Search: “hardware”

Bandit Algorithms for Deep Brain Stimulation

arXiv:2601.12699v2 Announce Type: replace Abstract: Deep Brain Stimulation (DBS) is an effective treatment for Parkinson's disease, but conventional fixed-parameter stimulation can reduce battery life

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BioRefusalAudit: Auditing Biosecurity Refusal Depth Using General and Domain-Fine-Tuned Sparse Autoencoders

DGX agent

arXiv:2605.30162v1 Announce Type: new Abstract: Biosecurity evaluations of language models typically ask whether models produce hazardous output. This paper asks a complementary question: when a model

model-releasesarxiv-cs-ai

29 May 2026

BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models

arXiv:2605.30226v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for grounding visual-language understanding into real-world robotic manipulat

safetyarxiv-cs-ai

HTAM: Hierarchical Transition-Attended Memory for Operator Optimization

arXiv:2605.29734v1 Announce Type: new Abstract: High-performance GPU kernels are essential for efficient LLM deployment, yet optimizing them remains expertise-intensive. Recent LLM-based code generati

local-aiarxiv-cs-cl

NeuroEdge: Real-Time Hand Gesture Recognition with High-Density EMG Using Deep Learning at the Edge

arXiv:2605.29326v1 Announce Type: new Abstract: High-density electromyography (HD-EMG) has emerged as a powerful modality for decoding fine-grained neuromuscular activity, enabling real-time neural-ma

Parallax: Parameterized Local Linear Attention for Language Modeling

arXiv:2605.29157v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become the central paradigm in artificial intelligence, yet the core computational primitive of attention has remain

Phantom: Training Robots Without Robots Using Only Human Videos

arXiv:2503.00779v2 Announce Type: replace Abstract: Training general-purpose robots requires learning from large and diverse data sources. Current approaches rely heavily on teleoperated demonstration

researcharxiv-cs-ro

Pocket-Dentist: On-Device Dental Image Understanding via Efficient Multimodal Large Language Models

arXiv:2605.29299v1 Announce Type: cross Abstract: Evaluations of dental vision-language models remain fragmented across datasets, task definitions and metrics, and often ignore their computational cos

The Open Motion Planning Library 2.0

model-releasesarxiv-cs-ro

arXiv:2605.29301v1 Announce Type: new Abstract: The Open Motion Planning Library (OMPL), first released in 2008, has become a cornerstone of the motion planning community, providing implementations of

Veda: Scalable Video Diffusion via Distilled Sparse Attention

arXiv:2605.30325v1 Announce Type: new Abstract: Scaling Diffusion Transformers to generate high-resolution, long videos is constrained by the quadratic cost of self-attention, and existing sparse atte

researcharxiv-cs-cv

A Methodology to Assess Power Modeling in Energy-Aware Federated Learning on Heterogeneous Mobile Devices

arXiv:2605.27601v1 Announce Type: cross Abstract: Estimating CPU power on heterogeneous ARM-based commodity devices is challenging due to limited access to CPU's voltage domains. As a result, state-of

Benchmarking AI for low-resource contexts: Thinking beyond leaderboards

arXiv:2605.28508v1 Announce Type: new Abstract: Existing AI evaluation practices often fail to capture how systems actually perform in low-resource environments, where operational constraints shape us

Benchmarking Inductive Biases for Multivariate Time-Series Anomaly Detection with a Robust Multi-View Channel-Graph Detector

arXiv:2605.28103v1 Announce Type: new Abstract: We present a unified experiment, analysis, and benchmark study of multivariate time-series (MTS) anomaly detection. Ten family-representative detectors

BlazeEdit: Generalist Image Editing on Mobile Devices with Image-to-Image Diffusion Models

arXiv:2605.28067v1 Announce Type: new Abstract: The remarkable generation quality of modern diffusion models often comes at the cost of massive parameter counts, which necessitate server-side inferenc

CircuitLM: A Multi-Agent LLM-Aided Design Framework for Generating Circuit Schematics from Natural Language Prompts

arXiv:2601.04505v3 Announce Type: replace Abstract: Generating accurate circuit schematics from high-level natural language descriptions remains a persistent challenge in electronic design automation

agentsarxiv-cs-ai

CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models

arXiv:2605.28115v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods the

Hybrid Neural World Models

arXiv:2605.28317v1 Announce Type: cross Abstract: Neural surrogates promise large speedups over classical solvers for physical dynamics but fail silently at sharp dynamical events such as shocks, fron

researcharxiv-cs-ai

Imitating and Finetuning Model Predictive Control for Robust and Symmetric Quadrupedal Locomotion

arXiv:2311.02304v3 Announce Type: replace Abstract: Control of legged robots is a challenging problem that has been investigated by different approaches, such as model-based control and learning algor

safetyarxiv-cs-ro

Learning Logical Operations for Arbitrary Quantum Error Correction Codes

arXiv:2605.28162v1 Announce Type: cross Abstract: Logical operations are essential for quantum computation within quantum error-correcting codes. However, discovering their physical realizations is ch

OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning

arXiv:2605.28691v1 Announce Type: new Abstract: Diffusion Transformers achieve strong video generation quality, but the quadratic cost of full attention limits efficiency. We introduce OSP-Next, an ef

local-aiarxiv-cs-cv

PrunePath: Towards Highly Structured Sparse Language Models

arXiv:2605.28283v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) dominate the parameter count and computation of modern language models, yet existing pruning methods often struggle to co

Real Time NILM Based Power Monitoring of Identical Induction Motors Representing Cutting Machines in Textile Industry

arXiv:2601.01616v2 Announce Type: replace Abstract: The textile industry in Bangladesh is one of the most energy-intensive sectors, yet its monitoring practices remain largely outdated, resulting in i

Regression Language Models for Code

arXiv:2509.26476v2 Announce Type: replace-cross Abstract: We study code-to-metric regression: predicting numeric outcomes of code executions, a challenging task due to the open-ended nature of program

ViCA: Efficient Multimodal LLMs with Vision-Only Cross-Attention

arXiv:2602.07574v2 Announce Type: replace-cross Abstract: Modern multimodal large language models (MLLMs) adopt a unified self-attention design that processes visual and textual tokens at every Transf

researcharxiv-cs-cl

Applications

Comparative Study of Vision-Based Metric Measurement for Large-Scale Planar Scenes

arXiv:2605.26475v1 Announce Type: cross Abstract: Vision-based metric distance and area measurement remains challenging in large-scale outdoor environments due to long-range sensing, camera zoom, and

applicationsarxiv-cs-ai

Dense2MoE: Pushing the Pareto Frontier of On-Device LLMs via Unified Pruning and Upcycling

arXiv:2605.26496v1 Announce Type: cross Abstract: The Mixture of Experts MoE architecture is highly promising for resource constrained on device deployments yet training these models from scratch incu

Device Context Protocol: A Compact, Safety-First Architecture for LLM-Driven Control of Constrained Devices

arXiv:2605.26159v1 Announce Type: cross Abstract: Large language models are increasingly used as orchestrators of external tools via the Model Context Protocol (MCP), but MCP is built for software ser

Edge AI Deployment Beyond Models: A BSP-Aware Systems Framework for Industrial Embedded Platforms

arXiv:2605.26119v1 Announce Type: cross Abstract: Industrial Edge AI programs often begin with the model and only later confront the platform. That sequencing is attractive because it allows early dem

Efficient On-policy Visual-RL via Stochastic Decoupled Policy Gradient

arXiv:2605.26478v1 Announce Type: cross Abstract: We present the stochastic decoupled policy gradient (SDPG), a lightweight visual reinforcement learning (RL) method that trains diverse visuomotor con

safetyarxiv-cs-ai

GENESIS: Harnessing AI Agents for Autonomous 6G RAN Synthesis, Research, and Testing

arXiv:2605.27360v1 Announce Type: cross Abstract: Cellular research and development (R&D) is throttled by six structural processes that each consume months of manual engineering work per iteration: (i

agentsarxiv-cs-ai

MicroSpec: Accelerating Speculative Decoding with Lightweight In-Context Vocabularies

arXiv:2605.26444v1 Announce Type: new Abstract: Large language models typically employ vocabularies of over 100k tokens, which creates a major computational bottleneck at the final linear projection l

local-aiarxiv-cs-cl

Applications

PhyPush: One Push is All You Need for Sensorless Physical Property Estimation with Physics-Guided Transformers

arXiv:2605.26284v1 Announce Type: new Abstract: Accurately estimating object mass and friction is fundamental to achieving reliable and adaptive robotic manipulation. Although interactive perception p

applicationsarxiv-cs-ro

SpatialBench: Is Your Spatial Foundation Model an All-Round Player?

model-releasesarxiv-cs-cv

arXiv:2605.27367v1 Announce Type: new Abstract: While spatial foundation models have demonstrated impressive performance on standard datasets, a critical question remains: are they truly all-round pla

