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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...
arXiv:2505.10117v3 Announce Type: replace Abstract: In cloud services, virtual machine (VM) scheduling is a typical Online Dynamic Multidimensional Bin Packing (ODMBP) problem, characterized by large-scale...
arXiv:2505.13770v2 Announce Type: replace Abstract: Reliable causal inference is essential for making decisions in high-stakes areas like medicine, economics, and public policy. However, it remains...
arXiv:2505.18374v2 Announce Type: replace Abstract: Modeling of command-line interface (CLI) interaction has enabled flexible, execution-free output presentation. However, current approaches struggle to model inputs with...
arXiv:2505.19255v4 Announce Type: replace Abstract: Reinforcement Learning Finetuning (RFT) has significantly advanced the reasoning capabilities of large language models (LLMs) by enabling long chains of...
arXiv:2505.20685v4 Announce Type: replace Abstract: Bayesian optimization (BO) struggles in high dimensions, where Gaussian-process surrogates demand heavy retraining and brittle assumptions, slowing progress on real...