model Adaptation with an Edge AI Inference Accelerator

    Jul 20, 2026Mateusz Piechocki, Alessandro Capotondi, Marek KraftOn-Device TrainingEdge ML

    Poznan University of Technology, Institute of Robotics and Machine Intelligence, Poznan, Poland · University of Modena and Reggio Emilia, The High-Performance Real-Time Laboratory, Modena, Italy

  23. A Hardware-oriented Approach for Efficient Bayesian Inference Computation and Deployment

    Jul 20, 2026Nikola Pižurica, Matteo Risso, Nikola Milović +4GPU Kernel OptimizationBayesian Inference

    Computer Science Center, University of Montenegro · Fain Tech, Podgorica, Montenegro · Department of Control and Computer Engineering, Politecnico di Torino +2

  24. Towards Efficient Convolutional Neural Network for Embedded Hardware via Multi-Dimensional Pruning

    Jul 13, 2026Hao Kong, Di Liu, Xiangzhong Luo +5Efficient Neural Network InferenceConvolutional Neural Networks

    School of Computer Science and Engineering, Nanyang Technological University, Singapore · HP-NTU Digital Manufacturing Corporate Lab, Nanyang Technological University, Singapore · Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway. +1

  25. On-Device Adaptive Battery Power Prediction for Electric Vehicles

    Jul 10, 2026Avik Bhatnagar, Anton Paule, Tobias Schuermann +2On-Device TrainingContinual Test-Time Adaptation

    FZI Research Center for Information Technology, University of Tübingen Germany

  26. Federated Low-Rank Koopman Learning for Multivariate Time-Series Anomaly Detection in IoT Systems

    Jul 9, 2026Tung-Anh Nguyen, Van-Phuc Bui, Anh Tuyen Le +4Koopman Operator LearningEdge ML

    Faculty of Engineering and IT, University of Technology Sydney, Ultimo, NSW, 2007, Australia · Faculty of Information Technology, FPT University, Vietnam · School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Vietnam

  27. Low-Power License Plate Detection and Recognition on a RISC-V Multi-Core MCU-Based Vision System

    Jul 7, 2026Lorenzo Lamberti, Manuele Rusci, Marco Fariselli +2Energy-Efficient MLTiny ML

    Department of Electrical, Electronic and Information Engineering - University of Bologna, Italy · GreenWaves Technologies, Grenoble, France · Integrated System Laboratory - ETH Zurich, Switzerland

  28. Energy-Efficient GPU DVFS for Fine-Tuning of SLMs on Resource-constrained Embedded Devices

    Jul 7, 2026Jurn-Gyu Park, Sanzhar Zholdybayev, Aidar Amangeldi +1Fine-TuningEnergy-Efficient ML

    School of Engineering and Digital Sciences, Nazarbayev University, 010000 Astana, Kazakhstan

  29. Multi-Teacher Contrastive Distillation for Edge-Efficient Pathology Foundation Models

    Jul 6, 2026Tim Lenz, Maurice Heide, Marco Gustav +2Computational PathologyPathology Foundation Models

    EKFZ for Digital Health, TU Dresden, Dresden, Germany · Pathology, University of Augsburg, Augsburg, Germany · Bavarian Cancer Research Center (BZKF), Augsburg, Germany +3

  30. Cross-Domain Generalization Failure in Lightweight Intrusion Detection Models for IIoT Networks

    Jul 1, 2026MD Azizul Hakim, Md Shihab Uddin, Talha Ibne AnisIoT Intrusion DetectionNetwork Intrusion Detection

    Department of Computer Science and Technology, Bangladesh Sweden Polytechnic Institute Kaptai, Rangamati, Chittagong 4530, Bangladesh · Department of Electrical Engineering, Bangladesh Sweden Polytechnic Institute Kaptai, Rangamati, Chittagong 4530, Bangladesh

  31. CoVStream: Edge-Cloud Collaboration for Understanding of Long Video Streams

    Jun 22, 2026Xu Liu, Guikun Chen, Zihao Yan +2Streaming Video UnderstandingLong-Video Understanding

    The State Key Lab of Brain-Machine Intelligence, Zhejiang University · vivo Mobile Communication Co., Ltd., Shenzhen, China.

