Search: “deployment”

arXiv:2604.27789v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used as core dependencies in software systems. However, the hosted LLM services evolve continuously thro

arXiv:2604.19468v1 Announce Type: cross Abstract: Fairness audits of institutional risk models are critical for understanding how deployed machine learning pipelines allocate resources. Drawing on mul

arXiv:2609.15422v1 Announce Type: new Abstract: AI agents are provisioned the same as employee-owned hosts in many enterprise settings with a static credential set fixed at deployment which includes a

arXiv:2608.07091v1 Announce Type: cross Abstract: Edge Artificial Intelligence (Edge AI) enables the deployment of AI models directly on local edge devices, while such deployments are subject to stric

arXiv:2610.13862v1 Announce Type: new Abstract: Deploying language-model agents onboard mobile robots requires task reasoning and responsive execution within limited compute and memory. We propose BT-

arXiv:2610.10827v1 Announce Type: cross Abstract: Corrective feedback is among the best-evidenced drivers of second-language acquisition, yet corrections delivered during lessons rarely accumulate int

arXiv:2610.11764v1 Announce Type: new Abstract: Reliable crop-row perception is essential for autonomous agricultural robots, but low-cost deployment is constrained by computation, memory, power, and

arXiv:2610.08864v1 Announce Type: cross Abstract: Machine learning-based intrusion detection systems (IDS) are increasingly used in resource-constrained Internet of Things (IoT) environments, yet thei

arXiv:2610.08259v1 Announce Type: new Abstract: Autonomous aerial parcel collection remains constrained by package-transfer operations that require manual loading, landing, or dedicated ground infrast

arXiv:2610.02497v1 Announce Type: new Abstract: Electromyography (EMG) signals vary substantially across individuals, body regions, recording sessions, and sensing hardware, limiting the generalizatio

arXiv:2609.34904v1 Announce Type: new Abstract: Graph neural networks (GNNs) need to exploit improved message passing without surrendering control over predictions already trusted in deployment. We in

arXiv:2608.00008v2 Announce Type: replace Abstract: The local deployment of large language models (LLMs) is gaining traction due to privacy concerns and the desire for on-premise inference. However, t

arXiv:2609.26981v1 Announce Type: new Abstract: We describe deploying imaging AI at six hospitals through PACS-AI, an open self-hosted platform. The binding constraint is not model accuracy but infras

arXiv:2609.25614v1 Announce Type: new Abstract: This article presents a bimanual teleoperation pipeline and conceptual design of a deployable four-finger payload for intra-vehicular free-flyers. Futur

arXiv:2609.21045v1 Announce Type: new Abstract: Collecting real-world robot data for dexterous manipulation is costly and time-consuming. While high-fidelity physics simulators enable scalable data sy

arXiv:2608.29615v1 Announce Type: cross Abstract: Across industries, machine-learning systems support applications ranging from prediction and anomaly detection to forecasting, optimization, and sched

arXiv:2608.23987v1 Announce Type: new Abstract: Virtual sensing enables digital twins and safety-critical systems to reconstruct and forecast spatial-temporal physics in real time. However, convention

arXiv:2608.22048v1 Announce Type: new Abstract: Large language models are increasingly deployed on local hardware for privacy, cost, and accessibility reasons. Yet many evaluations emphasize accuracy

arXiv:2608.08829v1 Announce Type: cross Abstract: Activation steering edits the behaviour of a frozen language model by adding a learned vector to its residual stream, and current practice fixes the i

arXiv:2608.06867v1 Announce Type: new Abstract: No single large language model (LLM) is optimal across all queries and budget constraints, making model routing essential for cost-effective deployment.

arXiv:2608.06110v1 Announce Type: new Abstract: This paper presents ECHO (Enhanced Care & Health Observer), a locally-deployable conversational health assistant for long-term chronic care management.

