Search: “hardware”

CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts

arXiv:2604.10496v1 Announce Type: new Abstract: Outliers have emerged as a fundamental bottleneck in preserving accuracy for low-precision large models, particularly within Mixture-of-Experts (MoE) ar

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Hardware

Deep Optimizer States: Towards Scalable Training of Transformer Models Using Interleaved Offloading

DGX agent

arXiv:2410.21316v2 Announce Type: replace-cross Abstract: Transformers and large language models~(LLMs) have seen rapid adoption in all domains. Their sizes have exploded to hundreds of billions of pa

hardwarearxiv-cs-ai

14 Apr 2026

Generative Design for Direct-to-Chip Liquid Cooling for Data Centers

arXiv:2604.10941v1 Announce Type: cross Abstract: Rapid growth in artificial intelligence (AI) workloads is driving up data center power densities, increasing the need for advanced thermal management.

GPU-Accelerated Continuous-Time Successive Convexification for Contact-Implicit Legged Locomotion

arXiv:2604.09993v1 Announce Type: new Abstract: Contact-implicit trajectory optimization (CITO) enables the automatic discovery of contact sequences, but most methods rely on fine time discretization

hardwarearxiv-cs-ro

PA-SFM: Tracker-free differentiable acoustic radiation for freehand 3D photoacoustic imaging

arXiv:2604.09643v1 Announce Type: new Abstract: Three-dimensional (3D) handheld photoacoustic tomography typically relies on bulky and expensive external positioning sensors to correct motion artifact

Real-Time Voicemail Detection in Telephony Audio Using Temporal Speech Activity Features

arXiv:2604.09675v1 Announce Type: cross Abstract: Outbound AI calling systems must distinguish voicemail greetings from live human answers in real time to avoid wasted agent interactions and dropped c

Relational Probing: LM-to-Graph Adaptation for Financial Prediction

arXiv:2604.10212v1 Announce Type: new Abstract: Language models can be used to identify relationships between financial entities in text. However, while structured output mechanisms exist, prompting-b

hardwarearxiv-cs-cl

StreamServe: Adaptive Speculative Flows for Low-Latency Disaggregated LLM Serving

arXiv:2604.09562v1 Announce Type: cross Abstract: Efficient LLM serving must balance throughput and latency across diverse, bursty workloads. We introduce StreamServe, a disaggregated prefill decode s

Sustainable Transformer Neural Network Acceleration with Stochastic Photonic Computing

arXiv:2604.09759v1 Announce Type: cross Abstract: Transformers achieve state-of-the-art performance in natural language processing, vision, and scientific computing, but demand high computation and me

Tree Training: Accelerating Agentic LLMs Training via Shared Prefix Reuse

arXiv:2511.00413v4 Announce Type: replace Abstract: Agentic large language model (LLM) training often involves multi-turn interaction trajectories that branch into multiple execution paths due to conc

VTC: DNN Compilation with Virtual Tensors for Data Movement Elimination

arXiv:2604.09558v1 Announce Type: cross Abstract: With the widening gap between compute and memory operation latencies, data movement optimizations have become increasingly important for DNN compilati

CSAttention: Centroid-Scoring Attention for Accelerating LLM Inference

arXiv:2604.08584v1 Announce Type: cross Abstract: Long-context LLMs increasingly rely on extended, reusable prefill prompts for agents and domain Q&A, pushing attention and KV-cache to become the domi

Fast Model-guided Instance-wise Adaptation Framework for Real-world Pansharpening with Fidelity Constraints

arXiv:2604.08903v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) and high-resolution panchromati

FlashLips: 100-FPS Mask-Free Latent Lip-Sync using Reconstruction Instead of Diffusion or GANs

arXiv:2512.20033v2 Announce Type: replace Abstract: We present FlashLips, a two-stage, mask-free lip-sync system that decouples lips control from rendering and achieves real-time performance, with our

High-dimensional inference for the gamma-ray sky with differentiable programming

arXiv:2604.08648v1 Announce Type: cross Abstract: We motivate the use of differentiable probabilistic programming techniques in order to account for the large model-space inherent to astrophysical gam

TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training

arXiv:2604.09107v1 Announce Type: cross Abstract: Modern LLM reinforcement learning (RL) workloads require a highly efficient weight transfer system to scale training across heterogeneous computationa

U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster

arXiv:2604.09041v1 Announce Type: cross Abstract: AI-based weather forecasting now rivals traditional physics-based ensembles, but state-of-the-art (SOTA) models rely on specialized architectures and

