Search: “hardware”

Open-Set Vein Biometric Recognition with Deep Metric Learning

model-releasesarxiv-cs-cv

arXiv:2604.14874v1 Announce Type: new Abstract: Most state-of-the-art vein recognition methods rely on closed-set classification, which inherently limits their scalability and prevents the adaptive en

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Optimal algorithmic complexity of inference in quantum kernel methods

DGX agent

arXiv:2604.15214v1 Announce Type: cross Abstract: Quantum kernel methods are among the leading candidates for achieving quantum advantage in supervised learning. A key bottleneck is the cost of infere

tutorialsarxiv-cs-lg

17 Apr 2026

POP: Prefill-Only Pruning for Efficient Large Model Inference

model-releasesarxiv-cs-cl

arXiv:2602.03295v2 Announce Type: replace Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated remarkable capabilities. However, their deployment is hindered by s

Quantization of Spiking Neural Networks Beyond Accuracy

arXiv:2604.14487v1 Announce Type: new Abstract: Quantization is a natural complement to the sparse, event-driven computation of Spiking Neural Networks, reducing memory bandwidth and arithmetic cost f

SpaceMind: A Modular and Self-Evolving Embodied Vision-Language Agent Framework for Autonomous On-orbit Servicing

arXiv:2604.14399v1 Announce Type: new Abstract: Autonomous on-orbit servicing demands embodied agents that perceive through visual sensors, reason about 3D spatial situations, and execute multi-phase

agentsarxiv-cs-ro

Speak, Segment, Track, Navigate: An Interactive System for Video-Guided Skull-Base Surgery

model-releasesarxiv-cs-cv

arXiv:2603.16024v2 Announce Type: replace Abstract: We introduce a speech-guided embodied agent framework for video-guided skull base surgery that dynamically executes perception and image-guidance ta

A KL Lens on Quantization: Fast, Forward-Only Sensitivity for Mixed-Precision SSM-Transformer Models

arXiv:2604.13440v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) on edge devices faces severe computational and memory constraints, limiting real-time processing and on-device in

local-aiarxiv-cs-lg

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model

arXiv:2604.05672v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often c

researcharxiv-cs-ro

CollabCoder: Plan-Code Co-Evolution via Collaborative Decision-Making for Efficient Code Generation

model-releasesarxiv-cs-cl

arXiv:2604.13946v1 Announce Type: cross Abstract: Automated code generation remains a persistent challenge in software engineering, as conventional multi-agent frameworks are often constrained by stat

Dataset-Level Metrics Attenuate Non-Determinism: A Fine-Grained Non-Determinism Evaluation in Diffusion Language Models

arXiv:2604.13413v1 Announce Type: new Abstract: Diffusion language models (DLMs) have emerged as a promising paradigm for large language models (LLMs), yet the non-deterministic behavior of DLMs remai

DeEscalWild: A Real-World Benchmark for Automated De-Escalation Training with SLMs

model-releasesarxiv-cs-cl

arXiv:2604.13075v1 Announce Type: new Abstract: Effective de-escalation is critical for law enforcement safety and community trust, yet traditional training methods lack scalability and realism. While

Explainable Fall Detection for Elderly Care via Temporally Stable SHAP in Skeleton-Based Human Activity Recognition

arXiv:2604.13279v1 Announce Type: new Abstract: Fall detection in elderly care requires not only accurate classification but also reliable explanations that clinicians can trust. However, existing pos

local-aiarxiv-cs-cv

Safety

Failure Identification in Imitation Learning Via Statistical and Semantic Filtering

arXiv:2604.13788v1 Announce Type: cross Abstract: Imitation learning (IL) policies in robotics deliver strong performance in controlled settings but remain brittle in real-world deployments: rare even

safetyarxiv-cs-cv

Fast training of accurate physics-informed neural networks without gradient descent

arXiv:2405.20836v3 Announce Type: replace-cross Abstract: Solving time-dependent Partial Differential Equations (PDEs) is one of the most critical problems in computational science. While Physics-Info

Multi-Agent Object Detection Framework Based on Raspberry Pi YOLO Detector and Slack-Ollama Natural Language Interface

arXiv:2604.13345v1 Announce Type: new Abstract: The paper presents design and prototype implementation of an edge based object detection system within the new paradigm of AI agents orchestration. It g

local-aiarxiv-cs-cv

Neuromorphic Spiking Ring Attractor for Proprioceptive Joint-State Estimation

arXiv:2604.14021v1 Announce Type: new Abstract: Maintaining stable internal representations of continuous variables is fundamental for effective robotic control. Continuous attractor networks provide

researcharxiv-cs-ro

Optimization with SpotOptim

arXiv:2604.13672v1 Announce Type: new Abstract: The `spotoptim` package implements surrogate-model-based optimization of expensive black-box functions in Python. Building on two decades of Sequential