arXiv:2606.11949v1 Announce Type: new Abstract: We present an online monitoring system for distributional shift in deployed safety classifiers, using calibrated sequential statistics to detect when a

arXiv:2606.04029v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has received increasing attention and adoption in real-world use cases. Most of these systems follow a train-then-fix para

arXiv:2604.01802v2 Announce Type: replace Abstract: Real-time inference of inaccessible interior physical fields from sparse boundary observations is a fundamental but unresolved problem in scientific

arXiv:2605.22331v1 Announce Type: new Abstract: Despite strong predictive results in the clinical machine learning literature, the translation of these models into bedside use remains limited by syste

arXiv:2605.20591v1 Announce Type: new Abstract: Medical large language models (LLMs), including custom medical GPTs (MedGPTs) and open-source models, are increasingly deployed on web platforms to prov

arXiv:2512.08237v3 Announce Type: replace Abstract: The advancement of vision-only Bird's-Eye-View (BEV) perception, a core paradigm for cost-effective autonomous driving, is hindered by the long-stan

arXiv:2509.12266v2 Announce Type: replace-cross Abstract: We introduce Genome-Factory, the first integrated Python library for tuning, deploying, and interpreting genomic foundation models. Our core c

arXiv:2605.11629v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown strong chain-of-thought (CoT) reasoning ability on vision-language tasks, but their direct de

arXiv:2604.23670v1 Announce Type: new Abstract: Motivated by the limited generalization of supervised image matching models to unseen image domains, we explore the zero-shot deployment of DINO feature

arXiv:2604.23341v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exp

arXiv:2604.12833v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable performance, yet their security remains insufficiently understood. Existing adversarial studies focu

arXiv:2610.12815v1 Announce Type: new Abstract: RDMA can reduce communication overhead in distributed machine learning systems, but realizing these benefits in production requires more than replacing

arXiv:2610.02679v1 Announce Type: new Abstract: Data journalism, the practice of using data analysis to surface newsworthy stories, depends increasingly on the ability of reporters and investigative j

arXiv:2606.15846v2 Announce Type: replace Abstract: Training Deep Reinforcement Learning (DRL) navigation policies for different robot configurations remains time-consuming. We present FlashNav, a GPU

arXiv:2610.00007v1 Announce Type: cross Abstract: Named-entity recognition (NER) is increasingly wanted on-device (no API, low latency, data kept local). The practitioner's question is not the leaderb

arXiv:2609.35810v1 Announce Type: cross Abstract: Large language models are increasingly used in oncology applications, but their predictions are often weakly grounded in explicit medical structure. W

arXiv:2609.31629v1 Announce Type: cross Abstract: Structured phenotype extraction from radiology reports supports cohort construction, quality auditing, and clinical analytics, but practical deploymen

arXiv:2609.28933v1 Announce Type: new Abstract: Outdoor robots require more than an accurate receiver and a path-tracking law: the navigation system must preserve geometric consistency from geographic

arXiv:2609.27359v1 Announce Type: new Abstract: Vietnam's Personal Data Protection Law (Law No. 91/2025/QH15) and Decree No. 356/2025/ND-CP, effective January 1, 2026, require organizations to establi

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:2609.12839v2 Announce Type: replace-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posin

arXiv:2609.03590v1 Announce Type: cross Abstract: Timely delivery of delay-sensitive information over dynamic, heterogeneous networks is essential for NextG interactive applications, yet providing str

arXiv:2608.31117v1 Announce Type: cross Abstract: Generative models have become central across science and industry, from image and text synthesis to the design of molecules and materials. Quantum gen

arXiv:2608.28151v1 Announce Type: new Abstract: A byte-level BPE tokenizer is an ordered list of merge rules, so applying only a prefix yields a vocabulary whose token identifiers are the first rows o

arXiv:2608.10694v1 Announce Type: cross Abstract: Evolutionary optimization of LLM prompts and agentic programs (e.g., GEPA) is dominated by fitness evaluation: scoring each candidate runs an answerin