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

arXiv:2605.26523v1 Announce Type: cross Abstract: Large-batch Contrastive Learning (CL), the foundation of modern representation learning, is fundamentally incompatible with the volatile resource cons

Telenor Nordics Customer Service self-help corpus

arXiv:2605.26891v1 Announce Type: new Abstract: This paper presents a multilingual customer service self-help corpus comprising 1,122 manually validated documents in Finnish, Danish, Norwegian, and Sw

agentsarxiv-cs-cl

The Constraint Tax: Measuring Validity-Correctness Tradeoffs in Structured Outputs for Small Language Models

arXiv:2605.26128v1 Announce Type: new Abstract: Production LLM systems increasingly require machine-readable outputs: JSON objects, typed traces, regex-constrained fields, and tool-call schemas. This

local-aiarxiv-cs-lg

Touch-R1: Reinforcing Touch Reasoning in MLLMs

arXiv:2605.27154v1 Announce Type: new Abstract: While rule-based reinforcement learning has recently catalyzed explicit reasoning in multimodal models, tactile reasoning remains largely underexplored.

researcharxiv-cs-cv

Verilog-Evolve: Feedback-Driven and Skill-Evolving Verilog Generation

arXiv:2605.26498v1 Announce Type: new Abstract: Large language models (LLMs) have improved Verilog generation from natural-language specifications, but most pipelines still treat generation as isolate

researcharxiv-cs-cl

Zero-Shot MARL Benchmark in the Cyber-Physical Mobility Lab

model-releasesarxiv-cs-ro

arXiv:2601.16578v2 Announce Type: replace Abstract: We present a reproducible benchmark for evaluating sim-to-real transfer of Multi-Agent Reinforcement Learning (MARL) policies for Connected and Auto

A Tabular Schedule Abstraction for Communication-Aware Evaluation of Pipeline-Parallel LLM Training

arXiv:2605.24006v1 Announce Type: cross Abstract: Pipeline parallelism is a key technique for distributed training of large language models because it reduces per-device parameter and activation memor

A Unified Python Framework for Direct PPO-based Control of AHUs with Economizer Logic and CO2-Constrained Ventilation

arXiv:2605.24406v1 Announce Type: new Abstract: Optimizing HVAC (Heating, Ventilation and Air Conditioning) can enhance a building's energy efficiency while providing comfort levels for its occupants.

safetyarxiv-cs-lg

AcroRL: Learning Aggressive Quadrotor Inversion using Bidirectional Thrust

arXiv:2605.24301v1 Announce Type: new Abstract: Bidirectional thrust grants quadrotors a second equilibrium condition and increased control authority, expanding the envelope of possible aggressive man

researcharxiv-cs-ro

Bridging the Gap: Enabling Soft Actor Critic for High Performance Legged Locomotion

arXiv:2605.24975v1 Announce Type: cross Abstract: Proximal Policy Optimization (PPO) has become the de facto standard for training legged robots, thanks to its robustness and scalability in massively

safetyarxiv-cs-ai

Data-Driven Optimization of Tactile Sensor Configurations for Efficient Dexterous Manipulation

arXiv:2409.20473v3 Announce Type: replace Abstract: Tactile sensing is critical for learning-based dexterous manipulation, yet principled guidelines for sensor placement remain largely absent. While d

safetyarxiv-cs-ro

Dynamic Neural Koopman Distillation for Real-Time Robot Control Using Diffusion Models

arXiv:2605.24924v1 Announce Type: new Abstract: Diffusion models excel at generating diverse and multimodal trajectories for robotic planning, yet their iterative denoising process introduces latency

safetyarxiv-cs-ro

EVA: Accelerating LLM Decoding via an Efficient Vector Quantization Architecture

arXiv:2605.24144v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved impressive performance across diverse domains but remain inefficient during the autoregressive decoding pha

Federated Learning over Human-Body Communication for On-Body Edge Intelligence: A Survey, Taxonomy, and BODYFED-HBC Scheduling Vignette

arXiv:2605.24062v1 Announce Type: cross Abstract: Human-body communication (HBC) is a promising physical substrate for wearable body-area networks because it can localize communication around the body

From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems

arXiv:2605.23955v1 Announce Type: new Abstract: Deploying machine learning in regulated financial environments -- credit risk, fraud detection, and anti-money laundering -- exposes critical vulnerabil

agentsarxiv-cs-ai