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arXiv:2503.05786v3 Announce Type: replace Abstract: With the increasing prevalence of mental health conditions worldwide, AI-powered chatbots and conversational agents have emerged as accessible tools to...
arXiv:2503.06759v2 Announce Type: replace Abstract: Achieving health equity in Artificial Intelligence (AI) requires diagnostic models that maintain reliability across diverse populations. However, breast cancer screening...
arXiv:2503.06950v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems enhance response credibility and traceability by displaying reference contexts, but this transparency simultaneously introduces a novel...
arXiv:2503.07137v4 Announce Type: replace Abstract: Artificial intelligence (AI) has achieved astonishing successes in many domains, especially with the recent breakthroughs in the development of foundational...
arXiv:2503.07527v2 Announce Type: replace Abstract: To enhance lifting-load estimation accuracy in industrial upper-limb assistive exoskeletons, this study proposes a machine learning-based approach using insole pressure...
arXiv:2503.07881v2 Announce Type: replace Abstract: We introduce higher-dimensional automata for infinite interval ipomsets ($\omega$-HDAs). We define key concepts from different points of view, inspired from...
arXiv:2503.08305v5 Announce Type: replace Abstract: We present the Electronic Tensor Reconstruction Algorithm (ELECTRA) - an equivariant model for predicting electronic charge densities using floating orbitals....
arXiv:2503.08603v2 Announce Type: replace Abstract: Cell microscopy data are abundant; however, corresponding segmentation annotations remain scarce. Moreover, variations in cell types, imaging devices, and staining...
arXiv:2503.10196v2 Announce Type: replace Abstract: In this paper, we establish error estimates for a fully discrete, filtered Lie splitting scheme applied directly to the Zakharov...
arXiv:2503.14764v3 Announce Type: replace Abstract: This paper explores the reconstruction of a space-dependent parameter in inverse diffusion problems, proposing a shape-optimization-based approach. We consider a...
arXiv:2503.16522v2 Announce Type: replace Abstract: Rectified flow models have achieved remarkable performance in image and video generation tasks. However, existing numerical solvers face a trade-off...
arXiv:2503.21424v2 Announce Type: replace Abstract: Recently, various automated testing approaches have been proposed that use specialized test oracles to find hundreds of logic bugs in...
arXiv:2503.21679v3 Announce Type: replace Abstract: This paper introduces JiraiBench, the first bilingual benchmark for evaluating large language models' effectiveness in detecting self-destructive content across Chinese...
arXiv:2503.23832v2 Announce Type: replace Abstract: ReLU matrix decomposition (RMD) is the following problem: given a sparse, nonnegative matrix $X$ and a factorization rank $r$, identify...
arXiv:2503.23972v4 Announce Type: replace Abstract: The pursuit of energy-efficient and adaptive artificial intelligence (AI) has positioned neuromorphic computing as a promising alternative to conventional computing....
arXiv:2504.00174v2 Announce Type: replace Abstract: Meta-Continual Learning (Meta-CL) enables models to learn new classes from limited labelled samples, making it promising for IoT applications where...
arXiv:2504.03380v2 Announce Type: replace Abstract: Recent advances in reinforcement learning with verifiable rewards (RLVR) show that large language models enhance their reasoning abilities when trained...
arXiv:2504.03408v2 Announce Type: replace Abstract: The paper presents a novel multimesh rational approximation scheme for the numerical solution of the (homogeneous) Dirichlet problem for the...
arXiv:2504.04139v2 Announce Type: replace Abstract: This paper presents COGENT3 (or Collective Growth and Entropy-modulated Triads System), a novel approach for emergent cognition integrating pattern formation...
arXiv:2504.04372v3 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:2504.05695v5 Announce Type: replace Abstract: We prove that overparametrized neural networks are able to generalize with a test error that is independent of the level...
arXiv:2504.08704v2 Announce Type: replace Abstract: Effective leveraging of real-world driving datasets is crucial for enhancing the training of autonomous driving systems. While Offline Reinforcement Learning...
arXiv:2504.12905v3 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) is widely used for novel view synthesis due to its high rendering quality and fast inference...
arXiv:2504.13393v3 Announce Type: replace Abstract: Ground beetles are a highly sensitive and speciose biological indicator, making them vital for monitoring biodiversity. However, they are currently...