Search: “hardware”

Design Space of Self--Consistent Electrostatic Machine Learning Interatomic Potentials

arXiv:2603.14700v2 Announce Type: replace-cross Abstract: Machine learning interatomic potentials (MLIPs) have become widely used tools in atomistic simulations. For much of the history of this field,

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Hardware

Differentiate the Solver, Not the Equation: Reverse-Sweep Adjoints for Block Implicit Simulation

DGX agent

arXiv:2608.08559v1 Announce Type: cross Abstract: Differentiable simulation is a key component in learning, control, and inverse problems, where gradients through nonlinear implicit solvers are requir

hardwarearxiv-cs-lg

11 Aug 2026

EasyBalance: Cross-Layer Load Balancing in Distributed MoE Inference

arXiv:2608.07964v1 Announce Type: cross Abstract: Load Balancing has emerged as a critical problem in expert-parallel distributed inference of Mixture-of-Experts (MoE) models. As routing distributions

ERF-GS: Reconstructing Fast Motion from Disjoint Event-RGB Viewpoints

arXiv:2608.08531v1 Announce Type: new Abstract: Deep learning-driven representations such as neural radiance fields (NeRFs) and 3D Gaussian splatting (3DGS) have revolutionized the field of dynamic 3D

EsaacSim: A Multimodal Event Camera Add-on for NVIDIA Isaac Sim

arXiv:2608.08522v1 Announce Type: new Abstract: Event-based vision is becoming an increasingly important sensing paradigm for robotics, yet its adoption remains limited by sensor availability and the

From Approachability Residuals to Anytime-Valid Evidence: The Online Convex Geometry of Testing by Betting

arXiv:2608.09450v1 Announce Type: new Abstract: Betting-based sequential tests and Blackwell approachability are linked by a rate-explicit reduction through support-function residuals. For a compact c

Holder Signed Distance: A Differentiable, Signed, Parallelizable Metric for Robotics

arXiv:2608.07707v1 Announce Type: new Abstract: Computing distances between sets is essential in robotic motion planning and control, where differentiable gradients enable real-time optimization. The

Mesh-Attention: A New Communication-Efficient Distributed Attention with Improved Data Locality

arXiv:2512.20968v2 Announce Type: replace-cross Abstract: Distributed attention is essential for scaling large language models (LLMs) to long contexts, yet existing methods either have limited paralle

Physics-Informed Condition Monitoring of SiC Power Modules

arXiv:2608.08363v1 Announce Type: cross Abstract: Silicon carbide (SiC) power modules are increasingly deployed in automotive traction inverters, where condition monitoring is essential to prevent in-

Real-time physics inversion for retrieval of sub-pixel wildfire temperatures from VSWIR imaging spectroscopy

arXiv:2608.07580v1 Announce Type: new Abstract: In this work, we present a wildfire temperature retrieval framework for VSWIR imaging spectroscopy data, employed on data from NASA's Airborne Visible I

StitchCUDA: An Automated Multi-Agents End-to-End GPU Programing Framework with Rubric-based Agentic Reinforcement Learning

arXiv:2603.02637v2 Announce Type: replace-cross Abstract: Modern machine learning (ML) workloads increasingly rely on GPUs, yet achieving high end-to-end performance remains challenging due to depende

SwiftQK: Fast and Communication-Efficient Tensor Parallelism for Query-Key Normalization

arXiv:2608.09160v1 Announce Type: new Abstract: Query-Key Normalization (QK-Norm) improves the training stability and quality of modern Large Language Models (LLMs). However, under Tensor Parallelism

Research

Thought-Level Beam Search for Reasoning

arXiv:2608.08020v1 Announce Type: new Abstract: Test-time compute scaling is a primary driver of performance in large reasoning models (LRMs), but extreme inefficiency bounds current approaches, shift

researcharxiv-cs-ai

verdi: retrieval is not transfer for continual world model optimization

arXiv:2608.09537v1 Announce Type: new Abstract: Foundation world models have made remarkable progress in planning, simulation, and embodied intelligence. However, optimizing a pretrained world model t

CubicQuant: Parametric Non-Uniform Codebooks for High-Throughput LLM Inference with 1-8-Bit Weights

arXiv:2608.06763v1 Announce Type: new Abstract: Weight quantization for large-language-model inference must balance adaptive reconstruction levels with representations regular enough for efficient GPU

