Search: “hardware”

ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning

arXiv:2602.11236v2 Announce Type: replace-cross Abstract: Building general-purpose embodied agents across diverse hardware remains a central challenge in robotics, often framed as the ''one-brain, man

15 Apr 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

Problem Reductions at Scale: Agentic Integration of Computationally Hard Problems

DGX agent

arXiv:2604.11535v1 Announce Type: new Abstract: Solving an NP-hard optimization problem often requires reformulating it for a specific solver -- quantum hardware, a commercial optimizer, or a domain h

agentsarxiv-cs-ai

14 Apr 2026

Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents

arXiv:2604.11465v1 Announce Type: new Abstract: Large language model (LLM) agents show promise on realistic tool-use tasks, but deploying capable agents on modest hardware remains challenging. We stud

14 Apr 2026

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning

arXiv:2507.04736v2 Announce Type: replace Abstract: Large Language Models have emerged as powerful tools for automating Register-Transfer Level (RTL) code generation, yet they face critical limitation

safetyarxiv-cs-ai

13 Apr 2026

Watt Counts: Energy-Aware Benchmark for Sustainable LLM Inference on Heterogeneous GPU Architectures

arXiv:2604.09048v1 Announce Type: cross Abstract: While the large energy consumption of Large Language Models (LLMs) is recognized by the community, system operators lack guidance for energy-efficient

13 Apr 2026

AI-Driven Research for Databases

arXiv:2604.06566v1 Announce Type: cross Abstract: As the complexity of modern workloads and hardware increasingly outpaces human research and engineering capacity, existing methods for database perfor

safetyarxiv-cs-ai

CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency

arXiv:2604.07286v1 Announce Type: cross Abstract: Autonomous vehicles deployed in remote environments typically rely on embedded processors, compact batteries, and lightweight sensors. These hardware

Extraction of linearized models from pre-trained networks via knowledge distillation

arXiv:2604.06732v1 Announce Type: new Abstract: Recent developments in hardware, such as photonic integrated circuits and optical devices, are driving demand for research on constructing machine learn

The Geometry of Forgetting

arXiv:2604.06222v1 Announce Type: cross Abstract: Why do we forget? Why do we remember things that never happened? The conventional answer points to biological hardware. We propose a different one: ge

ABNAT: Attention-Based Noise-Aware Training for Robust Transformers on Analog Compute-in-Memory Systems

arXiv:2610.22065v1 Announce Type: new Abstract: Transformer-based models have become the backbone of a wide range of tasks, but their intensive computation and data movement incur substantial energy o

DeepUnfolding_Agent: A Classical_Quantum Adaptive Control API

arXiv:2610.20615v1 Announce Type: new Abstract: Adaptive optimization workflows in machine learning, federated learning, quantum machine learning, and hybrid classical quantum systems often embed cont

Fractional Power-of-Two Quantization for Efficient and Effective Multiplier-Free LLM Inference

arXiv:2610.21257v1 Announce Type: cross Abstract: Large Language Models (LLMs) demand efficient inference, where the multiply-accumulate (MAC) operations in linear projections dominate compute and ene

MeddeX: A Retrieval-Augmented LLaMA-3 System with Gemini Vision for Evidence-Backed Medical Report Analysis

arXiv:2610.20632v1 Announce Type: new Abstract: Modern healthcare generates increasingly complex medical reports that challenge clinical professionals in terms of time and interpretive burden. Manual

ResStreamGS: Residual-Sensitive Dual-Stream Gaussian Splatting for Mobile Volumetric Video Streaming

arXiv:2610.21121v1 Announce Type: cross Abstract: Real-time mobile volumetric video enables immersive free-viewpoint experiences, but delivering high-quality 3D content under constrained bandwidth and

researcharxiv-cs-cv

Rethinking Routing Exploration in Modern Mixture-of-Experts

arXiv:2610.22353v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models have become an important approach for scaling model parameters. Modern MoE architectures increasingly combine two desi

X-RIC: An Agentic RAN-Intelligent Controller Benchmark for Enhancing Reinforcement Learning

arXiv:2610.22269v1 Announce Type: new Abstract: The O-RAN ALLIANCE introduces architectural flexibility through disaggregation and AI-driven control. While the RAN Intelligent Controller (RIC) enables

Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimization

arXiv:2604.25083v2 Announce Type: replace Abstract: Computer Architecture research has traditionally required the exploration of vast, highly complex design spaces through manual human effort. Large L