Parameter-efficient Quantum Multi-task Learning

arXiv:2604.13560v1 Announce Type: new Abstract: Multi-task learning (MTL) improves generalization and data efficiency by jointly learning related tasks through shared representations. In the widely us

Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors

arXiv:2604.13951v1 Announce Type: new Abstract: This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analy

The Spectrascapes Dataset: Street-view imagery beyond the visible captured using a mobile platform

arXiv:2604.13315v1 Announce Type: new Abstract: High-resolution data in spatial and temporal contexts is imperative for developing climate resilient cities. Current datasets for monitoring urban param

researcharxiv-cs-cv

Vectorizing Projection in Manifold-Constrained Motion Planning for Real-Time Whole-Body Control

arXiv:2604.13323v1 Announce Type: new Abstract: Many robot planning tasks require satisfaction of one or more constraints throughout the entire trajectory. For geometric constraints, manifold-constrai

applicationsarxiv-cs-ro

Vision-and-Language Navigation for UAVs: Progress, Challenges, and a Research Roadmap

arXiv:2604.13654v1 Announce Type: new Abstract: Vision-and-Language Navigation for Unmanned Aerial Vehicles (UAV-VLN) represents a pivotal challenge in embodied artificial intelligence, focused on ena

agentsarxiv-cs-ro

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI

arXiv:2603.18104v3 Announce Type: replace Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relat

researcharxiv-cs-ai

Classification of Epileptic iEEG using Topological Machine Learning

arXiv:2604.11971v1 Announce Type: new Abstract: Epileptic seizure detection from EEG signals remains challenging due to the high dimensionality and nonlinear, potentially stochastic, dynamics of neura

Safety

E2E-Fly: An Integrated Training-to-Deployment System for End-to-End Quadrotor Autonomy

arXiv:2604.12916v1 Announce Type: new Abstract: Training and transferring learning-based policies for quadrotors from simulation to reality remains challenging due to inefficient visual rendering, phy

safetyarxiv-cs-ro

Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects

arXiv:2604.05546v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) enable sophisticated reasoning over images and videos, yet their inference is hindered by a systemic efficiency

researcharxiv-cs-cl

On Efficient Variants of Segment Anything Model: A Survey

arXiv:2410.04960v5 Announce Type: replace Abstract: The Segment Anything Model (SAM) is a foundational model for image segmentation tasks, known for its strong generalization across diverse applicatio

applicationsarxiv-cs-cv

Ride the Wave: Precision-Allocated Sparse Attention for Smooth Video Generation

arXiv:2604.12219v1 Announce Type: cross Abstract: Video Diffusion Transformers have revolutionized high-fidelity video generation but suffer from the massive computational burden of self-attention. Wh

local-aiarxiv-cs-ai

RMGS-SLAM: Real-time Multi-sensor Gaussian Splatting SLAM

arXiv:2604.12942v1 Announce Type: new Abstract: Real-time 3D Gaussian splatting (3DGS)-based Simultaneous Localization and Mapping (SLAM) in large-scale real-world environments remains challenging, as

applicationsarxiv-cs-ro

TempoNet: Slack-Quantized Transformer-Guided Reinforcement Scheduler for Adaptive Deadline-Centric Real-Time Dispatchs

arXiv:2602.18109v2 Announce Type: replace Abstract: Real-time schedulers must reason about tight deadlines under strict compute budgets. We present TempoNet, a reinforcement learning scheduler that pa

local-aiarxiv-cs-lg

A collaborative agent with two lightweight synergistic models for autonomous crystal materials research

arXiv:2604.11540v1 Announce Type: new Abstract: Current large language models require hundreds of billions of parameters yet struggle with domain-specific reasoning and tool coordination in materials

agentsarxiv-cs-ai

CapBench: A Multi-PDK Dataset for Machine-Learning-Based Post-Layout Capacitance Extraction

arXiv:2604.11202v1 Announce Type: cross Abstract: We present CapBench, a fully reproducible, multi-PDK dataset for capacitance extraction. The dataset is derived from open-source designs, including si

Cooperation in Human and Machine Agents: Promise Theory Considerations

arXiv:2604.10505v1 Announce Type: new Abstract: Agent based systems are more common than we may think. A Promise Theory perspective on cooperation, in systems of human-machine agents, offers a unified

agentsarxiv-cs-ai

Domain-Aware Hybrid Quantum Learning via Correlation-Guided Circuit Design for Crime Pattern Analytics

arXiv:2604.07389v2 Announce Type: replace Abstract: Crime pattern analysis is critical for law enforcement and predictive policing, yet the surge in criminal activities from rapid urbanization creates