Fast LapSum: Exact Differentiable Top-k at Million Scale

arXiv:2608.06912v1 Announce Type: new Abstract: The top-k operation is a fundamental building block of modern sparse computation, enabling token routing, expert activation, memory selection, and atten

Scalable High-Fidelity Macromolecular Docking for GPU-Accelerated Supercomputers

arXiv:2608.07078v1 Announce Type: cross Abstract: Flexible macromolecular docking offers high-fidelity predictions of biomolecular interactions, but remains prohibitively expensive at scale. Among exi

Summarize First, Download Later: Onboard VLMs for Bandwidth-Efficient Earth Observation

arXiv:2608.06959v1 Announce Type: new Abstract: Modern Earth observation (EO) satellites carry increasingly advanced sensors that produce vast volumes of high-resolution, multispectral data, yet downl

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

arXiv:2512.02551v4 Announce Type: replace-cross Abstract: In this paper, we propose CUDA-L2, a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimi

IcFuzz: Fuzzing Isaac Sim with Semantic Stage Guidance and Multi-level Mutation

arXiv:2608.06088v1 Announce Type: new Abstract: Robotics simulators serve as a foundational infrastructure for embodied AI, facilitating safe and scalable robotic system development. NVIDIA Isaac Sim

Learning to Rank Tensor Network Contraction Plans for GPU-Accelerated Quantum Circuit Simulation

arXiv:2608.05819v1 Announce Type: new Abstract: Classical simulation remains essential for developing and validating quantum algorithms, but its cost grows rapidly with circuit size. Tensor-network co

PaDoc: Layout-Grounded Parallel Decoding for Document Parsing

arXiv:2608.06146v1 Announce Type: new Abstract: End-to-end document parsers provide a unified interface, but serialize page layouts and regional contents into one autoregressive sequence. This formula

AI-based single-shot structured-light depth reconstruction for real-time laparoscopic surgical guidance

arXiv:2608.05109v1 Announce Type: cross Abstract: Significance. Accurate intraoperative depth perception is important for autonomous and semi-autonomous robotic laparoscopic surgery. Conventional frin

An Explainable LLM Agent Layer for Open-World Anomaly Detection in Oil Wells

arXiv:2608.04041v1 Announce Type: new Abstract: Open-World Learning (OWL) pipelines for oil well anomaly detection have recently been shown to combine autoencoder-based detection, multiclass classific

ContextMaster: Interactive Multi-Shot Video Creation via Fixed-Budget Sparse Context Routing

arXiv:2608.04956v1 Announce Type: new Abstract: Recent video models increasingly support generation, reference conditioning, and editing within a single model, yet typically expose them as separate op

GASP: GPU-Accelerated Safe Planner for Real-Time Collision-Aware Motion Generation with Latent Trajectory Sampling

arXiv:2608.04612v1 Announce Type: new Abstract: We present GASP, a GPU-Accelerated Safe Planner for real-time, collision-aware joint-space motion generation in known environments. GASP combines a clam

Gaussian-LIC2: LiDAR-Inertial-Camera Gaussian Splatting SLAM

arXiv:2507.04004v3 Announce Type: replace Abstract: This paper presents the first photo-realistic LiDAR-Inertial-Camera Gaussian Splatting SLAM system that simultaneously addresses visual quality, geo

RORA: Realistic Object Reconstruction with Articulation

arXiv:2608.04842v1 Announce Type: new Abstract: Replicating real-world environments into simulation by realistic visual representation like NeRF and 3D Gaussian Splatting (3DGS) has emerged as an effe

StaticSegFormer: An Efficient High-Performance Semantic Segmentation Based on Static Structured Pruning

arXiv:2608.04811v1 Announce Type: new Abstract: Structured pruning enhances the efficiency of deep neural networks (DNNs) by eliminating groups of parameters during inference. Previous methods mostly

Accelerating Dynamic Graph Clustering on GPU Architectures with cuGraph

arXiv:2608.03695v1 Announce Type: cross Abstract: This work addresses community detection in temporal networks through GPU-accelerated extensions of spectral clustering and modularity-based algorithms

AcceptMoE: Commitment-Weighted Self-Sizing Verifier Expert Sets for Efficient MoE Speculative Decoding

arXiv:2608.02989v1 Announce Type: cross Abstract: Speculative decoding verifies a tree of draft tokens in one target-model forward pass. For a mixture-of-experts (MoE) target, however, parallel verifi