  32. From Handcrafted Features to Functional Edge Learning: Evolution of EEG Seizure Detection Frameworks

    Jun 20, 2026Sepideh Kheirollahi, Mohammad Rasoul RoshanshahElectroencephalographyEEG Seizure Detection

    School of Electrical and Computer Engineering College of Engineering, University of Tehran Tehran, Iran

  33. Efficient Neural Network Model Selection for Few-Class Application Datasets

    Jun 18, 2026Bryan Bo Cao, Abhinav Sharma, Lawrence O'Gorman +2Model SelectionClassification

    Department of Computer Science Stony Brook University Stony Brook, NY 11790, USA · Nokia Bell Labs Murray Hill, NJ 07974, USA

  34. Embedded Machine Learning for Microcontroller-Class Edge Devices: Data, Feature, Evaluation, and Deployment Pipelines

    Jun 16, 2026Mostafa DarvishiEfficient Neural Network InferenceKeyword Spotting

  35. An affordable hardware-aware neural architecture search for deploying convolutional neural networks on ultra-low-power computing platforms

    Jun 15, 2026Andrea Mattia Garavagno, Edoardo Ragusa, Antonio Frisoli +1Efficient Neural Network InferenceTiny ML

    Dept. of Electrical, Electronic, Telecommunications Engineering and Naval Architecture (DITEN), University of Genoa, Genoa, Italy · Department of Excellence in Robotics & AI and Institute of Mechanical Intelligence, Scuola Superiore Sant’Anna, 56127 Pisa, Italy

  36. Embedded Arena: Iterative Optimization via Hardware Feedback

    Jun 15, 2026Zhihan Zhang, Alexander Le Metzger, Jiuyang Lyu +10Large Language Model-Guided OptimizationTiny ML

    University of Washington · University of California San Diego · Northeastern University

  37. CogGuard: Cognitive and Operational Profiling for Proactive Warning in Edge Intelligent Services

    Jun 13, 2026Zhi Yao, Weihao Chen, Zhiqing Tang +4Fine-TuningUser Modeling

    Institute of Artificial Intelligence and Future Networks, Beijing Normal University, Zhuhai, China · Faculty of Arts and Science, Beijing Normal University, Zhuhai, China · School of Artificial Intelligence, Beijing Normal University, Beijing, China +2

  38. On-Device Neural Architecture Search

    Jun 12, 2026Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo +2Hardware-Aware NASEdge ML

    Department of Electrical, Electronic, Telecommunication Engineering and Naval Architecture, DITEN University of Genoa, Genoa 16145, Italy · Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, Piazza Martiri della Libert`a 33, Pisa 56127, Italy · Institute of Mechanical Intelligence, Scuola Superiore Sant’Anna, Ghezzano, 56010 Pisa, Italy +1

  39. Running hardware-aware neural architecture search on embedded devices under 512MB of RAM

    Jun 12, 2026Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo +1Hardware-Aware NASConvolutional Neural Networks

    Department of Electrical, Electronic, Telecommunication Engineering and Naval Architecture, DITEN University of Genoa, Genoa 16145, Italy · Department of Excellence in Robotics & AI, Institute of Mechanical Intelligence, Scuola Superiore Sant’Anna, Pisa 56127, Italy

  40. Reducing the Complexity of Deep Learning Models for EEG Analysis on Wearable Devices

    Jun 10, 2026Farough Shayeste Roodi, Parham Zilouchian Moghaddam, Mahdi Mohammadi-nasab +3ElectroencephalographyEEG Seizure Detection

    School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran · Intelligent Future Technologies (IFT), Mälardalen University, Väster˚as, Sweden · Department of Computer Systems, Tallinn University of Technology (TalTech), Tallinn, Estonia

  41. Privacy-Preserving Federated Autoencoder for ECG Anomaly Detection on Edge Devices

    Jun 10, 2026Kaan Arda Akyol, Jakub Kacper Szeląg, Aydin Abadi +9Electrocardiogram ClassificationReconstruction-Based Anomaly Detection

    School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom

  42. HydraCIL: Decoupled Class-Incremental Learning through Prototype-Guided Multi-Head Classifiers

    Jun 8, 2026Daniel Vila-Cruz, Laura Morán-Fernández, Verónica Bolón-CanedoClass-Incremental LearningEnergy-Efficient ML

    Universidade da Coruña CITIC A Coruña, Spain

  43. AlignFed: Alignment-Aware Asynchronous Federated Fine-Tuning for Large Language Models in Heterogeneous Edge Environments

    Jun 6, 2026Yan Wang, Ziyi Gao, Rui WangLLM Fine-TuningAsynchronous Federated Learning

    Department of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China

  44. Model Multiplicity for Adversarial Detection in Small Language Model Training on Edge Devices

    Jun 5, 2026Stefan Behfar, Richard MortierEdge MLFederated Learning

    Computer Lab, University of Cambridge, Cambridge, United Kingdom

  45. GenAutoML: An Agentic Framework for Dynamic Architecture Generation and Optimization in Time-Series Analysis

    Jun 4, 2026Oleeviya Babu Poikarayil, Cédric Schockaert, Abdulrahman Nahhas +3Efficient Neural Network InferenceLarge Language Model-Guided NAS

    Paul Wurth S.A., Luxembourg · Otto-von-Guericke University, Magdeburg, Germany · Technical University of Munich, Germany

