Search: “applications”

arXiv:2604.20944v1 Announce Type: cross Abstract: In many real-world machine learning (ML) applications, the true target cannot be precisely defined due to ambiguity or subjectivity information. To ad

arXiv:2511.17265v2 Announce Type: replace-cross Abstract: Nowadays, we are witnessing an Artificial Intelligence revolution that dominates the technology landscape in various application domains, such

arXiv:2602.05416v2 Announce Type: replace-cross Abstract: While proper orthogonal decomposition (POD)-based surrogates are widely explored for hydrodynamic applications, the use of Koopman autoencoder

arXiv:2603.04592v3 Announce Type: replace Abstract: Standard Large Language Models (LLMs) are predominantly designed for static inference with pre-defined inputs, which limits their applicability in d

arXiv:2505.07033v2 Announce Type: replace-cross Abstract: Many classification performance metrics exist, each suited to a specific application. However, these metrics often differ in scale and can exh

arXiv:2604.16123v1 Announce Type: new Abstract: Accurate molecular property prediction is central to drug discovery, catalysis, and process design, yet real-world applications are often limited by sma

arXiv:2604.12095v1 Announce Type: cross Abstract: Monitoring binomial proportions across multiple independent streams is a critical challenge in Statistical Process Control (SPC), with applications fr

arXiv:2502.06595v3 Announce Type: replace-cross Abstract: Diffusion kernels over graphs have been widely utilized as effective tools in various applications due to their ability to accurately model th

arXiv:2511.15083v2 Announce Type: replace Abstract: Time-series anomaly detection plays a critical role in numerous real-world applications, including industrial monitoring and fault diagnosis. Recent

arXiv:2604.08980v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have been widely adopted in engineering applications such as social network analysis, chemical research and computer visi

arXiv:2604.07477v1 Announce Type: new Abstract: For applications including facial identification, forensic analysis, photographic improvement, and medical imaging diagnostics, facial image deblurring

arXiv:2608.11053v1 Announce Type: cross Abstract: The application of computer vision in agriculture has shown significant potential for improving crop monitoring and precision farming. However, many e

arXiv:2608.11083v1 Announce Type: cross Abstract: Low Power Wide Area Networks like LoRa are increasingly deployed for smart city applications, requiring accurate path loss prediction for effective ne

arXiv:2608.10345v1 Announce Type: new Abstract: Free-viewpoint 3D scene media is increasingly important for immersive applications, yet practical capture often suffers from severe view sparsity and mo

arXiv:2603.29418v2 Announce Type: replace-cross Abstract: Although multimodal large language models (MLLMs) are increasingly deployed in real-world applications, their instruction-following behavior l

arXiv:2608.08561v1 Announce Type: new Abstract: In medical applications, raw data is frequently associated with significant privacy concerns, lending particular importance to the encoding of summary s

arXiv:2510.21891v2 Announce Type: replace-cross Abstract: To deploy large language models (LLMs) in high-stakes application domains that require substantively accurate responses to open-ended prompts,

arXiv:2608.08010v1 Announce Type: cross Abstract: Time series forecasting (TSF) plays an important role in a wide range of real-world applications. Recently, time series foundation models (TSFMs), pre

arXiv:2608.07364v1 Announce Type: new Abstract: Contribution: This paper presents a six-phase AI-assisted instructional design architecture based on the Curriculum as Code paradigm, integrating Genera

arXiv:2608.04471v1 Announce Type: cross Abstract: Time series in real-world applications are often generated by nonlinear dynamical systems, making accurate forecasting challenging. Existing approache

arXiv:2606.17824v2 Announce Type: replace-cross Abstract: Segmenting 3D assets into meaningful regions remains challenging, especially when segmentation criteria are application-dependent and require

arXiv:2608.03926v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) underpins applications in predictive maintenance, finance, and cloud computing, however performance remains sensi

arXiv:2608.03250v1 Announce Type: cross Abstract: The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting i