Benchmarking Quantum Kernel SVMs for Credit Card Fraud Detection: Performance Realities Under NISQ Constraints

arXiv:2610.17027v1 Announce Type: new Abstract: Detecting credit card fraud is notoriously difficult because fraudulent charges make up less than 0.2% of total transactions. Quantum Machine Learning (

Cross-Scenario Industrial Defect Detection via Domain-Robust Training and Metric-Aligned Selection

model-releasesarxiv-cs-cv

arXiv:2610.19540v1 Announce Type: new Abstract: Automated defect detection of industrial boards must remain highly reliable under cross-scenario variations in lighting, surface contaminants, and produ

Design and Characterization of a Unified Continuum Robot Actuation Platform

arXiv:2610.19798v1 Announce Type: new Abstract: Continuum robots enable dexterous access to confined spaces in applications such as minimally invasive surgery and industrial inspection. However, their

researcharxiv-cs-ro

SAGE: Efficient Protected Vision-Language Inference on Smart Glasses

arXiv:2610.14089v1 Announce Type: cross Abstract: Smart glasses are a promising platform for vision-language assistants, but private split inference remains expensive: protecting visual representation

SAGE: Pushing 2-Bit Vector-Quantized LLMs toward Real-World Usability

arXiv:2610.14745v1 Announce Type: new Abstract: Extreme low-bit weight-only quantization is an effective approach to reducing the deployment costs of large language models. Below 3 bits, scalar quanti

Tactile-Guided Robot Learning: From Representation Learning to Foundation Models

arXiv:2610.20134v1 Announce Type: new Abstract: Tactile sensing is becoming central to robust, adaptive, and dexterous robotic manipulation. Beyond its traditional role in contact detection and reacti

Locomotion with Online Awareness of Dynamics for Precision Footholds

arXiv:2610.17930v1 Announce Type: new Abstract: Unknown payloads alter robot dynamics and make precise contact execution difficult when foothold margins are small. We present LOAD, a perceptive locomo

14 Oct 2026

On physical implementability of reinforcement-learning-driven reasoning

arXiv:2610.14131v1 Announce Type: cross Abstract: In the machine learning community, the reinforcement-learning-driven reasoning process has been intensively studied since around 2025. In this article

14 Oct 2026

Tutorials

Use Of Convolutional Neural Networks In Detection Of Branch Dieback Disease In Pequi Trees

arXiv:2610.15049v1 Announce Type: new Abstract: This study aims to evaluate and compare convolutional neural network (CNN) architectures, specifically AlexNet, Inception, LeNet, VGG16, and MobileNet,

tutorialsarxiv-cs-cv

14 Oct 2026

Deploying RDMA for Large-Scale Inference and Training Workloads

arXiv:2610.12815v1 Announce Type: new Abstract: RDMA can reduce communication overhead in distributed machine learning systems, but realizing these benefits in production requires more than replacing

12 Oct 2026

Monarch-MoE: Structured Experts for Multimodal Continual Instruction Tuning

arXiv:2610.13215v1 Announce Type: new Abstract: Learning new tasks in multimodal continual instruction tuning can cause catastrophic forgetting of previously acquired knowledge. Although multi-expert

12 Oct 2026

Large-Scale Benchmarking of Quantum Neural Network Configurations for Financial Time Series Forecasting

arXiv:2610.12148v1 Announce Type: new Abstract: Quantum machine learning, and quantum neural networks (QNNs) in particular, are advancing fields with growing potential. Although systematic comparisons

9 Oct 2026

TACROSS: An Efficient and Low-Cost Scalable Human Touch System Across Heterogeneous Tactile Sensors for Dexterous Robot Learning

arXiv:2610.11945v1 Announce Type: cross Abstract: Collecting tactile demonstrations on robots is costly and slow, motivating the use of lower-cost human tactile gloves for scalable data collection. Ho

safetyarxiv-cs-lg

9 Oct 2026

BEACON-SP: Ontology-Grounded GraphRAG Framework for Clinical Suicide Risk Assessment

arXiv:2610.09026v1 Announce Type: cross Abstract: We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavior

8 Oct 2026

From Wearable Interfaces to Dexterous Policies: Contact Shifts and Tactile Representations

arXiv:2610.08870v1 Announce Type: new Abstract: Unlike conventional teleoperation, wearable interfaces allow operators to collect dexterous demonstrations through their own hand motions while directly

