Search: “applications”

arXiv:2606.10023v1 Announce Type: cross Abstract: Accurate posterior estimation is central to scientific inference, as uncertainties determine what can be reliably learned from observational data. Whi

arXiv:2407.05886v3 Announce Type: replace Abstract: Continuum and soft robots can transform automation tasks requiring compliant interaction in constrained or unstructured environments, including heal

arXiv:2606.01362v1 Announce Type: cross Abstract: Video generative models have achieved remarkable progress in synthesizing photorealistic video sequences. However, enabling broader and more creative

arXiv:2510.03745v2 Announce Type: replace Abstract: Low-discrepancy points are designed to efficiently fill the space in a uniform manner. This uniformity is highly advantageous in many problems in sc

arXiv:2307.04722v2 Announce Type: replace Abstract: Meta-learning empowers learning systems with the ability to acquire knowledge from multiple tasks, enabling faster adaptation and generalization to

arXiv:2605.31434v1 Announce Type: new Abstract: Robot-Assisted Minimally Invasive Surgery (RAMIS) enhances surgeon dexterity, with newer platforms leveraging haptic feedback to further improve perform

arXiv:2605.29939v1 Announce Type: cross Abstract: Integrated sensing, communication, and computation (ISCC) provides a promising framework for indoor human-centric applications. In these applications,

arXiv:2605.27920v1 Announce Type: new Abstract: Driven by the wave of large language models, Video-Language Models (VLMs) have become a significant yet challenging technology to bridge the gap between

arXiv:2605.28711v1 Announce Type: new Abstract: The distortion-perception (D-P) tradeoff is a fundamental phenomenon of Bayesian inverse problems, which characterizes the inherent tension between dist

arXiv:2205.14090v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) has well-documented merits for optimizing black-box functions with an expensive evaluation cost. Such functions eme

arXiv:2605.24515v1 Announce Type: new Abstract: With climate change and increasing human pressure on natural landscapes, inland water resources are becoming progressively scarcer, more vulnerable, and

arXiv:2605.24411v1 Announce Type: new Abstract: Existing language model applications struggle to meet the demand for emotionally oriented support, primarily due to their inability to maintain deep, pe

arXiv:2605.23775v1 Announce Type: new Abstract: This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for mat

arXiv:2510.25348v2 Announce Type: replace Abstract: Information cascade popularity prediction is a key problem in analyzing content diffusion in social networks. However, current related works suffer

arXiv:2504.17548v2 Announce Type: replace-cross Abstract: Anomaly Detection (AD) defines the task of identifying observations or events that deviate from typical - or normal - patterns, a critical cap

arXiv:2605.16966v1 Announce Type: new Abstract: Solving inverse partial differential equation (PDE) problems is a fundamental topic in scientific research due to its broad significance across a wide r

arXiv:2605.14488v1 Announce Type: new Abstract: Large Language Models (LLMs) augmented with Retrieval-Augmented Generation (RAG) techniques are revolutionizing applications across multiple domains, su

arXiv:2605.13360v1 Announce Type: new Abstract: There is a growing demand for agentic AI technologies for a range of downstream applications like customer service and personal assistants. For applicat

arXiv:2605.13041v1 Announce Type: new Abstract: With recent advances in embodied agents and AR devices, egocentric observations are readily available as input for real-world interactive online applica

arXiv:2605.12668v1 Announce Type: cross Abstract: Conformal prediction provides a principled framework for uncertainty quantification with finite-sample coverage guarantees. While recent work has exte

arXiv:2511.16868v2 Announce Type: replace Abstract: The Gromov-Wasserstein (GW) distance serves as a powerful tool for matching objects in metric spaces. However, its traditional formulation is constr

arXiv:2512.03199v2 Announce Type: replace Abstract: Biometric facial recognition models often demonstrate significant decreases in accuracy when processing real-world images, often characterized by po

