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By leveraging the retrieval of information from external knowledge databases, Large Language Models (LLMs) exhibit enhanced capabilities for accomplishing many knowledge-intensive tasks. However, due to the inherent flaws of current…

Computation and Language · Computer Science 2024-09-13 Siye Wu , Jian Xie , Jiangjie Chen , Tinghui Zhu , Kai Zhang , Yanghua Xiao

Usually, methods evaluating system reliability require engineers to quantify the reliability of each of the system components. For series and parallel systems, there are some options to handle the estimation of each component's reliability.…

Methodology · Statistics 2018-05-29 Agatha Rodrigues , Carlos Alberto Pereira , Adriano Polpo

Software reliability is an important quality attrib-ute, often evaluated as either a function of time or of system structures. The goal of this study is to have this metric cover both for component-based software, be-cause its reliability…

Software Engineering · Computer Science 2007-05-23 Wen-Li Wang , Mei-Huei Tang

Analysis of repair systems usually uses an As Good As New or As Bad As Old repair assumptions. In practice, repair actions do not result in such extreme situations, but rather in a complex transitional one, that is imperfect maintenance,…

Applications · Statistics 2016-09-06 Sergey Porotsky

This article is a survey of results concerning an inequality, which may be seen as a versatile tool to solve problems in the domain of Applied Probability. The inequality, which we call BRS-inequality, gives a convenient upper bound for the…

Probability · Mathematics 2020-07-13 F. Thomas Bruss

In this work, we propose a new estimation method of a Structural Equation Model. Our method is based on the EM likelihood-maximization algorithm. We show that this method provides estimators, not only of the coefficients of the model, but…

Statistics Theory · Mathematics 2015-10-02 Xavier Bry , Christian Lavergne , Myriam Tami

This paper presents a new methodology for structural reliability analysis via stochastic finite element method (SFEM). A novel sample-based SFEM is firstly used to compute structural stochastic responses of all spatial points at the same…

Computational Physics · Physics 2020-08-19 Zhibao Zheng

This paper studies the robustness of large-scale interconnected systems with respect to external disturbances, focussing on their scalability properties. Specifically, a notion of scalability is introduced that asks for these robustness…

Optimization and Control · Mathematics 2020-05-14 Steffi Knorn , Bart Besselink

Redundancy matrices provide insights into the load carrying behavior of statically indeterminate structures. This information can be employed for the design and analysis of structures with regard to certain objectives, for example…

Computational Engineering, Finance, and Science · Computer Science 2023-06-22 Tim Krake , Malte von Scheven , Jan Gade , Moataz Abdelaal , Daniel Weiskopf , Manfred Bischoff

Ensuring the robustness of factual knowledge in LLMs is critical for reliable applications in tasks such as question answering and reasoning. However, existing evaluation methods predominantly focus on performance-based metrics, often…

Computation and Language · Computer Science 2025-11-21 Alina Fastowski , Bardh Prenkaj , Gjergji Kasneci

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses.…

Physics and Society · Physics 2015-05-08 Sarah LaRocca , Jonas Johansson , Henrik Hassel , Seth Guikema

Maintenance is the last and the most critical phase of the software development life cycle. It involves debugging of errors and different types of enhancements which are requested by the user. Software reliability regarding maintenance is…

Software Engineering · Computer Science 2016-05-04 Ahmad Mateen , Muhammad Azeem Akbar

Empirical risk minimization (ERM) is sensitive to spurious correlations in the training data, which poses a significant risk when deploying systems trained under this paradigm in high-stake applications. While the existing literature…

Machine Learning · Computer Science 2023-10-31 Christos Tsirigotis , Joao Monteiro , Pau Rodriguez , David Vazquez , Aaron Courville

The reliability of machine learning (ML) software systems is heavily influenced by changes in data over time. For that reason, ML systems require regular maintenance, typically based on model retraining. However, retraining requires…

Machine Learning · Computer Science 2025-06-18 Lorena Poenaru-Olaru , June Sallou , Luis Cruz , Jan Rellermeyer , Arie van Deursen

An important factor to guarantee a fair use of data-driven recommendation systems is that we should be able to communicate their uncertainty to decision makers. This can be accomplished by constructing prediction intervals, which provide an…

Methodology · Statistics 2019-08-16 Yaniv Romano , Rina Foygel Barber , Chiara Sabatti , Emmanuel J. Candès

Despite being able to generate fluent and grammatical text, current Seq2Seq summarization models still suffering from the unfaithful generation problem. In this paper, we study the faithfulness of existing systems from a new perspective of…

Computation and Language · Computer Science 2022-11-02 Wenhao Wu , Wei Li , Jiachen Liu , Xinyan Xiao , Ziqiang Cao , Sujian Li , Hua Wu

Bayesian model updating facilitates the calibration of analytical models based on observations and the quantification of uncertainties in model parameters such as stiffness and mass. This process significantly enhances damage assessment and…

Applications · Statistics 2024-08-06 Taro Yaoyama , Tatsuya Itoi , Jun Iyama

This paper establishes unified frameworks of renewable weighted sums (RWS) for various online updating estimations in the models with streaming data sets. The newly defined RWS lays the foundation of online updating likelihood, online…

Methodology · Statistics 2020-08-21 Lu Lin , Weiyu Li , Jun Lu

Starting from a linear fractional representation of a linear system affected by constant parametric uncertainties, we demonstrate how to enhance standard robust analysis tests by taking available (noisy) input-output data of the uncertain…

Optimization and Control · Mathematics 2023-03-27 Tobias Holicki , Carsten W. Scherer

Recent discussions on alternative facts, fake news, and post truth politics have motivated research on creating technologies that allow people not only to access information, but also to assess the credibility of the information presented…

Information Retrieval · Computer Science 2017-08-25 Christina Lioma , Jakob Grue Simonsen , Birger Larsen