8 Oct 2026

SAPS: Shared Autonomy for Policy Steering by Blending Teleoperation with a Pretrained VLA

arXiv:2606.15568v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models perform well in generalist robot manipulation but remain brittle to out-of-distribution perturbations, while ful

8 Oct 2026

Activation Denoising: A Robustness View on Parallel vs Sequential LLM Quantization

arXiv:2610.07522v1 Announce Type: new Abstract: Post-training quantization is a powerful tool for compressing large language models. The most scalable methods quantize every layer in parallel, but qua

Component and Dimension Sparsity in Transformer Refusal Mechanisms

arXiv:2610.06903v1 Announce Type: cross Abstract: Activation steering manipulates large language model behavior by intervening on internal activations, but the mechanistic basis of these interventions

Massive Activation Gating Channel in Large Language Models

arXiv:2610.07661v1 Announce Type: new Abstract: Massive activations, a phenomenon in which a small number of hidden channels exhibit exceptionally large magnitudes, are pervasive in large language mod

Tutorials

Mu-DisCoCat: A Variational Pipeline for Compositional Generalization on Quantum Processors

arXiv:2610.08131v1 Announce Type: cross Abstract: Achieving compositional concept generalization (CoCoGen), the ability to understand novel situations by recombining learned primitives, remains a fund

tutorialsarxiv-cs-cv

RoboCap: A New Platform for Egocentric Robot Learning

arXiv:2610.07217v1 Announce Type: cross Abstract: Despite its promise for scaling robot learning, egocentric manipulation data is still scarce today. Collection at scale requires vertically integratin

CIPHER-MoE: Balancing Efficiency and Routing Fidelity in Trillion-Scale MoE Training

arXiv:2610.05744v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has been widely adopted in recent large language model (LLM) architectures. However, scaling up MoE in LLM training introduces

Dynamic Harness Search: Building Multi-Agent Systems Per-Query via Prediction

arXiv:2610.04137v1 Announce Type: new Abstract: Agent harnesses specify the roles, instructions, tools, and communication structure used to solve a task, and the right harness depends on the query. Be

Local Ai

RepTC: Representation-Aware Optimization for Efficient Traffic Classification on Edge IoT Devices

arXiv:2610.04784v1 Announce Type: cross Abstract: Traffic classification (TC) is crucial to secure Internet of Things (IoT) networks, whose edge nodes often operate under privacy, bandwidth, and energ

local-aiarxiv-cs-lg

Scaling Down the Scaling Laws: Parameter Efficiency and Compute-Optimal Training in Resource-Constrained Large Language Models

arXiv:2610.06387v1 Announce Type: new Abstract: Large language models (LLMs) have achieved substantial performance gains through increases in model size, training data, and computational resources. Ho

Understanding the Weight Averaging Mechanism in LLM Training for Post-Training Quantization

arXiv:2610.05329v1 Announce Type: new Abstract: Large language models (LLMs) are typically pretrained in high precision but increasingly deployed with low-precision post-training quantization (PTQ). R

What Does a Harness Buy? Tokens, Mostly

arXiv:2610.04433v1 Announce Type: cross Abstract: A coding agent is a language model wrapped in a harness: the system prompt, the tool set, and the context management that turn a chat model into somet

Around the World: Unified Learned Locomotion on a 270 g Continuous-Rotation Quadruped

model-releasesarxiv-cs-ro

arXiv:2610.02728v1 Announce Type: new Abstract: Closed-loop learned locomotion is established on commercial quadrupeds but remains uncommon at the sub-kilogram scale. Continuous-rotation legs give MiN

5 Oct 2026

Post-Training Quantization of Autoregressive Weather Models

arXiv:2610.02511v1 Announce Type: new Abstract: Advancements in high-resolution numerical weather prediction (NWP) and data assimilation (DA) have shaped the developments in deep learning (DL) archite

5 Oct 2026

SimuVerity: Benchmarking Agents for Engineering-Grade Simulink Model Generation

arXiv:2610.02304v1 Announce Type: cross Abstract: Existing Simulink benchmarks mainly evaluate whether generated models compile, execute, or resemble a reference model. These criteria do not establish

5 Oct 2026

Format-Aware Fusion for Fast FP4 Pretraining

arXiv:2610.00053v1 Announce Type: new Abstract: Four-bit floating-point (FP4) Tensor Cores accelerate matrix multiplication, but scale computation, operand packing, layout construction, and saved back