Knowledge catalogue
arXiv:2609.13566v1 Announce Type: new Abstract: Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational co
arXiv:2605.31281v1 Announce Type: new Abstract: As wind turbine fleets age, data-driven reliability engineering is essential to optimise their operation and maintenance for service life extension and
arXiv:2608.01819v1 Announce Type: new Abstract: To improve the operational readiness of combat aircraft engines and reduce unplanned maintenance costs, accurately estimating the remaining useful life
arXiv:2607.04786v1 Announce Type: cross Abstract: Test maintenance is a critical, yet costly, activity - particularly as codebases rapidly evolve. To assist, we present MAST, a multi-agent framework t
arXiv:2609.22583v1 Announce Type: new Abstract: Predictive maintenance in Industry 4.0 refers to using data from sensors, machines, and production systems to estimate when equipment is likely to fail,
arXiv:2609.23582v1 Announce Type: new Abstract: Maintenance work orders must often be processed offline on embedded hardware, yet downstream software requires predictable structured output. We present
arXiv:2609.24250v1 Announce Type: new Abstract: The shipping industry has a significant impact on the global economy, emphasizing the need for operational availability and safety through the use of ef
arXiv:2609.22360v1 Announce Type: new Abstract: Electrical submersible pumps (ESPs) are essential in offshore oil production, where unexpected failures can result in significant operational and financ
arXiv:2609.22229v1 Announce Type: new Abstract: We generated synthetic multivariate time series for 27 refrigerators with a simplified physicsinspired simulator at one-minute resolution. The simulator
arXiv:2609.22160v1 Announce Type: new Abstract: Semiconductor manufacturing relies on tightly interconnected components, so early identification of the assets most likely to fail is essential to preve
arXiv:2608.14491v1 Announce Type: cross Abstract: Network-level maintenance planning requires repeated evaluations of equilibrium traffic flows under road capacity reductions. While equilibrium traffi
arXiv:2604.27468v1 Announce Type: new Abstract: Maintaining information in context is essential in successful real-time language comprehension, but maintenance is cognitively costly and can slow proce
arXiv:2601.16737v2 Announce Type: replace Abstract: Highway networks are crucial for economic prosperity. Climate change-induced temperature fluctuations are exacerbating stress on road pavements, res
arXiv:2604.18399v1 Announce Type: new Abstract: Daily infrastructure management in preparation for disasters is critical for urban resilience. When bridges remain resilient against disaster-induced ex
arXiv:2609.20535v1 Announce Type: new Abstract: Deep learning predictive maintenance models suffer from poor transferability across machines and operating conditions, especially when labelled data are
arXiv:2609.17124v1 Announce Type: new Abstract: Offshore maintenance requires operations in the air, the surface, and the subsea domain and include human supervision. This paper presents LOTUSim-Energ
arXiv:2609.16267v1 Announce Type: cross Abstract: Many operational cases are documented more than once, at different workflow stages and for different purposes, yet model evaluations normally select o
arXiv:2609.07533v1 Announce Type: new Abstract: In data-driven predictive maintenance (PdM), feature extraction is usually treated as fixed preprocessing: a descriptor set is chosen once and reused wh
arXiv:2601.09721v2 Announce Type: replace-cross Abstract: Consumer artificial intelligence chatbots are now accessed by hundreds of millions of users seeking health information, yet systematic evaluat
arXiv:2609.05677v1 Announce Type: cross Abstract: Lifelong LLM agents increasingly rely on external skill artifacts as one element for preserving and reusing capabilities over time. These skills (usua
arXiv:2506.03828v4 Announce Type: replace Abstract: AI for Industrial Asset Lifecycle Management aims to automate complex operational workflows, such as condition monitoring and maintenance scheduling
arXiv:2608.29310v1 Announce Type: cross Abstract: Organizations often develop and maintain portfolios of related applications: independently deployable codebases that share substantial domain logic, i
arXiv:2608.31102v1 Announce Type: cross Abstract: Industrial post-training is a brownfield regime. Teams inherit a deployed checkpoint and must land targeted improvements under fixed compute and mixtu
arXiv:2606.29469v1 Announce Type: new Abstract: While robust map maintenance has advanced significantly, existing studies have focused on specific tasks, especially dynamic object removal or change de
arXiv:2603.12703v3 Announce Type: replace Abstract: Video understanding requires models to continuously track and update world state during playback. Although existing benchmarks have advanced video u
arXiv:2606.28720v1 Announce Type: new Abstract: Lifelong scene mapping under rigid object rearrangement remains a fundamental challenge in robotics. While 3D Gaussian Splatting (3DGS) enables high-fid
arXiv:2606.27808v1 Announce Type: new Abstract: A minute lexical variation can reverse the procedural meaning of an instruction even when the rest of the sentence remains unchanged. In automotive main
arXiv:2605.14318v1 Announce Type: new Abstract: Predictive maintenance in complex systems is often complicated by the heterogeneity and redundancy of monitored variables,which can obscure fault-releva
arXiv:2604.23446v1 Announce Type: new Abstract: Industrial maintenance environments increasingly rely on AI systems to assist operators in understanding asset behavior, diagnosing failures, and evalua
arXiv:2604.11754v1 Announce Type: cross Abstract: In this work, we study angle-based localization and rigidity maintenance control for multi-robot networks under sensing constraints. We establish the