Compound and Parallel Modes of Tropical Convolutional Neural Networks

arXiv:2504.06881v2 Announce Type: replace-cross Abstract: Convolutional neural networks (CNNs) are foundational to many state-of-the-art computer vision systems, yet their reliance on multiplication-i

Learning and Clustering on Temporal Graphs: Principles, Primitives, and Pooling

arXiv:2608.03696v1 Announce Type: new Abstract: This work focuses on the problem of learning on temporal graphs, with particular emphasis on the task of clustering: obtaining coarse-grained representa

LiLa-WAM: Lightweight Latent Reasoning World-Action Model for Robotic Manipulation

arXiv:2608.03701v1 Announce Type: cross Abstract: World-action modeling has emerged as a promising paradigm for robotic control, as it empowers models to go beyond reacting to observations and anticip

LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs

arXiv:2608.03036v1 Announce Type: cross Abstract: Large Language Models (LLMs) are integrated into software systems and AI services, making efficient LLM serving a concern for software engineering. Se

A Fortran General-Purpose Transpiler: Proof of Concept

arXiv:2608.00130v1 Announce Type: cross Abstract: Fortran has been the cornerstone of high-performance computing for decades and remains unmatched in many domains. Yet the language faces an expertise

Bole: Efficient Tree Speculation for Hybrid-Attention Language Models

arXiv:2608.01651v1 Announce Type: cross Abstract: Hybrid-attention large language models combine full attention with recurrent linear attention to reduce long-context inference costs, yet their autore

HetRoute Heterogeneous and Cost-aware Collaborative Routing Framework for Distributed Edge MoE Inference

arXiv:2608.00577v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have become a dominant architecture for large-scale AI services, yet deploying them over geo-distributed heterogeneous

MiniWorld: Democratizing the Training of Video World Models from Scratch

arXiv:2608.01127v1 Announce Type: new Abstract: Video world models predict future observations conditioned on historical observations and control signals, enabling long-horizon generation through auto

Model Releases

Nova: An End-to-End MLIR Compiler for Deep Learning

model-releasesarxiv-cs-lg

arXiv:2608.00029v1 Announce Type: cross Abstract: The performance of deep learning models at scale relies heavily on how effectively high-level mathematical operations are mapped to underlying physica

Partial FC: Training 10 Million Identities on a Single Machine

arXiv:2010.05222v3 Announce Type: replace Abstract: Training face recognition models with millions of identities is challenging because classifier storage, logit memory, and computation grow linearly

Stipple: Real-Time Incremental Gaussian Splatting with Visual-Inertial Tracking

arXiv:2608.00931v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) provides efficient rendering of photo-realistic scenes, but its heavy preprocessing and training steps make it a poor fit

Toward Geometry-Scalable Whole-Body Touch for Humanoids: A 3D-Printed Conformal EIT Skin

arXiv:2608.02080v1 Announce Type: new Abstract: Whole-body tactile sensing is a prerequisite for humanoids that operate in contact-rich human environments, but conventional taxel arrays scale poorly w

Event-Based Upper-Body Humanoid Teleoperation Under Challenging Illumination

arXiv:2607.29227v1 Announce Type: new Abstract: We present a real-time upper-body human-to-humanoid motion imitation framework driven by neuromorphic event-based vision. This work addresses practical

GPU-Accelerated ANNS: Quantized for Speed, Built for Change

arXiv:2601.07048v5 Announce Type: replace-cross Abstract: Approximate nearest neighbor search (ANNS) is a core problem in machine learning and information retrieval applications. GPUs offer a promisin

Implicit Machine Learning Force Fields Accelerate Molecular Dynamics Simulations

arXiv:2607.29158v1 Announce Type: cross Abstract: We introduce implicit machine learning force fields (I-MLFFs), which replace explicit stacks of neural network layers with self-consistent fixed-point

Point2Radio: A Foundation Model for Cross-Scene Radio Fields from Material-Aware Point Clouds

arXiv:2607.28994v1 Announce Type: cross Abstract: High-fidelity radio fields are typically simulated for every scene--transmitter configuration or fitted separately to each scene, failing to exploit p

Studying quantization trade-offs for efficient inference deployment in machine translation

arXiv:2607.29397v1 Announce Type: new Abstract: Deploying large language models in realistic server environments poses challenges, as the system needs to provide high-quality responses with low latenc