A Lightweight Library for Energy-Based Joint-Embedding Predictive Architectures

arXiv:2602.03604v3 Announce Type: replace-cross Abstract: We present EB-JEPA, an open-source library for learning representations and world models using Joint-Embedding Predictive Architectures (JEPAs

AgiPIX: Bridging Simulation and Reality in Indoor Aerial Inspection

model-releasesarxiv-cs-ro

arXiv:2604.08009v1 Announce Type: new Abstract: Autonomous indoor flight for critical asset inspection presents fundamental challenges in perception, planning, control, and learning. Despite rapid pro

CodecSight: Leveraging Video Codec Signals for Efficient Streaming VLM Inference

arXiv:2604.06036v3 Announce Type: replace-cross Abstract: Video streaming analytics is a crucial workload for vision-language model serving, but the high cost of multimodal inference limits scalabilit

DynLP: Parallel Dynamic Batch Update for Label Propagation in Semi-Supervised Learning

arXiv:2604.06596v1 Announce Type: cross Abstract: Semi-supervised learning aims to infer class labels using only a small fraction of labeled data. In graph-based semi-supervised learning, this is typi

ForkKV: Scaling Multi-LoRA Agent Serving via Copy-on-Write Disaggregated KV Cache

arXiv:2604.06370v1 Announce Type: cross Abstract: The serving paradigm of large language models (LLMs) is rapidly shifting towards complex multi-agent workflows where specialized agents collaborate ov

Foundry: Template-Based CUDA Graph Context Materialization for Fast LLM Serving Cold Start

arXiv:2604.06664v1 Announce Type: cross Abstract: Modern LLM service providers increasingly rely on autoscaling and parallelism reconfiguration to respond to rapidly changing workloads, but cold-start

Full State-Space Visualisation of the 8-Puzzle: Feasibility, Design, and Educational Use

arXiv:2604.06186v1 Announce Type: cross Abstract: Search algorithms are a foundational topic in artificial intelligence education, yet even simple domains can generate large state spaces that challeng

Graph Neural ODE Digital Twins for Control-Oriented Reactor Thermal-Hydraulic Forecasting Under Partial Observability

arXiv:2604.07292v1 Announce Type: new Abstract: Real-time supervisory control of advanced reactors requires accurate forecasting of plant-wide thermal-hydraulic states, including locations where physi

HAWK: Head Importance-Aware Visual Token Pruning in Multimodal Models

arXiv:2604.07812v1 Announce Type: new Abstract: In multimodal large language models (MLLMs), the surge of visual tokens significantly increases the inference time and computational overhead, making th

Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning

arXiv:2604.07345v1 Announce Type: cross Abstract: The rapid growth of generative artificial intelligence (AI) has introduced unprecedented computational demands, driving significant increases in the e

NestPipe: Large-Scale Recommendation Training on 1,500+ Accelerators via Nested Pipelining

arXiv:2604.06956v1 Announce Type: cross Abstract: Modern recommendation models have increased to trillions of parameters. As cluster scales expand to O(1k), distributed training bottlenecks shift from

Object-Centric Stereo Ranging for Autonomous Driving: From Dense Disparity to Census-Based Template Matching

arXiv:2604.07980v1 Announce Type: new Abstract: Accurate depth estimation is critical for autonomous driving perception systems, particularly for long range vehicle detection on highways. Traditional

OpenPRC: A Unified Open-Source Framework for Physics-to-Task Evaluation in Physical Reservoir Computing

arXiv:2604.07423v1 Announce Type: new Abstract: Physical Reservoir Computing (PRC) leverages the intrinsic nonlinear dynamics of physical substrates, mechanical, optical, spintronic, and beyond, as fi

hardwarearxiv-cs-ro

RDSplat: Robust Watermarking for 3D Gaussian Splatting Against 2D and 3D Diffusion Editing

arXiv:2512.06774v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has become a leading representation for high-fidelity 3D assets, yet protecting these assets via digital watermarking r

RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs

arXiv:2510.19225v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become essential for unlocking advanced reasoning capabilities in large language models (LLMs). RL workflows i

Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets

arXiv:2604.07177v1 Announce Type: cross Abstract: We investigate the feasibility of real-time 3D Gaussian Splatting (3DGS) rasterisation on edge clients with varying Gaussian splat counts and GPU comp

