Search: “applications”

arXiv:2604.16399v2 Announce Type: replace-cross Abstract: The widespread adoption of AI-assisted development tools in 2025 -- and the emergence of vibe coding, a practice of generating complete applic

arXiv:2604.26213v1 Announce Type: cross Abstract: Loading high dimensional distributions is an important task for utilizing quantum computers on applications ranging from machine learning to finance.

IBM Granite 4.1 is a family of foundation models released by IBM Research designed for enterprise AI applications. The models likely offer improvements in performance, efficiency, and capabilities com

arXiv:2604.24833v1 Announce Type: cross Abstract: Despite transformative advances in generative motion synthesis, real-time interactive motion control remains dominated by traditional techniques. In t

arXiv:2604.23281v1 Announce Type: cross Abstract: Human activity recognition serves as the foundation for various emerging applications. In recent years, researchers have used collaborative sensing of

arXiv:2407.08750v4 Announce Type: replace-cross Abstract: Large-scale streaming data are common in modern machine learning applications and have led to the development of online learning algorithms. M

arXiv:2604.22749v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for text generation tasks from everyday use to high-stakes enterprise and government applications, in

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

Many folks seem to be confused, and think the collapse of the CS major graduation numbers at Berkeley could be linked to the 'AI is taking SWE jobs' hysteria narrative. Here's the easiest way to see t

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

A Reddit post in r/ChatGPT titled 'Deploying my vibe-coded app on production' discusses the experience of taking an AI-generated application to a live production environment. The post reflects a br...

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

arXiv:2610.19532v1 Announce Type: new Abstract: Existing student models in educational applications largely focus on student responses to questions. However, as tutoring becomes more accessible at lar

arXiv:2610.20053v1 Announce Type: new Abstract: Regression models used in real-world applications are often challenged by noise, outliers, data heterogeneity, and asymmetric error characteristics, whi

arXiv:2610.18514v1 Announce Type: new Abstract: Motivated by applications to cognitive radio networks, multi-player multi-armed bandits (MMAB) have attracted considerable attention in recent years. Th

arXiv:2610.18621v1 Announce Type: new Abstract: Accurate uncertainty quantification is critical for many time series forecasting applications, and recent studies have increasingly adopted generative m

arXiv:2601.16333v3 Announce Type: replace Abstract: Foundation models are used for many real-world applications involving language understanding and generation from temporally-ordered multimodal event

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