Search: “applications”

As a business intelligence user, this probably sounds familiar: Most dashboards only provide you with a standardized canvas and a fixed library of charts, and the “analysis” consists of a CSV export t

arXiv:2509.02302v2 Announce Type: replace Abstract: We study history-dependent online problems with a possibly inaccurate prediction of the future request sequence. Motivated by several real-world app

arXiv:2610.11863v1 Announce Type: cross Abstract: Kernel Stein discrepancies (KSDs) provide a versatile tool for comparing distributions. One of their main applications is in quantifying the goodness-

arXiv:2610.11934v1 Announce Type: cross Abstract: Industrial environments are increasingly characterized by the tight interaction among physical processes, communication infrastructures, and intellige

arXiv:2610.11308v1 Announce Type: new Abstract: Accurate and reliable relative localization is crucial for multi-robot applications like exploration, search, and rescue missions. LiDAR-based solutions

arXiv:2610.11104v1 Announce Type: new Abstract: Accurate segmentation of thin curvilinear structures is vital for various real-world applications, from vessel analysis to road extraction. Yet their in

arXiv:2610.11957v1 Announce Type: cross Abstract: Conformal prediction offers a distribution-free coverage guarantee, making it especially attractive for clinical applications. Standard conformal pred

arXiv:2610.10227v1 Announce Type: cross Abstract: While Large Language Models (LLMs) possess rich world knowledge and impressive generalization capabilities, their direct application to tabular data c

arXiv:2610.06980v1 Announce Type: new Abstract: Sensing technologies have advanced rapidly across industries ranging from energy to automotive manufacturing. These systems generate high-dimensional (H

arXiv:2610.06936v1 Announce Type: new Abstract: Irregular multivariate time series forecasting is a challenging yet important problem in real-world applications, where observations are often irregular

arXiv:2610.06809v1 Announce Type: new Abstract: Causal representation learning (CRL) is the process of recovering causally-related latent variables from high-dimensional observations. As a label-free

arXiv:2610.05825v1 Announce Type: new Abstract: Classification problem in the context of highly imbalanced data is a major challenge in many real-world applications (e.g., FinTech, healthcare, etc.).

arXiv:2410.16089v3 Announce Type: replace Abstract: The cost, flexibility, and efficiency of modern UAVs make them attractive across many applications, but their proliferation has driven a rising numb

arXiv:2609.40075v1 Announce Type: new Abstract: Partial Optimal Transport (POT) extends the classical optimal transport problem by relaxing the strict mass conservation constraint, enabling its use in

arXiv:2609.39294v1 Announce Type: new Abstract: Precise numerical reasoning with Large Language Models (LLMs) is essential for expanding their applicability to complex real-world tasks. However, text-

arXiv:2512.22819v2 Announce Type: replace Abstract: Panoramic depth estimation captures the complete 360^irc scene geometry, being essential for robotics and AR/VR applications. While perspective dept

arXiv:2609.38760v1 Announce Type: new Abstract: Scalable robotic fleets have become increasingly popular for various applications such as package delivery, warehouse management, and military operation

arXiv:2609.38538v1 Announce Type: cross Abstract: Random splitting can yield non-independent train--test subsets when a dataset contains related samples, as is common in certain applications such as b

arXiv:2602.06700v2 Announce Type: replace-cross Abstract: Graph-structured data underpin a wide spectrum of modern applications, yet their multiple sensitive attributes are not isolated but deeply cou

arXiv:2510.17611v3 Announce Type: replace Abstract: Unsupervised anomaly detection (UAD) has evolved from specialized single-class models to unified multi-class models, yet existing multi-class models

arXiv:2609.31653v1 Announce Type: cross Abstract: Sentiment analysis is a common tool for converting unstructured text into quantitative signals in finance and risk management. Yet most applications r

arXiv:2609.33530v1 Announce Type: cross Abstract: Natural Language Understanding (NLU) plays a crucial role in various applications, yet its performance suffers from weaknesses in handling the complex

