Search: “industry”

arXiv:2604.09932v1 Announce Type: cross Abstract: Hybrid approaches that combine data-driven learning with physics-based insight have shown promise for improving the reliability of industrial conditio

arXiv:2604.10248v1 Announce Type: new Abstract: Complex systems such as aircraft engines, turbines, and industrial machinery often operate under dynamically changing conditions. These varying operatin

arXiv:2610.13145v1 Announce Type: new Abstract: Large language models (LLMs) increasingly generate structured layouts and executable scene programs from natural-language instructions. However, executa

Standard Bots develops AI‑native industrial robot arms (used for machine tending, welding, assembly) that rely on a shared pretrained base model with 1–2 billion parameters. The model is adapted to ea

arXiv:2610.07016v1 Announce Type: cross Abstract: In few-shot industrial anomaly detection, the few normal target images provide no direct defect supervision, making anomaly prompts difficult to learn

Breakthroughs on every frontier. I can't wait to share more on what Praxis-1 will unlock across industries. Media Introducing Praxis-1, an open-weight World Action Model that turns our video pre-train

arXiv:2609.37314v1 Announce Type: new Abstract: Synthetic anomaly generation helps expand industrial anomaly datasets when real defects are scarce or unavailable. Existing approaches lie at two extrem

OpenAI: OpenAI is adopting a structured “safety case” documentation framework modeled after industries like aviation and nuclear power to govern frontier RL training — Loading... We believe we are ent

arXiv:2609.30805v1 Announce Type: cross Abstract: Industrial control system (ICS) threats documented for one plant can express cyber-physical effects relevant to another, but semantic similarity alone

arXiv:2609.30001v1 Announce Type: new Abstract: Sustaining industrial recommendation research requires using the results of one experiment to decide what to investigate next. We present AgentX-Model,

Learn how to build a synthetic data augmentation pipeline on Amazon SageMaker AI and Amazon Rekognition that generates photo-realistic, auto-labeled training images for industrial safety AI. This appr

arXiv:2609.13234v1 Announce Type: new Abstract: Industrialized construction imposes stringent precision requirements on robotic assembly of modular components such as prefabricated window units. In to

Kai Nicol-Schwarz / CNBC: Netherlands-based inference chip startup Euclyd raised a €200M+ Series A co-led by Samsung, Somerset Capital, Scaleup Europe Fund, and Innovation Industries — Samsung has bac

arXiv:2609.11752v1 Announce Type: cross Abstract: For industrial content risk control, the real deployment constraint is not average accuracy but how much risk can be auto-handled under high precision

arXiv:2609.10339v1 Announce Type: new Abstract: A confidence-aware multimodal fusion framework (CAMF) is proposed to realize reliable human intention prediction for industrial human-robot collaboratio

arXiv:2609.08970v1 Announce Type: new Abstract: Industrial fraud detection often relies on costly expert-crafted features that overlook graph-structured relational signals, while GNNs often do not mee

Reuters: The NSA, CISA, and FBI issue a joint advisory warning that Chinese AI companies, including DeepSeek, are conducting “industrial-scale” distillation campaigns — The U.S. government on Tuesday

arXiv:2609.04871v1 Announce Type: new Abstract: Improving an industrial recommender is an iterative research-and-engineering process rather than a direct path from idea to deployment. In extbf{DASHEN,

arXiv:2608.23723v1 Announce Type: new Abstract: Few-shot anomaly detection (FSAD) has recently benefited from vision-language models such as CLIP, which enable anomaly de?tection by aligning visual fe

arXiv:2608.22968v1 Announce Type: new Abstract: Industrial monitoring models must detect operationally relevant deviations while satisfying target-specific data, calibration, and resource constraints.

