Search: “hardware”

Adaptive DNN Partitioning and Offloading in Heterogeneous Edge-Cloud Continuum

arXiv:2605.09623v1 Announce Type: cross Abstract: In recent years, the use of artificial intelligence on resource-constrained IoT devices has grown significantly. However, existing approaches to DNN p

researcharxiv-cs-ai

b9123

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b9123 is a release of llama.cpp created on May 12, 2026 . llama.cpp is an open source software library that performs inference on various large language models such as Llama , providing LLM inference

local-aillama-cpp-releases

12 May 2026

BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

arXiv:2605.10867v1 Announce Type: cross Abstract: Continuous authentication in high-stakes digital environments requires datasets with fine-grained behavioral signals under realistic cognitive and mot

Contextual Plackett-Luce: An Efficient Neural Model for Probabilistic Sequence Selection under Ambiguity

arXiv:2605.09112v1 Announce Type: cross Abstract: Selecting a coherent sequence or subset of elements is a fundamental problem in structured prediction, arising in tasks such as detection, trajectory

researcharxiv-cs-ai

Counterfactual Stress Testing for Image Classification Models

arXiv:2605.10894v1 Announce Type: new Abstract: Deep learning models in medical imaging often fail when deployed in new clinical environments due to distribution shifts in demographics, scanner hardwa

applicationsarxiv-cs-cv

cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport

arXiv:2605.08793v1 Announce Type: cross Abstract: Optimal transport (OT) has emerged as a fundamental tool in modern machine learning, yet its computational cost remains a significant bottleneck for l

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices

arXiv:2605.10933v1 Announce Type: cross Abstract: While Mixture-of-Experts (MoE) scales model capacity without proportionally increasing computation, its massive total parameter footprint creates sign

Dolphin-CN-Dialect: Where Chinese Dialects Matter

arXiv:2605.08961v1 Announce Type: new Abstract: We present Dolphin-CN-Dialect, a streaming-capable ASR model with a focus on Chinese and dialect-rich scenarios. Compared to the previous version, Dolph

applicationsarxiv-cs-cl

Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-Experts

arXiv:2509.21892v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models typically fix the number of activated experts k at both training and inference. However, real-world deployment

applicationsarxiv-cs-ai

enclawed: A Configurable, Sector-Neutral Hardening Framework for Single-User AI Assistant Gateways

arXiv:2604.16838v2 Announce Type: replace-cross Abstract: We present enclawed, a hard-fork hardening framework built on the OpenClaw AI assistant gateway. enclawed targets deployments that need attest

applicationsarxiv-cs-ai

End-to-End Keyword Spotting on FPGA Using Graph Neural Networks with a Neuromorphic Auditory Sensor

arXiv:2605.09570v1 Announce Type: new Abstract: With the rapid growth of mobile robotics and embedded intelligence, there is an increasing demand for efficient on-device data processing on edge platfo

local-aiarxiv-cs-lg

Energy-based models for diagnostic reconstruction and analysis in a laboratory plasma device

arXiv:2605.08645v1 Announce Type: cross Abstract: Energy-based models (EBMs) provide a powerful and flexible way of learning a joint probability distribution over data by constructing an energy surfac

EROAS: 3D Efficient Reactive Obstacle Avoidance System for Autonomous Underwater Vehicles using 2.5D Forward-Looking Sonar

arXiv:2411.05516v3 Announce Type: replace Abstract: Autonomous Underwater Vehicles (AUVs) have advanced significantly in obstacle detection and path planning through sonar, cameras, and learning-based

safetyarxiv-cs-ro

Finer is Better (with the Right Scaling)

arXiv:2605.08565v1 Announce Type: new Abstract: Microscaling is a critical technique for preserving the quality of Large Language Models (LLMs) quantized to ultra-low precision formats. Intuitively, f

FLARE: One-Shot PE-Level Fault Localization in Systolic Arrays via Algebraic Test Vectors

arXiv:2605.08594v1 Announce Type: cross Abstract: Systolic arrays are the dominant compute fabric for neural network inference. Prior work has addressed column-level fault detection efficiently with u

local-aiarxiv-cs-lg

Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling

arXiv:2512.02010v5 Announce Type: replace Abstract: As large language models have grown larger, interest has grown in low-precision numerical formats such as NVFP4 as a way to improve speed and reduce