Duration-Informed Workload Scheduler

arXiv:2604.09599v1 Announce Type: cross Abstract: High-performance computing systems are complex machines whose behaviour is governed by the correct functioning of its many subsystems. Among these, th

researcharxiv-cs-ai

EDFNet: Early Fusion of Edge and Depth for Thin-Obstacle Segmentation in UAV Navigation

arXiv:2604.09694v1 Announce Type: new Abstract: Autonomous Unmanned Aerial Vehicles (UAVs) must reliably detect thin obstacles such as wires, poles, and branches to navigate safely in real-world envir

agentsarxiv-cs-cv

EdgeDAM: Real-time Object Tracking for Mobile Devices

model-releasesarxiv-cs-cv

arXiv:2603.05463v2 Announce Type: replace Abstract: Single-object tracking (SOT) on edge devices is a critical computer vision task, requiring accurate and continuous target localization across video

Efficient Matrix Implementation for Rotary Position Embedding

arXiv:2604.09742v1 Announce Type: cross Abstract: Rotary Position Embedding (RoPE) has become a core component of modern Transformer architectures across language, vision, and 3D domains. However, exi

researcharxiv-cs-cv

End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables

arXiv:2604.10117v1 Announce Type: new Abstract: Photoplethysmography (PPG)-based blood pressure (BP) estimation is a challenging task, particularly on resource-constrained wearable devices. However, f

Flow Gym: A framework for the development, benchmarking, training, and deployment of flow-field quantification methods

arXiv:2512.20642v2 Announce Type: replace-cross Abstract: Particle image velocimetry (PIV) and related optical-flow methods are widely used to quantify fluid motion, but their development and evaluati

researcharxiv-cs-cv

Frugal Knowledge Graph Construction with Local LLMs: A Zero-Shot Pipeline, Self-Consistency and Wisdom of Artificial Crowds

model-releasesarxiv-cs-ai

arXiv:2604.11104v1 Announce Type: new Abstract: This paper presents an empirical study of a multi-model zero-shot pipeline for knowledge graph construction and exploitation, executed entirely through

Graph-Coarsening Approach for the Capacitated Vehicle Routing Problem with Time Windows

arXiv:2510.22329v2 Announce Type: replace Abstract: The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is a fundamental NP-hard optimization problem in logistics. Solving large-scale i

researcharxiv-cs-ai

HearthNet: Edge Multi-Agent Orchestration for Smart Homes

model-releasesarxiv-cs-ai

arXiv:2604.09618v1 Announce Type: cross Abstract: Smart-home users increasingly want to control their homes in natural language rather than assemble rules, dashboards, and API integrations by hand. At

Lagrangian-based Equilibrium Propagation: generalisation to arbitrary boundary conditions & equivalence with Hamiltonian Echo Learning

arXiv:2506.06248v2 Announce Type: replace Abstract: Equilibrium Propagation (EP) is a learning algorithm for training Energy-based Models (EBMs) on static inputs which leverages the variational descri

Safety

MADQRL: Distributed Quantum Reinforcement Learning Framework for Multi-Agent Environments

arXiv:2604.11131v1 Announce Type: new Abstract: Reinforcement learning (RL) is one of the most practical ways to learn from real-life use-cases. Motivated from the cognitive methods used by humans mak

safetyarxiv-cs-ai

MeloTune: On-Device Arousal Learning and Peer-to-Peer Mood Coupling for Proactive Music Curation

arXiv:2604.10815v1 Announce Type: cross Abstract: MeloTune is an iPhone-deployed music agent that instantiates the Mesh Memory Protocol (MMP) and Symbolic-Vector Attention Fusion (SVAF) as a productio

local-aiarxiv-cs-ai

ML-Based Real-Time Downlink Performance Prediction in Standalone 5G NR Using Smartphones

arXiv:2604.09632v1 Announce Type: cross Abstract: We propose a machine learning (ML)-based framework for downlink performance prediction in 5G networks using real-time measurements from commercial off

applicationsarxiv-cs-lg

Natural Gradient Gaussian Approximation Filter on Lie Groups for Robot State Estimation

model-releasesarxiv-cs-ro

arXiv:2604.10057v1 Announce Type: new Abstract: Accurate state estimation for robotic systems evolving on Lie group manifolds, such as legged robots, is a prerequisite for achieving agile control. How