ZipMap: Linear-Time Stateful 3D Reconstruction via Test-Time Training

arXiv:2603.04385v3 Announce Type: replace Abstract: Feed-forward transformer models have driven rapid progress in 3D vision, but state-of-the-art methods such as VGGT and pi^3 have a computational

Tutorials

Epically Powerful: An open-source software and mechatronics infrastructure for wearable robotic systems

arXiv:2511.05033v2 Announce Type: replace Abstract: Epically Powerful is an open-source robotics infrastructure that streamlines the underlying framework of wearable robotic systems - managing communi

tutorialsarxiv-cs-ro

Research

Janus: An Algorithm-Evaluator Co-Evolution Framework for LLM-Driven Discovery under Expensive Evaluation Budgets

arXiv:2608.08189v1 Announce Type: new Abstract: LLM-driven program discovery relies on rapid evaluator feedback, but many scientific and engineering tasks require high-fidelity simulations, hardware e

researcharxiv-cs-ai

QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture

model-releasesarxiv-cs-ai

arXiv:2510.22087v3 Announce Type: replace-cross Abstract: The field of computer architecture, which bridges high-level software abstractions and low-level hardware implementations, remains absent from

Safety

Reconfigurable Structural Robotic Assembly: Interlocking 3D Aggregations with Self-Aligning Compound Nested Lattice Modules

arXiv:2608.07576v1 Announce Type: new Abstract: Robotic construction systems often treat the material system and the robot as separate design problems, locating intelligence primarily in hardware, sen

safetyarxiv-cs-ro

HLSmith: An Expert-Guided Agentic Framework for C/C++-to-HLS Translation

model-releasesarxiv-cs-ai

arXiv:2608.06791v1 Announce Type: cross Abstract: Application-specific FPGA accelerators offer substantial performance and energy-efficiency gains across many application domains, but developing them

10 Aug 2026

Learning Fault-Tolerant Locomotion with Adaptive Gait Timing

model-releasesarxiv-cs-lg

arXiv:2608.07328v1 Announce Type: cross Abstract: Hardware failures require legged robots to rapidly reorganize coordination and gait timing to maintain stability and mobility. This is particularly ch

10 Aug 2026

Safety

CheckOne: Lightweight Fault Detection and Mitigation for Vision Transformers

arXiv:2608.04035v1 Announce Type: cross Abstract: The wide adoption of Vision Transformers (ViTs) in safety-critical applications raises reliability concerns related to hardware faults. Algorithm-Base

safetyarxiv-cs-ai

6 Aug 2026

Research

LLM-based Vulnerability Discovery in Business Process Documentation

arXiv:2608.04271v1 Announce Type: cross Abstract: Just like software and hardware, business processes are susceptible to vulnerabilities that can lead to product quality issues, delays, and increased

researcharxiv-cs-cl

6 Aug 2026

Local Ai

Representational separation between unitary and channel quantum generative models via shared classical randomness at shallow depth

arXiv:2608.05110v1 Announce Type: cross Abstract: Near-term quantum hardware limits circuit depth and often imposes geometrically local connectivity for quantum generative models, restricting the outp

local-aiarxiv-cs-ai

6 Aug 2026

Research

A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures

arXiv:2311.17815v3 Announce Type: replace-cross Abstract: Given their increasing size and complexity, the need for efficient execution of deep neural networks has become increasingly pressing in the d

researcharxiv-cs-ai

5 Aug 2026

Morphology-Aware Implicit Super-Resolution Network for Pathological Images

model-releasesarxiv-cs-cv

arXiv:2608.03664v1 Announce Type: new Abstract: Accurate diagnosis in Digital Pathology (DP) relies on high-resolution whole-slide images, yet clinical deployment is often limited by hardware costs. S

5 Aug 2026

Adaptive Reconstruction of Bosonic Quantum States

model-releasesarxiv-cs-lg

arXiv:2608.02049v1 Announce Type: cross Abstract: Bosonic quantum systems provide a hardware-efficient platform for quantum information processing but remain challenging to characterise due to their l

4 Aug 2026

Local Ai

Device-First Feedback: Toward Mobile-Native LLM-Driven Neural Architecture Search

arXiv:2608.00078v1 Announce Type: new Abstract: Deploying convolutional neural networks generated by large language models (LLMs) on real mobile hardware requires more than GPU validation accuracy: IN

local-aiarxiv-cs-cv

4 Aug 2026

Loggia dei Lanzi: AI Thermography Enhancement Comparisons through 3D Photogrammetry