arXiv:2608.03087v1 Announce Type: cross Abstract: Fine-grained energy consumption data are essential for applications such as demand forecasting, demand response planning, and grid reliability assessm

arXiv:2510.15127v3 Announce Type: replace-cross Abstract: Identifying the effects of mechanical ventilation (MV) protocols in critical care requires analyzing data from heterogeneous patient-ventilato

arXiv:2608.01905v1 Announce Type: new Abstract: Hand-object interaction (HOI) is a fundamental human behavior with broad applications in AR/VR, digital humans, and embodied interaction. Existing metho

arXiv:2608.00289v1 Announce Type: cross Abstract: Recognizing Human-Object Interactions (HOI) is essential for intelligent systems, underpinning applications in virtual and augmented reality, embodied

arXiv:2608.00356v1 Announce Type: new Abstract: The First AI Children Challenge aims to advance real-world applications of computer vision and AI in child healthcare, child education, and pediatrics.

arXiv:2607.28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cros

arXiv:2511.00847v5 Announce Type: replace-cross Abstract: The widespread adoption of Large Language Models (LLMs) through Application Programming Interfaces (APIs) induces a critical vulnerability: th

arXiv:2507.21799v2 Announce Type: replace-cross Abstract: The empirical success of deep learning has spurred its application to the radio-frequency (RF) domain, leading to significant advances in Deep

arXiv:2607.28035v1 Announce Type: new Abstract: Irregular multivariate time series are widely encountered in applications such as healthcare monitoring, human activity recognition, and environmental s

arXiv:2209.00546v5 Announce Type: replace-cross Abstract: Signed and directed networks are ubiquitous in real-world applications. However, there has been relatively little work proposing spectral grap

arXiv:2501.13104v3 Announce Type: replace Abstract: Neural Radiance Fields (NeRFs) have remodeled 3D scene representation since release. NeRFs can effectively reconstruct complex 3D scenes from 2D ima

arXiv:2502.11150v5 Announce Type: replace Abstract: Automatic methods for scoring text readability have been studied for over a century, and are widely used in research and in user-facing applications

arXiv:2607.23295v1 Announce Type: cross Abstract: In real-world machine learning applications, incomplete observations create a fundamental challenge. Researchers have come up with several ideas to ad

arXiv:2607.23395v1 Announce Type: cross Abstract: Music Source Separation (MSS), the task of recovering individual sound components (stems) from a polyphonic mixture, is central to applications rangin

arXiv:2607.22320v1 Announce Type: new Abstract: The passive adaptability inherent in soft robotic hands affords them advantages in applications that require safe and compliant interaction. However, ex

arXiv:2607.22287v1 Announce Type: new Abstract: Graph-based recommendations are widely adopted in real-world industrial applications. However, graphs in these systems often reach a massive scale, posi

arXiv:2505.23378v3 Announce Type: replace Abstract: Speaker-dependent modelling can substantially improve performance in speech-based health monitoring applications. While mixed-effect models are comm

arXiv:2607.21756v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in database-backed applications to classify tuples, filter records using semantic predicates, extra

arXiv:2607.19704v1 Announce Type: new Abstract: Scaling LLM-based applications to millions of users is bottlenecked by the inference cost and latency of modern foundation models. A natural fix is to c

arXiv:2508.00909v2 Announce Type: replace Abstract: Time series anomaly detection plays a critical role in a wide range of real-world applications. Among unsupervised approaches, self-supervised learn

arXiv:2607.13837v1 Announce Type: cross Abstract: In real-world applications, node classification on graphs often faces the challenge of class imbalance, where majority classes dominate training, resu

arXiv:2607.13698v1 Announce Type: cross Abstract: In recent years, there has been growing interest in robust robotic systems for precise bin-picking applications. To achieve reliable performance, such

arXiv:2602.16727v2 Announce Type: replace Abstract: Simulating large-scale human mobility is fundamental to understanding population movement patterns and supporting real-world geospatial applications