Delve into the cutting edge of Artificial Intelligence with our dedicated Research Paper section.
![[2408.11925] An Open Knowledge Graph-Based Approach for Mapping Concepts and Requirements between the EU AI Act and International Standards](http://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png "[2408.11925] An Open Knowledge Graph-Based Approach for Mapping Concepts and Requirements between the EU AI Act and International Standards"){kind=logo}
[Submitted on 21 Aug 2024] View a PDF of the paper titled An Open Knowledge Graph-Based Approach for Mapping Concepts and Requirements between the EU AI Act and International Standards, by Julio Hernandez and 2 other authors View PDF HTML…
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.…
arXiv:2408.11085v1 Announce Type: new Abstract: We leverage 3D Gaussian Splatting (3DGS) as a scene representation and propose a novel test-time camera pose refinement framework, GSLoc. This framework enhances the localization accuracy of state-of-the-art absolute pose regression and scene coordinate regression…
arXiv:2408.11827v1 Announce Type: new Abstract: Locating and editing knowledge in large language models (LLMs) is crucial for enhancing their accuracy, safety, and inference rationale. We introduce “concept editing”, an innovative variation of knowledge editing that uncovers conceptualisation mechanisms within these…
arXiv:2408.11977v1 Announce Type: new Abstract: This paper studies the problem of learning Bayesian networks from continuous observational data, generated according to a linear Gaussian structural equation model. We consider an $\ell_0$-penalized maximum likelihood estimator for this problem which is known…
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak; 25(231):1−40, 2024. Abstract This paper introduces a novel theoretical framework for the analysis of vector-valued neural networks through…
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.…
[Submitted on 6 Aug 2024] View a PDF of the paper titled MicroXercise: A Micro-Level Comparative and Explainable System for Remote Physical Therapy, by Hanchen David Wang and 5 other authors View PDF HTML (experimental) Abstract:Recent global estimates suggest that…
arXiv:2408.10248v1 Announce Type: new Abstract: The natural language processing and multimedia field has seen a notable surge in interest in multimodal sentiment recognition. Hence, this study aims to employ Target-Dependent Multimodal Sentiment Analysis (TDMSA) to identify the level of sentiment…
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.…
arXiv:2408.11164v1 Announce Type: new Abstract: In the high-dimensional setting, Gaussian mixture kernel density estimates become increasingly suboptimal. In this work we aim to show that it is practical to instead use the optimal multivariate Epanechnikov kernel. We make use of…
Individual-centered Partial Information in Social Networks Xiao Han, Y. X. Rachel Wang, Qing Yang, Xin Tong; 25(230):1−60, 2024. Abstract In statistical network analysis, we often assume either the full network is available or multiple subgraphs can be sampled to estimate…