Search: “automated”

arXiv:2609.31540v1 Announce Type: cross Abstract: Sending every network-automation input to a third-party frontier LLM exports sensitive artifacts such as production configurations, topologies, and lo

arXiv:2609.26580v1 Announce Type: new Abstract: The repeated forward-reverse maneuvers performed by wheel loaders during earthmoving operations make them well suited for automation. However, the nonli

arXiv:2606.19795v2 Announce Type: replace-cross Abstract: Electronic design automation (EDA) is multi-stage and handoff-heavy, relying on transfers among humans, design artifacts, and multiple tools.

arXiv:2608.26199v1 Announce Type: new Abstract: We ask whether AI agents powered by locally deployed large language models can reliably automate expert-defined hardware design workflows in an industry

arXiv:2608.26091v1 Announce Type: cross Abstract: Civil infrastructure compliance checking has long relied on engineers manually reading legacy 2D plans; however, OCR-based automation strips away the

arXiv:2508.07617v2 Announce Type: replace-cross Abstract: AI has the potential to augment human decision making. However, even high-performing models can produce inaccurate predictions when deployed.

arXiv:2608.08577v1 Announce Type: new Abstract: Fraud operations must allocate events among automatic approval, analyst review, and automatic blocking even though the labels needed to evaluate these a

arXiv:2608.02254v2 Announce Type: replace Abstract: exttt{Homebot} is a locally deployable AI agent for conversational household assistance and automation. It accepts voice and instant-messaging reque

arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.

arXiv:2604.07263v2 Announce Type: replace-cross Abstract: Existing driving automation (DA) systems on production vehicles rely on human drivers to decide when to engage DA while requiring them to rema

arXiv:2506.12339v2 Announce Type: replace-cross Abstract: We present SheetMind, a modular multi-agent framework powered by large language models (LLMs) for spreadsheet automation via natural language

arXiv:2602.12966v2 Announce Type: replace Abstract: Understanding how and why large language models (LLMs) fail is becoming a central challenge as models rapidly evolve and static evaluations fall beh

arXiv:2605.30914v1 Announce Type: new Abstract: Automated formal verification remains challenging for large language models because data for proof assistants and verification-aware languages is scarce

arXiv:2605.16679v1 Announce Type: cross Abstract: End-to-end automation of realistic healthcare operations stresses three capabilities underrepresented in current benchmarks: policy density, decisions

arXiv:2605.17617v1 Announce Type: new Abstract: Complex operational workflows coordinating personnel, tools, and information are central to enterprise operations, yet end-to-end automation remains cha

arXiv:2605.11518v1 Announce Type: cross Abstract: Effectively configuring scalable large language model (LLM) experiments, spanning architecture design, hyperparameter tuning, and beyond, is crucial f

arXiv:2605.09675v1 Announce Type: new Abstract: Clinical reasoning agents based on large language models (LLMs) aim to automate tasks such as intensive care unit (ICU) monitoring and patient state tra

arXiv:2605.03202v1 Announce Type: new Abstract: Large language models offer a tempting solution to address the peer review crisis. This position paper argues that today's AI systems should not be used

arXiv:2604.22235v1 Announce Type: cross Abstract: Industrial robots are widely used in manufacturing, yet most manipulation still depends on fixed waypoint scripts that are brittle to environmental ch

arXiv:2601.14541v4 Announce Type: replace-cross Abstract: This report distills the discussions and recommendations from the NSF Workshop on AI for Electronic Design Automation (EDA), held on December

arXiv:2604.21910v1 Announce Type: new Abstract: Scientific workflow systems automate execution -- scheduling, fault tolerance, resource management -- but not the semantic translation that precedes it.