  46. TinyML-Driven Cybersecurity for Autonomous Spacecraft: Latency-Accuracy Analysis for SPARTA RF and Cyber Threat Detection

    Jun 4, 2026Van Le, Trevor Tran, Tan LeAutonomous Cyber DefenseCybersecurity

    Virginia Tech, Blacksburg, VA 24061, USA · Hampton University, Hampton, VA 23669, USA

  47. An RRAM-based Hardware Implementation of a Radial Basis Function Neuron for Edge Classifiers

    Jun 2, 2026Georgios Papandroulidakis, Shady Agwa, Themis ProdromakisCompute-in-MemoryEdge ML

    Centre for Electronics Frontiers, Institute of Micro and Nano Systems, School of Engineering, The University of Edinburgh, EH9 3BF, UK.

  48. Toward a Modular Architecture for Embedded AI Agent Systems at the Edge

    Jun 1, 2026Marcus Rüb, Michael GerhardsAI Agent SafetyAI Agent Governance

    Foresthub.Ai Villingen, Germany · Deloitte Consulting DÜsseldorf, Germany

  49. ArrythML: An Autoencoder-Based TinyML Approach for On-Device Arrhythmia Detection on Resource-Constrained Embedded Systems

    Jun 1, 2026Nagarajan S, Kurian PolachanElectrocardiogram ClassificationReconstruction-Based Anomaly Detection

    International Institute of Information Technology, Bangalore, India

  50. What changes after deployment? A survey on On-device Learning in TinyML

    May 29, 2026Massimo Pavan, Luca Pezzarossa, Fabrizio Pittorino +2On-Device TrainingDistribution Shift

    Technical University of Denmark (DTU), Kongens Lyngby, Denmark · Politecnico di Milano, Milan, Italy

  51. Active Continual Learning with Metaplastic Binary Bayesian Neural Networks

    May 28, 2026Kellian Cottart, Théo Ballet, Djohan Bonnet +1Bayesian Neural NetworksBinary Neural Networks

    Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies, Palaiseau, France · Forschungszentrum Jülich, Germany

  52. Dot-Flik: A Scalable Edge AI Architecture for Distributed Insect Monitoring

    May 27, 2026Mattia Consani, Denisa-Andreea Constantinescu, Åse Håtveit +4Edge ComputingInternet of Things

    ´Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Lausanne, Switzerland · Massachusetts Institute of Technology (MIT), Cambridge, MA, USA

  53. StreamSplit: Continuous Audio Representation Learning via Uncertainty-Guided Adaptive Splitting

    May 26, 2026Minh K. Quan, Pubudu N. PathiranaContrastive LearningAudio Representation Learning

    School of Engineering, Deakin University Waurn Ponds, Australia

  54. FD-RAG: Federated Dual-System Retrieval-Augmented Generation

    May 22, 2026Tianhao Gao, Kai Yang, Yiyang LiRetrieval-Augmented GenerationMemory-Augmented Language Models

    School of Computer Science and Technology, Tongji University

  55. AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems

    May 20, 2026Penglin Dai, Zijie Zhou, Xincao Xu +3Efficient Neural Network InferenceHardware-Aware NAS

    School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, China · Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China · School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China

  56. FTerViT: Fully Ternary Vision Transformer

    May 20, 2026Szymon Ruciński, Pietro Bonazzi, Engin Türetken +3Ternary QuantizationVision Transformer

    CSEM, Neuchâtel, Switzerland · ETH Zürich, Zurich, Switzerland

  57. Embedded ConvNet Ensembles: A Lightweight Approach to Recognize Arabic Handwritten Characters

    May 18, 2026Mohsine El Khayati, Rachid Elouahbi, Abdelillah SemmaEfficient Neural Network InferenceEnsemble Learning

    Systems theory and informatics laboratory Moulay Ismail University of Meknes Meknes, Morocco · Laboratory of Computer Science and Applications Moulay Ismail University of Meknes Meknes, Morocco · Computer Science Dept. EST of Sidi Bennour Chouaib Doukkali University Eljadida, Morocco

  58. Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks

    May 18, 2026Alessio Caviglia, Filippo Marostica, Alessandro Savino +1On-Device TrainingEnergy-Efficient ML

    Control and Computer Engineering Department, Politecnico di Torino, Turin, Italy

  59. Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning

    May 17, 2026Vedant Waykole, Haroon R. LoneNon-IID Federated LearningEdge ML

    IISER Bhopal · India

  60. Sustainable Intelligence for the Wild: Democratizing Ecological Monitoring via Knowledge-Adaptive Edge Expert Agents

    May 15, 2026Jiaxing Li, Hao Fang, Chi Xu +5Knowledge RepresentationEdge ML

    Simon Fraser University, Vancouver, Canada · Wild Salmon Center, Portland, USA · Pacific Salmon Foundation, Vancouver, Canada +1