Agents

Generalization Bounds of Emergent Communications for Agentic AI Networking

arXiv:2605.08613v1 Announce Type: new Abstract: The evolution of 6G networking toward agentic AI networking (AgentNet) systems requires a shift from traditional data pipelines to task-aware, agentic A

agentsarxiv-cs-ai

Tutorials

How to achieve truly serverless GPUs

This article explains how to implement and deploy GPU workloads in a truly serverless architecture, likely covering Modal's approach to abstracting away infrastructure management while providing GPU c

tutorialsmodal-blog

IMPACT: An Implicit Active-Set Augmented Lagrangian for Fast Contact-Implicit Trajectory Optimization

arXiv:2605.09127v1 Announce Type: new Abstract: Contact-implicit trajectory optimization (CITO) has attracted growing attention as a unified framework for planning and control in contact-rich robotic

Kaczmarz Linear Attention

arXiv:2605.08587v1 Announce Type: cross Abstract: Long-context language modeling remains central to modern sequence modeling, but the quadratic cost of Transformer attention makes scaling computationa

researcharxiv-cs-ai

Language Conditioned Multi-Finger Dexterous Manipulation Enabled by Physical Compliance and Switching of Controllers

arXiv:2410.14022v2 Announce Type: replace-cross Abstract: Human dexterity arises from combining high-level task reasoning with finger-level dexterity control and physical compliance at the muscle and

safetyarxiv-cs-ai

LiteMedCoT-VL: Parameter-Efficient Adaptation for Medical Visual Question Answering

arXiv:2605.09384v1 Announce Type: cross Abstract: The reasoning gap between large and compact vision-language models (VLMs) limits the deployment of medical AI on portable clinical devices. Compact VL

Locking Pretrained Weights via Deep Low-Rank Residual Distillation

model-releasesarxiv-cs-lg

arXiv:2605.10777v1 Announce Type: new Abstract: The quality of open-weight language models has dramatically improved in recent years. Sharing weights greatly facilitates model adoption by enabling the

Loom: Hybrid Retrieval-Scoring Outfit Recommendation with Semantic Material Compatibility and Occasion-Aware Embedding Priors

arXiv:2605.09830v1 Announce Type: cross Abstract: We present Loom, an outfit recommendation system that combines neural embedding retrieval with structured domain scoring to generate complete, coheren

researcharxiv-cs-cv

Tutorials

Markerless Head Tracking for Accurate and Accessible Neuronavigation

arXiv:2602.07052v2 Announce Type: replace Abstract: Neuronavigation is widely used in biomedical research and interventions to guide the precise placement of instruments around the head to support pro

tutorialsarxiv-cs-cv

MicroViTv2: Beyond the FLOPS for Edge Energy-Friendly Vision Transformers

arXiv:2605.10148v1 Announce Type: new Abstract: The Vision Transformer (ViT) achieves remarkable accuracy across visual tasks but remains computationally expensive for edge deployment. This paper pres

researcharxiv-cs-cv

MOBIUS: A Multi-Modal Bipedal Robot that can Walk, Crawl, Climb, and Roll

arXiv:2511.01774v3 Announce Type: replace Abstract: This paper presents the MOBIUS platform, a bipedal robot capable of walking, crawling, climbing, and rolling. MOBIUS features four limbs, two 6-DoF

Model-Free Neural Filtering: A Comparison with Classical Filters in Nonlinear Systems

model-releasesarxiv-cs-lg

arXiv:2601.21266v3 Announce Type: replace Abstract: Neural network models are increasingly used for state estimation in control and decision-making, yet it remains unclear to what extent they behave a

Morphology-Aware Graph Reinforcement Learning for Tensegrity Robot Locomotion

arXiv:2510.26067v2 Announce Type: replace Abstract: Tensegrity robots combine rigid rods and elastic cables, offering high resilience and deployability but at the same time posing major challenges for

safetyarxiv-cs-ro

Muninn: Your Trajectory Diffusion Model But Faster

arXiv:2605.09999v1 Announce Type: new Abstract: Diffusion-based trajectory planners can synthesize rich, multimodal robot motions, but their iterative denoising makes online planning and control prohi

safetyarxiv-cs-ro

On the Overscaling Curse of Parallel Thinking: System Efficacy Contradicts Sample Efficiency

arXiv:2601.21619v2 Announce Type: replace-cross Abstract: Parallel thinking improves LLM reasoning through multi-path sampling and aggregation. In standard evaluations, due to a lack of sample-specifi

applicationsarxiv-cs-ai

Optimizing Server Placement for Vertical Federated Learning in Dynamic Edge/Fog Networks

arXiv:2605.09813v1 Announce Type: cross Abstract: We investigate the control and optimization of vertical federated learning (VFL), a class of distributed machine learning (ML) methods in which edge/f

