Energy-Efficient

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RISC-V and machine learning: a survey
Sep 17, 2026Shriman Keshri, Apparna Singh, Chinmaya Kumar Palo +2Risc-V Machine Learning
Energy-Regularized Imitation Learning for Force- and Work-Aware Robotic Manipulation
Sep 16, 2026Toshiki Otani, Hiromu Taketsugu, Norimichi UkitaRobotic Manipulation Policies Generalizable Robotic Manipulations
Learning to Exploit Passive Dynamics for Energy-Efficient Target Hopping of a Spring-Legged Quadcopter
Sep 14, 2026Ruigang Chen, Qi Zhang, Zhicheng Zhong +3Quadrotor Control Actuator
Tuning ROS 2 for Energy-Efficient Navigation: Empirical Insights from Costmap 2D Configurations
Sep 14, 2026Michel Albonico, Andreas Wortmann, Ivano MalavoltaSocial Robot Navigation Robot Operating System
Very Exciting: Zero-Shot Model Predictive Control of Buildings via Excitation-Based Generalized Transfer Learning Models
Sep 11, 2026Fabian Raisch, Felix Koch, Zack Xuereb Conti +2Model Predictive Control Transfer Learning
A Peer-Relative Representation Learning Framework for Energy Inefficiency Identification in Mobile Network Sites
Sep 3, 2026Eliud Nyakweba Koto, Jaco du Toit, Adham Stoltz +1Energy-Efficient Mobile Networks
Artificial Intelligence for Energy Optimization in Data Centers
Sep 3, 2026Mohammed Basharath Ullah, Summaiya Unnisa Begum, Mohammed Nadeem UllahArtificial Intelligence Data Centers Energy Resources
Multi-Level Modeling of Large Language Model Inference Latency and Energy via Hybrid Analytical--Machine-Learning Predictors
Aug 7, 2026Saeid Shokoufa, Mohammad Erfan Sadeghi, Mehdi Kamal +1LLM Inference Efficiency Nvidia Nemotron
The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing
Jul 27, 2026Stefan Scholze, Johannes Partzsch, Sebastian Höppner +27Neuromorphic Hardware Chip Design
ML-based Predictive Models for Power Consumption in Virtualised O-RANs
Jul 27, 2026Rishu Raj, Genevieve Akude, Urooj Tariq +1Open Radio Access Networks Energy-Efficient
Toward Energy-Efficient and Low-Power Arrhythmia Detection for Wearable Devices
Jul 16, 2026Floriaan Bulten, Yawar Rasheed, Arlene John +2Atrial Fibrillation Wearable Devices
Beyond the Need for Speed: Energy-Aware Code Generation via Simulation-Guided Reinforcement Learning
Jul 6, 2026Saurabhsingh Rajput, Tushar SharmaEnergy-Efficient Code Generation
SpikeLogBERT: Energy-Efficient Log Parsing Using Spiking Transformer Networks
Jun 30, 2026Thuan Bui, Duong Do, Tung Vu +2Energy-Efficient Binary Spikes
Energy-Optimal Spatial Iterative Learning within a Virtual Tube
Jun 30, 2026Chen Min, Shuli Lv, Pengda Mao +3Unmanned Aerial Vehicle Trajectories Trajectory Optimization
Neuromorphic Energy-Aware Learning for Adaptive Deep Brain Stimulation
Jun 26, 2026Binh Nguyen, Colleen Josephson, Mircea Teodorescu +2Neuromorphic Hardware Energy-Efficient
MambaRaw: Selective State Space Modeling for Efficient 4K Raw Image Reconstruction
Jun 23, 2026Peize Li, Fanhu Zeng, Tongda Xu +5Image Reconstruction Medmamba
Energy-efficient codon optimization on thermodynamic hardware
Jun 15, 2026Andraz Jelincic, Ross C. WalkerThermodynamics Energy-Efficient
From Compression to Deployment: Real-Time and Energy-Efficient FastGRNN on Ultra-Constrained Microcontrollers
Jun 15, 2026Emre Can KizilatesCortex Energy-Efficient
ReSCom: A Reconfigurable Spiking Neural Network Accelerator Using Stochastic Computing
Jun 11, 2026Ali Alipour Fereidani, Mohammad Rasoul Roshanshah, Saeed SafariSpiking Neural Networks Neuromorphic Hardware
SpikeDecoder: Realizing the GPT Architecture with Spiking Neural Networks
Jun 10, 2026Claas Beger, Florian Walter, Alois KnollSpiking Neural Networks Transformer Encoder
From Perception to Action: Can UI Interventions Foster Sustainable LLM Chatbot
Jun 9, 2026Nitish Patkar, Pooja Rani, Jack Glässer +2Chatbots Interaction Design
GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators
Jun 6, 2026Jason Sulskis, Sathya RaviFourier Neural Operators Neural Operators
Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks
May 31, 2026Marwan Dhuheir, Thang X. Vu, Symeon ChatzinotasOpen Radio Access Networks Mobile Networks
Adaptive PD Gains for Energy-Conscious Control in Physical Human-Robot Interaction
May 30, 2026Danyal Saqib, Francisco Andrade Chavez, Marie CharbonneauAdaptive Controller Actuator
Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly Detection
May 29, 2026Yilin Liu, Hongchao Zhang, Taylor T. Johnson +2Generalist Graph Anomaly Detection Anomaly
Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation
May 28, 2026Boyuan Zhang, Huanshan Huang, Yifei CaoOut-Of-Distribution Detection Dense Semantic Segmentation
PIRS: Physics-Informed Reward Shaping for SAC-Based Building Energy Management
May 27, 2026Shadmehr Zaregarizi, Khashayar YavariEnergy-Efficient Smart Homes
Scaling up Energy-Aware Multi-Agent Reinforcement Learning for Mission-Oriented Drone Networks with Individual Reward
May 24, 2026Changling Li, Ying LiMulti-Drone Coordination Multi-Agent Reinforcement Learning
GenAI for Energy-Efficient and Interference-Aware Compressed Sensing of GNSS Signals on a Google Edge TPU
May 14, 2026Thorben Wegner, Lucas Heublein, Tobias Feigl +3Jamming Attacks Global Navigation Satellite System
Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations
May 12, 2026Arthur Fyon, Julien Brandoit, Loris Mendolia +3Analog Recurrent Model
Energy-Efficient Implementation of Spiking Recurrent Cells on FPGA
May 11, 2026Pascal Harmeling, Florent De Geeter, Guillaume DrionSpiking Neural Networks Field-Programmable Gate Arrays
XiYOLO: Energy-Aware Object Detection via Iterative Architecture Search and Scaling
May 7, 2026Tony Tran, Richie R. Suganda, Bin HuYolo26 Heterogeneous Edge Devices
EULER-ADAS: Energy-Efficient & SIMD-Unified Logarithmic-Posit Engine for Precision-Reconfigurable Approximate ADAS Acceleration
May 7, 2026Mukul Lokhande, Ratko Pilipovic, Omkar Kokane +2Energy-Efficient Acceleration
A Scalable Digital Twin Framework for Energy Optimization in Data Centers
May 7, 2026Raphael Hendrigo de Souza Gonçalves, Wendel Marcos dos SantosArtificial Intelligence Data Centers Data Centers
Height Control and Optimal Torque Planning for Jumping With Wheeled-Bipedal Robots
May 5, 2026Yulun Zhuang, Yuan Xu, Binxin Huang +5Actuator Legged Robots
QAROO: AI-Driven Online Task Offloading for Energy-Efficient and Sustainable MEC Networks
Apr 28, 2026Yongtao Yao, Yao Yang, Haorui Shi +3Heterogeneous Edge Devices Edge Computing
Vision SmolMamba: Spike-Guided Token Pruning for Energy-Efficient Spiking State-Space Vision Models
Apr 28, 2026Dewei Bai, Hongxiang Peng, Yunyun Zeng +3Self-Supervised Vision Transformers Visual Token Pruning
LIPP: Load-Aware Informative Path Planning with Physical Sampling
Mar 6, 2026Hojune Kim, Guangyao Shi, Gaurav S. SukhatmeCoverage Path Planning Efficient Exploration
VoltanaLLM: Energy-Efficient and SLO-Aware Disaggregated LLM Serving via Adaptive Frequency Control and State-Space Routing
Sep 5, 2025Jiahuan Yu, Aryan Taneja, Junfeng Lin +1Large Language Model Serving Energy-Efficient
Energy-Efficient Real-Time 4-Stage Sleep Classification at 10-Second Resolution
Aug 6, 2025Zahra Mohammadi, Parnian Fazel, Siamak MohammadiSleep Stage Classification Electrocardiogram Classification
Enabling Energy-Efficient Simultaneous Multi-Task Reinforcement Learning through Spiking Neural Networks with Active Dendrites for Bio-inspired Generalist Agents
Dec 6, 2024Rachmad Vidya Wicaksana Putra, Avaneesh Devkota, Muhammad ShafiqueMulti-Task Reinforcement Learning Spiking Neural Networks