arXiv:2605.11526v1 Announce Type: cross Abstract: Training a deep neural network with the outputs of selected layers satisfying linear constraints is required in many contemporary data-driven applicat

arXiv:2605.08138v1 Announce Type: new Abstract: Synthetic data has emerged as a crucial solution to the data scarcity bottleneck in large language models (LLMs), particularly for specialized domains a

arXiv:2605.08971v1 Announce Type: cross Abstract: Computer-Aided Design is ubiquitous in todays world, as almost every manufactured object begins as a digital model across industries. At the same time

arXiv:2605.08093v1 Announce Type: cross Abstract: The use of chatbots for various forms of companionship is growing rapidly, raising a myriad of questions about simulated relationships, emotional depe

arXiv:2605.05121v1 Announce Type: new Abstract: Automated mental health prediction using textual data has shown promising results with deep learning and large language models. However, deploying these

arXiv:2512.22588v3 Announce Type: replace Abstract: One of the main limitations of multirotor UAVs is their short flight time due to battery constraints. A practical solution for continuous operation

arXiv:2507.13305v2 Announce Type: replace Abstract: Team modeling remains a fundamental challenge at the intersection of Artificial Intelligence and Social Sciences. Although a variety of computationa

arXiv:2605.02901v1 Announce Type: cross Abstract: This work aims to establish an end-to-end system for tracking of physical 3D objects for virtual reality (VR) applications. We focus on training appli

arXiv:2409.14500v5 Announce Type: replace Abstract: Although data that can be naturally represented as graphs is widespread in real-world applications across diverse industries, popular graph ML bench

arXiv:2601.00678v2 Announce Type: replace Abstract: Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an ess

arXiv:2604.27476v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong applicability in edge industrial applications, yet their deployment remains severely constrained

arXiv:2604.26598v1 Announce Type: new Abstract: Face Recognition (FR) is used in a variety of application domains, from entertainment and banking to security and surveillance. Such applications rely o

arXiv:2604.26080v1 Announce Type: cross Abstract: Current and future applications demand ultra-low latency and consistent throughput, yet frequently traverse 5G cellular networks, so cope with volatil

arXiv:2604.24796v1 Announce Type: cross Abstract: Liver cirrhosis is a major global health problem causing millions of deaths annually, and timely detection with aggressive treatment can significantly

arXiv:2511.10161v2 Announce Type: replace Abstract: In the Data-Centric Artificial Intelligence (AI) paradigm, improving data quality is essential for robust machine learning. However, many denoising

arXiv:2503.03023v2 Announce Type: replace Abstract: We study non-linear bandit optimization where the learner maximizes a black-box function with zeroth order function oracle, which has been successfu

arXiv:2601.05414v2 Announce Type: replace Abstract: As large language models (LLMs) transition from chat interfaces to integral components of stochastic pipelines and systems approaching general intel

arXiv:2604.17158v1 Announce Type: cross Abstract: The occurrence of cybersickness in virtual reality (VR) significantly impairs users' perception and sense of immersion. Therefore, timely detection of

arXiv:2604.18548v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a powerful framework for learning governing equations of dynamical systems from data. Biologically-info

arXiv:2604.16432v1 Announce Type: cross Abstract: AI in applications like screening job applicants had become widespread, and may contribute to unemployment especially among the young. Biases in the A

arXiv:2604.16388v1 Announce Type: cross Abstract: Rapidly-exploring random trees (RRTs) have been widely adopted for robot motion planning due to their robustness and theoretical guarantees. However,

arXiv:2604.14179v1 Announce Type: new Abstract: Rare diseases affect over 300 million people worldwide and are characterized by complex care pathways, limited clinical expertise, and substantial unmet

arXiv:2604.13863v1 Announce Type: new Abstract: Image generation technology can synthesize condition-specific images to supplement real-world industrial anomaly data and enhance anomaly detection mode

arXiv:2511.15875v2 Announce Type: replace Abstract: The automated analysis of historical documents, particularly maps, has drastically benefited from advances in deep learning and its success across v