Search: “hardware”

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN

model-releasesarxiv-cs-ai

arXiv:2509.25612v2 Announce Type: replace-cross Abstract: Ensuring power grid resilience requires the timely and unsupervised detection of anomalies in synchrophasor data streams. We introduce T-BiGAN

14 Apr 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

WARPED: Wrist-Aligned Rendering for Robot Policy Learning from Egocentric Human Demonstrations

DGX agent

arXiv:2604.10809v1 Announce Type: new Abstract: Recent advancements in learning from human demonstration have shown promising results in addressing the scalability and high cost of data collection req

safetyarxiv-cs-ro

14 Apr 2026

An Algorithm for Fast Assembling Large-Scale Defect-Free Atom Arrays

arXiv:2604.08669v1 Announce Type: cross Abstract: It is widely believed that tens of thousands of physical qubits are needed to build a practically useful quantum computer. Atom arrays formed by optic

Dream to Fly: Model-Based Reinforcement Learning for Vision-Based Drone Flight

model-releasesarxiv-cs-ro

arXiv:2501.14377v2 Announce Type: replace Abstract: Autonomous drone racing has risen as a challenging robotic benchmark for testing the limits of learning, perception, planning, and control. Expert h

Agents

Fast-dVLM: Efficient Block-Diffusion VLM via Direct Conversion from Autoregressive VLM

arXiv:2604.06832v2 Announce Type: replace Abstract: Vision-language models (VLMs) predominantly rely on autoregressive decoding, which generates tokens one at a time and fundamentally limits inference

agentsarxiv-cs-cl

Integrated electro-optic attention nonlinearities for transformers

arXiv:2604.09512v1 Announce Type: new Abstract: Transformers have emerged as the dominant neural-network architecture, achieving state-of-the-art performance in language processing and computer vision

Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction

arXiv:2506.11552v2 Announce Type: replace-cross Abstract: Quantum error correction is crucial for protecting quantum information against decoherence. Traditional codes like the surface code require su

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

arXiv:2604.08971v1 Announce Type: new Abstract: Edge devices increasingly run multimodal sensing pipelines that must remain accurate despite fluctuating power budgets and unpredictable sensor dropout.

One Interface, Many Robots: Unified Real-Time Low-Level Motion Planning for Collaborative Arms

arXiv:2604.08787v1 Announce Type: new Abstract: This paper proposes a common interface for real-time low-level motion planning of collaborative robotic arms, aimed at enabling broader applicability an

researcharxiv-cs-ro

Online Intention Prediction via Control-Informed Learning

model-releasesarxiv-cs-lg

arXiv:2604.09303v1 Announce Type: cross Abstract: This paper presents an online intention prediction framework for estimating the goal state of autonomous systems in real time, even when intention is

Local Ai

Statistical Properties of the King Wen Sequence: An Anti-Habituation Structure That Does Not Improve Neural Network Training

arXiv:2604.09234v1 Announce Type: cross Abstract: The King Wen sequence of the I-Ching (c. 1000 BC) orders 64 hexagrams -- states of a six-dimensional binary space -- in a pattern that has puzzled sch

local-aiarxiv-cs-ai

Variational Quantum Physics-Informed Neural Networks for Hydrological PDE-Constrained Learning with Inherent Uncertainty Quantification

arXiv:2604.09374v1 Announce Type: cross Abstract: We propose a Hybrid Quantum-Classical Physics-Informed Neural Network (HQC-PINN) that integrates parameterized variational quantum circuits into the P

ActiveGlasses: Learning Manipulation with Active Vision from Ego-centric Human Demonstration

arXiv:2604.08534v1 Announce Type: new Abstract: Large-scale real-world robot data collection is a prerequisite for bringing robots into everyday deployment. However, existing pipelines often rely on s

safetyarxiv-cs-ro

DHFP-PE: Dual-Precision Hybrid Floating Point Processing Element for AI Acceleration

arXiv:2604.04507v2 Announce Type: replace-cross Abstract: The rapid adoption of low-precision arithmetic in artificial intelligence and edge computing has created a strong demand for energy-efficient

researcharxiv-cs-ro

Distributed Interpretability and Control for Large Language Models

model-releasesarxiv-cs-ai

arXiv:2604.06483v1 Announce Type: cross Abstract: Large language models that require multiple GPU cards to host are usually the most capable models. It is necessary to understand and steer these model

