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arXiv:2502.13379v3 Announce Type: replace Abstract: Trusted Execution Environments (TEEs) isolate a special space within a device memory that is not accessible to the normal world...
arXiv:2502.17100v4 Announce Type: replace Abstract: Generative models have fundamentally reshaped the landscape of decision-making, reframing the problem from pure scalar reward maximization to high-fidelity trajectory...
arXiv:2503.07928v4 Announce Type: replace Abstract: The widespread availability of large language models (LLMs), such as ChatGPT, has significantly impacted education, raising both opportunities and challenges....
arXiv:2503.11730v2 Announce Type: replace Abstract: Prognostic and Health Management (PHM) are crucial ways to avoid unnecessary maintenance for Cyber-Physical Systems (CPS) and improve system reliability....
arXiv:2503.11832v4 Announce Type: replace Abstract: Recent vision language models (VLMs) have made remarkable strides in generative modeling with multimodal inputs, particularly text and images. However,...
arXiv:2503.16481v3 Announce Type: replace Abstract: Robots are increasingly being deployed in public spaces such as shopping malls, sidewalks, and hospitals, where safe and socially aware...
arXiv:2503.16558v2 Announce Type: replace Abstract: Problem-Based Learning (PBL) has significantly impacted biomedical engineering (BME) education since its introduction in the early 2000s, effectively enhancing critical...
arXiv:2503.21692v5 Announce Type: replace Abstract: The integration of multi-view imaging and pose estimation represents a significant advance in computer vision applications, offering new possibilities for...
arXiv:2504.04372v4 Announce Type: replace Abstract: Generative Large Language Models (LLMs) are increasingly used in non-generative software maintenance tasks, such as fault localization (FL). Success in...
arXiv:2504.05738v4 Announce Type: replace Abstract: Cloud applications heavily rely on APIs to communicate with each other and exchange data. To ensure the reliability of cloud...
arXiv:2504.07654v2 Announce Type: replace Abstract: The problem of Time-series Forecasting is generally addressed by recurrent, Transformer-based and the recently proposed Mamba-based architectures. However, existing architectures...
arXiv:2504.09940v5 Announce Type: replace Abstract: Accurate Subseasonal-to-Seasonal (S2S) forecasting is vital for decision-making in agriculture, energy production, and emergency management. However, it remains a challenging...
arXiv:2504.10288v3 Announce Type: replace Abstract: We present a new self-supervised deep-learning-based Ghost Imaging (GI) reconstruction method, which provides unparalleled reconstruction quality for noisy acquisitions among...
arXiv:2504.13596v3 Announce Type: replace Abstract: Vision-based 3D semantic occupancy prediction is vital for autonomous driving, enabling unified modeling of static infrastructure and dynamic agents. Global...
arXiv:2504.16729v2 Announce Type: replace Abstract: With the rapid development of the Artificial Intelligence of Things (AIoT), mobile edge computing (MEC) becomes an essential technology underpinning...
arXiv:2504.18597v3 Announce Type: replace Abstract: The Brakerski-Gentry-Vaikuntanathan (BGV) scheme is one of the most significant fully homomorphic encryption (FHE) schemes. It belongs to a class...
arXiv:2505.03621v2 Announce Type: replace Abstract: Remote photoplethysmography (rPPG) enables non-contact physiological measurement but remains highly susceptible to illumination changes, motion artifacts, and limited temporal modeling....
arXiv:2505.03858v2 Announce Type: replace Abstract: Computing the principal component (PC) of the adjacency matrix of an undirected graph has several applications ranging from identifying key...
arXiv:2505.04997v2 Announce Type: replace Abstract: Computational fluid dynamics (CFD) has been the main workhorse of computational physics. Yet its steep learning curve and fragmented, multi-stage...
arXiv:2505.05589v3 Announce Type: replace Abstract: Reactive dance generation (RDG), the task of generating a dance conditioned on a lead dancer's motion, holds significant promise for...
arXiv:2505.06515v2 Announce Type: replace Abstract: Bird's-Eye-View (BEV) semantic segmentation provides comprehensive environmental perception for autonomous driving but suffers multi-modal misalignment and sensor noise. We propose...
arXiv:2505.06737v3 Announce Type: replace Abstract: Reinforcement Learning (RL) is a promising approach for achieving autonomous driving due to robust decision-making capabilities. RL learns a driving...
arXiv:2505.06740v3 Announce Type: replace Abstract: Accurate prediction of surrounding road users' trajectories is essential for safe and efficient autonomous driving. While deep learning models have...
arXiv:2505.08264v3 Announce Type: replace Abstract: This paper addresses the challenges of training end-to-end autonomous driving agents using Reinforcement Learning (RL). RL agents are typically trained...