Sep 17, 2026 · cs.LGJ/K move · Enter open · S save

RISC-V and machine learning: a survey

Shriman Keshri, Apparna Singh, Chinmaya Kumar Palo, Shreya Adya+1

The intersection of open-source processor architectures and machine learning is driving the demand for customizable, efficient, and accessible hardware. This survey examines the state of the RISC-V ISA in machine learning applications, analyzing current capabilities, challenges, and future directions based on recent research. The analysis covers academic and commercial implementations, software frameworks, and real-world applications. The RISC-V machine learning ecosystem is evaluated, from instruction set extensions and core implementations to compiler optimizations and deployment strategies. Key contributions include a unified taxonomy of RISC-V ML implementations, a comparative analysis of performance and design trade-offs, an evaluation of software toolchain maturity, and the identification of emerging trends in instruction set extensions and specialized accelerators. Findings reveal progress in energy efficiency, specialized instruction development, and framework integration, while highlighting challenges in standardization, verification complexity, and ecosystem fragmentation. The analysis proposes four research directions to address current limitations: specialized neural processing extensions, adaptive and modular processor architectures, security frameworks, and energy-efficient multi-domain architectures. These directions provide a roadmap for advancing RISC-V as a foundational platform for next-generation machine learning systems.

Risc-V Machine Learning Neural Processing Units Code Optimization Energy-Efficient Survey

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