As threat actors increasingly use AI to accelerate and develop cyberattacks, enterprise defenders need to rely on both AI and a critical defender’s advantage: Business context that only you possess. E

arXiv:2609.33096v1 Announce Type: new Abstract: Rapid advances in humanoid robotics have motivated growing interest in the application of humanoids for healthcare and clinical tasks. However, it remai

arXiv:2609.33232v1 Announce Type: new Abstract: Continuous-time sensing and monitoring with timely and accurate decision-making are critical for many real-world applications. In healthcare monitoring

arXiv:2609.31881v1 Announce Type: new Abstract: Dynamic text-attributed graphs (DTAGs), where nodes, edges, and textual attributes evolve over time, are crucial in applications such as social networks

arXiv:2609.30887v1 Announce Type: new Abstract: Mobile GUI agents complete tasks using GUI actions like taps and swipes. These actions are broadly applicable across applications, but reaching a naviga

arXiv:2609.29363v1 Announce Type: new Abstract: The public visibility of Artificial Intelligence (AI) is growing rapidly, driven by the positive impact of its applications across diverse fields of kno

arXiv:2509.20702v3 Announce Type: replace-cross Abstract: Recent advances in large language model (LLM) embeddings have enabled powerful representations for biological data, but most applications to d

arXiv:2411.15921v3 Announce Type: replace Abstract: The removal of multiplicative Gamma noise is a critical research area in the application of synthetic aperture radar (SAR) imaging, where neural net

arXiv:2609.23509v1 Announce Type: new Abstract: Novel view synthesis is a key task for dynamic scene reconstruction, where high rendering speed is essential for applications such as virtual reality. E

arXiv:2609.23980v1 Announce Type: cross Abstract: AI agents now report vulnerabilities faster than maintainers can review them. Reports often depend on security properties specific to the application,

arXiv:2609.24441v1 Announce Type: new Abstract: Multivariate time-series forecasting is essential to many real-world applications. Recent large vision models (LVMs) offer a promising paradigm by trans

arXiv:2609.24226v1 Announce Type: new Abstract: Instance segmentation is a fundamental computer vision task with diverse real-world applications. Recently, prompt-driven foundation models have shown p

Identity security now determines how safely artificial intelligence agents can access systems and act across enterprise workflows. As AI agents log in to applications and execute tasks, companies must

arXiv:2609.21293v1 Announce Type: new Abstract: Autonomous software generation (ASG) aims to turn human requirements into executable applications, but delivering these applications does not necessaril

arXiv:2609.19855v1 Announce Type: cross Abstract: Geographic applications need every object inside a radius that satisfies a semantic threshold, yet embedding indexes return approximate top-ranked lis

arXiv:2509.03405v2 Announce Type: replace Abstract: Language models (LMs) increasingly drive real-world applications that require world knowledge. However, the internal processes through which models

arXiv:2609.19871v1 Announce Type: new Abstract: Time series forecasting has seen signicant advancements with the emergence of new deep learning models. However, forecasting time series in applications

arXiv:2609.18737v1 Announce Type: new Abstract: Underwater 3D reconstruction supports applications ranging from marine ecosystem monitoring and subsea inspection to underwater archaeology, education,

arXiv:2512.09524v2 Announce Type: replace-cross Abstract: Neural decoding is fundamental to brain-computer interfaces, with growing applications in healthcare. Previous research has focused on leverag

arXiv:2609.17995v1 Announce Type: new Abstract: Natural-language datasets support many downstream applications and research studies, but releasing text can reveal sensitive global properties of the un

arXiv:2602.03344v2 Announce Type: replace-cross Abstract: Robustness is widely viewed as a key challenge for real-world applications. However, because current research focuses only on difficult tasks,

arXiv:2602.07273v2 Announce Type: replace Abstract: Immersive applications such as virtual and augmented reality impose stringent requirements on frame rate, latency, and synchronization between physi

arXiv:2609.13919v1 Announce Type: new Abstract: This chapter explores how machine learning (ML) is transforming aquaculture, with a particular focus on enhancing decision-making processes and improvin

arXiv:2609.15359v1 Announce Type: new Abstract: The surge of large language model (LLM) applications on personal devices imposes massive, bursty workloads on cloud serving infrastructure. While prefil