arXiv:2609.33641v1 Announce Type: cross Abstract: Several businesses apply maintenance, repair, and overhaul (MRO) principles to the life-cycle of their existing products. In cases like casted gas tur
arXiv:2609.35416v1 Announce Type: new Abstract: Continuous video counting requires distinguishing new observations from new objects or completed events. We introduce StaMina (State Maintenance), which
arXiv:2609.34498v1 Announce Type: new Abstract: Long-term human habitation and in-situ development on the Moon open a new era of space utilization. In this context, robots are a key technology for fac
arXiv:2609.35257v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization offers a memory-efficient alternative for LLM fine-tuning by estimating updates only from forward evaluations of perturbe
arXiv:2609.18935v1 Announce Type: new Abstract: A game character should not have to reread its entire life before every conversation. For locally deployed language-model characters, however, revising
arXiv:2609.04840v1 Announce Type: new Abstract: Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal operating-regime variation over planning wind
arXiv:2607.08177v1 Announce Type: new Abstract: In this paper, we study the automatic schema generation problem: given a collection of historical ship maintenance and operational reports across multip
arXiv:2603.13343v3 Announce Type: replace-cross Abstract: Predictive maintenance for connected vehicles offers the potential to reduce unexpected breakdowns and improve fleet reliability, but most exi
arXiv:2605.24953v1 Announce Type: new Abstract: Industrial asset operations and maintenance question answering is inherently multi-turn, iterative, and highly dependent on external tool invocation. Ho
arXiv:2605.24294v1 Announce Type: cross Abstract: Android malware detectors often degrade after deployment because of concept drift, while full retraining at each maintenance step is costly. We propos
arXiv:2604.06770v1 Announce Type: cross Abstract: Maintenance procedures in manufacturing facilities are often documented as flowcharts in static PDFs or scanned images. They encode procedural knowled
arXiv:2510.05524v2 Announce Type: replace Abstract: We present Knowledge Extraction on OMIn (KEO), a domain-specific knowledge extraction and reasoning framework with large language models (LLMs) in s
arXiv:2608.01772v2 Announce Type: replace Abstract: LLM agents increasingly run policy-bound enterprise workflows, where they must apply rules consistently and stay auditable. Deploying such an agent
arXiv:2608.08896v1 Announce Type: new Abstract: Imaging device downtime is a major barrier to healthcare delivery in low- and middle-income countries (LMICs), often driven by limited access to special
arXiv:2607.21444v1 Announce Type: cross Abstract: Reliable electric vehicle (EV) charging infrastructure is a cornerstone of sustainable, low-carbon cities, yet urban climate stress such as extreme he
arXiv:2605.02163v1 Announce Type: cross Abstract: Software documentation frequently drifts from executable logic as codebases evolve, creating technical debt that degrades maintainability and causes d
arXiv:2604.13102v1 Announce Type: cross Abstract: Enterprise software organizations face an escalating challenge in maintaining the integrity, security, and freshness of codebases that span hundreds o
arXiv:2605.15537v1 Announce Type: new Abstract: This paper introduces RTL-BenchMT, an agentic framework for dynamically maintaining RTL generation benchmarks. Large Language Models (LLMs) assisted aut
arXiv:2605.08614v1 Announce Type: new Abstract: Monitoring complex industrial assets relies on engineer-authored symbolic rules that trigger based on sensor conditions and prompt technicians to perfor
arXiv:2605.07860v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for preserving client data ownership and control over distributed Internet of Things (IoT)
arXiv:2511.14791v2 Announce Type: replace-cross Abstract: Early detection of faults in district heating substations is imperative to reduce return temperatures and enhance efficiency. However, progres
arXiv:2609.40071v1 Announce Type: cross Abstract: Digital twins increasingly support downstream analytical tasks that depend on time-series data, motivating interest in time-series foundation models (
arXiv:2609.29735v1 Announce Type: new Abstract: Long-horizon tasks require preserving and later recovering cross-session evidence under a bounded, query-blind memory budget. Existing compression can d
arXiv:2609.29545v1 Announce Type: new Abstract: Deployed agents run on handed-over knowledge: a frozen policy consults a briefing of consolidated items written before the stream begins. The world then
arXiv:2605.20742v1 Announce Type: new Abstract: With the rapid proliferation of electric vehicles, the safety and reliability of lithium-ion batteries have become critical concerns. Effective anomaly
arXiv:2610.06128v1 Announce Type: new Abstract: Predictive maintenance requires reliable remaining useful life (RUL) estimation. Existing methods mainly follow two paradigms: wear-based aging models t
arXiv:2609.06194v1 Announce Type: cross Abstract: Offshore wind turbines are widely used to generate renewable energy, but their maintenance can result in decreased efficiency due to forced shutdowns.
arXiv:2607.24551v1 Announce Type: new Abstract: Maintenance regulations are complex legal texts that are difficult to exploit when addressing a specific case and challenging to integrate into operatio
arXiv:2607.11957v1 Announce Type: new Abstract: Maintenance of critical infrastructures, such as railways and power plants, is essential for ensuring operational safety and reliability. However, the d
arXiv:2606.21364v1 Announce Type: new Abstract: Accurate prediction of repair duration is an important challenge in product maintenance due to its implications for resource allocation, customer satisf