ORICF -- Open Robotics Inference and Control Framework

arXiv:2605.09656v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) have enabled effective perception and language models for robots, but their deployment remains computati

Parallel Multi-Circuit Quantum Feature Fusion in Hybrid Quantum-Classical Convolutional Neural Networks for Breast Tumor Classification

arXiv:2512.02066v2 Announce Type: replace-cross Abstract: Quantum machine learning has emerged as a promising approach to improve feature extraction and classification tasks in high-dimensional data d

PolarVSR: A Unified Framework and Benchmark for Continuous Space-Time Polarization Video Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.10275v1 Announce Type: new Abstract: Polarimetric imaging captures surface polarization characteristics, such as the Degree of Linear Polarization (DoLP) and the Angle of Polarization (AoP)

Position: AI Security Policy Should Target Systems, Not Models

arXiv:2605.09504v1 Announce Type: cross Abstract: We present swarm-attack, an open-source adversarial testing framework in which multiple lightweight LLM agents coordinate through shared memory, paral

PumpSense: Real-Time Detection and Target Extraction of Crypto Pump-and-Dumps on Telegram

arXiv:2605.09431v1 Announce Type: new Abstract: Cryptocurrency pump-and-dump schemes coordinated via Telegram threaten market integrity. However, existing research addressing this specific threat has

Reconfigurable Computing Challenge: Real-Time Graph Neural Networks for Online Event Selection in Big Science

arXiv:2605.10612v1 Announce Type: cross Abstract: Graph neural networks are increasingly adopted in trigger systems for collider experiments, where strict latency and throughput constraints render dep

Relative Kinetic Utility for Reasoning-Aware Structural Pruning in Large Language Models

arXiv:2605.09008v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) prompting symbolized a huge improvement of reasoning capabilities of Large Language Models (LLMs). However, scaling up test-tim

SAFA-SNN: Sparsity-Aware On-Device Few-Shot Class-Incremental Learning with Fast-Adaptive Structure of Spiking Neural Network

model-releasesarxiv-cs-lg

arXiv:2510.03648v2 Announce Type: replace Abstract: Continuous learning of novel classes is crucial for edge devices to preserve data privacy and maintain reliable performance in dynamic environments.

Seed Hijacking of LLM Sampling and Quantum Random Number Defense

arXiv:2605.08313v1 Announce Type: cross Abstract: Large language models (LLMs) rely on deterministic pseudorandom number generators (PRNGs) for autoregressive sampling, creating a critical supply-chai

TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling

arXiv:2605.09281v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models achieve remarkable performance by sparsely activating specialized experts, yet their massive parameters in experts pose

To Redact, or not to Redact? A Local LLM Approach to Deliberative Process Privilege Classification

arXiv:2605.10211v1 Announce Type: cross Abstract: Government transparency laws, like the Freedom of Information (FOIA) acts in the United States and United Kingdom, and the Woo (Open Government Act) i

Total Generalized Variation regularization closes the gap between neural-eld and classical methods in seismic travel-time tomography

arXiv:2605.09960v1 Announce Type: cross Abstract: Travel-time tomography forces a trade-off between mesh resolution and stability in which the regularizer choice dominates what can be recovered. We in

safetyarxiv-cs-lg

Towards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control

arXiv:2603.08588v2 Announce Type: replace-cross Abstract: State-of-the-art deep reinforcement learning (RL) methods have achieved remarkable performance in continuous control tasks, yet their computat

local-aiarxiv-cs-ai

VRA: Grounding Discrete-Time Joint Acceleration in Voltage-Constrained Actuation

arXiv:2605.10696v1 Announce Type: new Abstract: Discrete-time joint acceleration constraints are widely used to enforce position and velocity limits. However, under voltage-constrained electric actuat

Weight Pruning Amplifies Bias: A Multi-Method Study of Compressed LLMs for Edge AI

arXiv:2605.08137v1 Announce Type: cross Abstract: Weight pruning is widely advocated for deploying Large Language Models on resource-constrained IoT and edge devices, yet its impact on model fairness

When a Robot is More Capable than a Human: Learning from Constrained Demonstrators

arXiv:2510.09096v3 Announce Type: replace-cross Abstract: Learning from demonstrations enables experts to teach robots complex tasks using interfaces such as kinesthetic teaching, joystick control, an

safetyarxiv-cs-ai