arXiv:2604.14661v1 Announce Type: cross Abstract: Edge AI model deployment is a multi-stage engineering process involving model conversion, operator compatibility handling, quantization calibration, r

arXiv:2603.27195v2 Announce Type: replace Abstract: Designing microstructures with coupled cross-physics objectives is a fundamental challenge where traditional topology optimization is often computat

arXiv:2604.08588v1 Announce Type: cross Abstract: Effective automation hinges on deciding when to act and when to escalate. We model this as a decision under uncertainty: an LLM forms a prediction, es

arXiv:2604.07240v1 Announce Type: cross Abstract: We introduce a code-based challenge for automated, open-ended mathematical discovery based on the k-server conjecture, a central open problem in com

arXiv:2609.34586v1 Announce Type: cross Abstract: Deploying LLM-enabled agentic applications across the Edge-to-Cloud continuum remains challenging due to hardware heterogeneity, deployment complexity

arXiv:2609.28557v1 Announce Type: new Abstract: DNA sequencing pipelines, spanning quality control, alignment, variant calling, and annotation, are now reliably executed by workflow management systems

arXiv:2509.15959v2 Announce Type: replace-cross Abstract: Autonomous navigation in maritime domains is accelerating alongside advances in artificial intelligence, sensing, and connectivity. Opaque dec

arXiv:2608.23336v1 Announce Type: new Abstract: Developing competitive deep learning baselines for medical imaging remains a highly iterative process requiring literature review, implementation, exper

arXiv:2606.16465v2 Announce Type: replace Abstract: AI agents can now take irreversible actions in operational systems, but agent-caused losses are still not clearly assigned, priced, or transferred.

arXiv:2608.09185v1 Announce Type: cross Abstract: Enterprise data warehouses (DWs) support business-critical analytics, but warehouse task delivery remains a complicated production process involving c

arXiv:2607.05369v1 Announce Type: cross Abstract: For robots to work reliably in commercial and industrial applications, can recent advances in agentic coding systems combine interpretable robot progr

arXiv:2606.30111v1 Announce Type: cross Abstract: Embodied agents are typically built as hand-designed compositions of perception, memory, planning, and action modules. This modularity exposes a large

arXiv:2606.12207v1 Announce Type: cross Abstract: Embodied intelligence now spans navigation, household assistance, manipulation, autonomous driving, aerial agents, and multimodal large-model control.

arXiv:2605.27486v1 Announce Type: new Abstract: Federated learning (FL) has broadened the horizon for multivariate time series anomaly detection (MTSAD). However, benchmarking such anomaly detection m

arXiv:2605.23204v1 Announce Type: new Abstract: Scientific research is being reshaped by AI systems that move beyond isolated assistance toward longer-horizon workflows spanning literature grounding,

arXiv:2605.20176v1 Announce Type: new Abstract: Large language models (LLMs) and agentic systems have shown promise for clinical decision support, but existing works largely assume that evidence has a

arXiv:2605.11378v1 Announce Type: new Abstract: Agent evaluation requires assessing complex multi-step behaviors involving tool use and intermediate reasoning, making it costly and expertise-intensive

arXiv:2409.13107v3 Announce Type: replace Abstract: Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning compl

arXiv:2605.02592v1 Announce Type: new Abstract: Foundation models, particularly large language models, are increasingly integrated into agent architectures for industrial tasks such as decision suppor

arXiv:2604.20134v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) increasingly encounter difficulties in correlating heterogeneous alerts, interpreting multi-stage attack progressio

arXiv:2510.10074v2 Announce Type: replace Abstract: Effective incident management in large-scale IT systems relies on troubleshooting guides (TSGs), but their manual execution is slow and error-prone.

arXiv:2604.06231v1 Announce Type: cross Abstract: Database systems incorporate an ever-growing number of functions in their kernels (a.k.a., database native functions) for scenarios like new applicati

arXiv:2610.14163v1 Announce Type: cross Abstract: Terminal agents solve tasks in software engineering and scientific research by executing commands in a terminal. Training them via reinforcement learn

arXiv:2603.25063v2 Announce Type: replace-cross Abstract: Recent agentic systems demonstrate that large language models can generate complex codebases from natural language prompts. Despite this progr

arXiv:2610.11312v1 Announce Type: new Abstract: Large-scale construction of medical vision-language model (VLM) benchmarks is increasingly feasible with richly annotated imaging datasets and large lan