arXiv:2608.21792v1 Announce Type: new Abstract: Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-go

arXiv:2608.22089v1 Announce Type: cross Abstract: Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security

arXiv:2601.22754v2 Announce Type: replace-cross Abstract: Industrial troubleshooting guides encode diagnostic procedures in flowchart-like diagrams where spatial layout and technical language jointly

arXiv:2608.23547v1 Announce Type: cross Abstract: Machine-learning-based anomaly detection is increasingly used in industrial control systems (ICS), yet most studies assume that detector training data

Control is becoming the defining topic in enterprise AI adoption. Across the world, and especially in regulated industries, organizations want the benefits of AI without giving up control over their s

arXiv:2608.17962v1 Announce Type: new Abstract: Recent progress in robotic learning has been fueled by large-scale datasets collected in everyday environments. However, most existing datasets emphasiz

arXiv:2608.14666v1 Announce Type: new Abstract: Unsupervised fault detection in industrial systems is dominated by reconstruction based methods that monitor individual sensor marginal distributions. T

arXiv:2608.15090v1 Announce Type: new Abstract: Studies of industrial visual inspection commonly report the area under the receiver operating characteristic curve (AUROC) and the overlap between anoma

arXiv:2608.09789v1 Announce Type: new Abstract: Industrial anomaly detection (IAD) requires identifying fine-grained deviations from normal visual patterns. Multimodal large language models (MLLMs) ca

arXiv:2608.05235v1 Announce Type: cross Abstract: Research agents increasingly conduct multi-round machine-learning experiments in industrial recommendation settings and retain the resulting trajector

arXiv:2608.03866v1 Announce Type: new Abstract: This white paper presents ADMITBench, a reference framework for evaluating industrial LLM advisories at the level of the proposed action. The framework

arXiv:2608.03150v1 Announce Type: new Abstract: Generative retrieval (GR) is a promising paradigm for industrial search advertising, yet its deployment is constrained by strict relevance and latency r

arXiv:2607.29533v1 Announce Type: new Abstract: Industrial anomaly detection and localization are limited by scarce real anomalies and pixel-level annotations, a bottleneck that synthetic image-mask p

arXiv:2505.22039v2 Announce Type: replace Abstract: While anomaly detection has made significant progress, generating detailed analyses that incorporate industrial knowledge remains a challenge. To ad

arXiv:2601.17303v2 Announce Type: replace Abstract: As Industrial Internet of Things (IIoT) environments scale to tens of thousands of connected devices, centralized security architectures introduce l

arXiv:2508.21797v2 Announce Type: replace-cross Abstract: Industry 4.0's highly networked Machine Tool Controllers (MTCs) are prime targets for replay attacks that use outdated sensor data to manipula

arXiv:2607.18850v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have recently shown strong potential for industrial anomaly detection (IAD) by providing image-level anomaly judgme

Mistral is announcing an expanded global strategic partnership with @Microsoft to give enterprises and regulated industries frontier AI they can control. As Mistral is expanding its AI compute capacit

arXiv:2607.07883v1 Announce Type: new Abstract: There is relatively little, public, and model-ready data on industrial machinery for African economies. This makes it hard to do quantitative analysis o

arXiv:2607.03817v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) show strong few-shot generalization, but industrial anomaly detection remains difficult because defects are small, input

arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit

arXiv:2607.03701v1 Announce Type: cross Abstract: Large language models (LLMs) can propose circuit-optimization decisions, but industrial analog flows cannot expose foundry PDK content, proprietary sc

Customers are not an abstraction for us: we exist to help enterprises, public institutions, and industries build their own intelligence, so the value created from their data, workflows, feedback, and

arXiv:2607.00591v1 Announce Type: new Abstract: With the increasing deployment of heterogeneous robot fleets in industrial environments, efficient coordination remains a critical challenge. Real-time

arXiv:2606.31163v1 Announce Type: cross Abstract: Large language models deployed in regulated industries operate under two constraints: compliance enforcement and cost efficiency. Personally identifia

arXiv:2506.00599v3 Announce Type: replace Abstract: While current 6D pose estimation benchmarks have reached near-saturation on household objects, they often fail to capture the stochastic and optical