Flux Attention: Context-Aware Hybrid Attention for Efficient LLMs Inference

model-releasesarxiv-cs-cl

arXiv:2604.07394v1 Announce Type: cross Abstract: The quadratic computational complexity of standard attention mechanisms presents a severe scalability bottleneck for LLMs in long-context scenarios. W

FP4 Explore, BF16 Train: Diffusion Reinforcement Learning via Efficient Rollout Scaling

arXiv:2604.06916v1 Announce Type: cross Abstract: Reinforcement-Learning-based post-training has recently emerged as a promising paradigm for aligning text-to-image diffusion models with human prefere

safetyarxiv-cs-ai

Incorporating Social Awareness into Control of Unknown Multi-Agent Systems: A Real-Time Spatiotemporal Tubes Approach

arXiv:2510.25597v2 Announce Type: replace-cross Abstract: This paper presents a decentralized control framework that incorporates social awareness into multi-agent systems with unknown dynamics to ach

safetyarxiv-cs-ro

Iteratively Learning Muscle Memory for Legged Robots to Master Adaptive and High Precision Locomotion

arXiv:2507.13662v2 Announce Type: replace Abstract: This paper presents a scalable and adaptive control framework for legged robots that integrates Iterative Learning Control (ILC) with a biologically

researcharxiv-cs-ro

Local Ai

NativeTernary: A Self-Delimiting Binary Encoding with Unary Run-Length Hierarchy Markers for Ternary Neural Network Weights, Structured Data, and General Computing Infrastructure

arXiv:2604.03336v2 Announce Type: replace Abstract: BitNet b1.58 (Ma et al., 2024) demonstrates that large language models can operate entirely on ternary weights {-1, 0, +1}, yet no native binary wir

local-aiarxiv-cs-lg

Agents

ParkSense: Where Should a Delivery Driver Park? Leveraging Idle AV Compute and Vision-Language Models

arXiv:2604.07912v1 Announce Type: new Abstract: Finding parking consumes a disproportionate share of food delivery time, yet no system addresses precise parking-spot selection relative to merchant ent

agentsarxiv-cs-cv

PrivFedTalk: Privacy-Aware Federated Diffusion with Identity-Stable Adapters for Personalized Talking-Head Generation

model-releasesarxiv-cs-cv

arXiv:2604.08037v1 Announce Type: cross Abstract: Talking-head generation has advanced rapidly with diffusion-based generative models, but training usually depends on centralized face-video and speech

Applications

Production-Ready Automated ECU Calibration using Residual Reinforcement Learning

arXiv:2604.07059v1 Announce Type: new Abstract: Electronic Control Units (ECUs) have played a pivotal role in transforming motorcars of yore into the modern vehicles we see on our roads today. They ac

applicationsarxiv-cs-lg

SANDO: Safe Autonomous Trajectory Planning for Dynamic Unknown Environments

model-releasesarxiv-cs-ro

arXiv:2604.07599v1 Announce Type: new Abstract: SANDO is a safe trajectory planner for 3D dynamic unknown environments, where obstacle locations and motions are unknown a priori and a collision-free p

SentinelSphere: Integrating AI-Powered Real-Time Threat Detection with Cybersecurity Awareness Training

model-releasesarxiv-cs-ai

arXiv:2604.06900v1 Announce Type: cross Abstract: The field of cybersecurity is confronted with two interrelated challenges: a worldwide deficit of qualified practitioners and ongoing human-factor wea

Spike-based alignment learning solves the weight transport problem

arXiv:2503.02642v3 Announce Type: replace-cross Abstract: In both machine learning and in computational neuroscience, plasticity in functional neural networks is frequently expressed as gradient desce

safetyarxiv-cs-lg