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Related papers: Root/Additional Metric (RoAM) framework: a guide f…

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The simulation of complex nonlinear engineering systems such as compressible fluid flows may be targeted to make more efficient and accurate the approximation of a specific (scalar) quantity of interest of the system. Putting aside modeling…

Numerical Analysis · Mathematics 2018-11-14 Jan Van Langenhove , Didier Lucor , Frédéric Alauzet , Anca Belme

A key component of creativity is associative reasoning: the ability to draw novel yet meaningful connections between concepts. We introduce CREATE, a benchmark designed to evaluate models' capacity for creative associative reasoning. CREATE…

Computation and Language · Computer Science 2026-05-12 Manya Wadhwa , Tiasa Singha Roy , Harvey Lederman , Junyi Jessy Li , Greg Durrett

As the demand for mass customization increases, manufacturing systems must become more flexible and adaptable to produce personalized products efficiently. Additive manufacturing (AM) enhances production adaptability by enabling on-demand…

Robotics · Computer Science 2026-03-27 Yifei Li , Ruizhe Fu , Huihang Liu , Guha Manogharan , Feng Ju , Ilya Kovalenko

Software engineering practices such as constructing requirements and establishing traceability help ensure systems are safe, reliable, and maintainable. However, they can be resource-intensive and are frequently underutilized. To alleviate…

Software Engineering · Computer Science 2024-08-21 Katherine R. Dearstyne , Alberto D. Rodriguez , Jane Cleland-Huang

This work introduces an innovative parallel, fully-distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well-known that virtual part design and qualification in additive…

Computational Engineering, Finance, and Science · Computer Science 2019-04-30 Eric Neiva , Santiago Badia , Alberto F. Martín , Michele Chiumenti

Given a learning problem with real-world tradeoffs, which cost function should the model be trained to optimize? This is the metric selection problem in machine learning. Despite its practical interest, there is limited formal guidance on…

Machine Learning · Statistics 2022-08-22 Gaurush Hiranandani

Systematic application of software metric techniques can lead to significant improvements of the quality of a final software product. However, there is still the evident lack of wider utilization of software metrics techniques and tools due…

Software Engineering · Computer Science 2013-11-18 Gordana Rakic , Zoran Budimac

This paper develops an axiomatic framework for ranking metrics, a general class of functionals for evaluating and ordering financial or insurance positions. Unlike traditional risk-adjusted performance measures-such as the Sharpe ratio,…

Risk Management · Quantitative Finance 2026-04-21 Asmerilda Hitaj , Elisa Mastrogiacomo , Ilaria Peri , Marcelo Righi

For many optimization problems it is possible to define a distance metric between problem variables that correlates with the likelihood and strength of interactions between the variables. For example, one may define a metric so that the…

Neural and Evolutionary Computing · Computer Science 2012-01-12 Martin Pelikan , Mark W. Hauschild

A significant amount of work is invested in human-machine teaming (HMT) across multiple fields. Accurately and effectively measuring system performance of an HMT is crucial for moving the design of these systems forward. Metrics are the…

Computers and Society · Computer Science 2020-08-12 Praveen Damacharla , Ahmad Y. Javaid , Jennie J. Gallimore , Vijay K. Devabhaktuni

Objective: To present an overview on the current state of the art concerning metrics-based quality evaluation of software components and component assemblies. Method: Comparison of several approaches available in the literature, using a…

Software Engineering · Computer Science 2011-10-03 Miguel Goulão , Fernando Brito e Abreu

Lack of reliability is a well-known issue for reinforcement learning (RL) algorithms. This problem has gained increasing attention in recent years, and efforts to improve it have grown substantially. To aid RL researchers and production…

Machine Learning · Statistics 2020-02-14 Stephanie C. Y. Chan , Samuel Fishman , John Canny , Anoop Korattikara , Sergio Guadarrama

Clinical randomized controlled trials (RCTs) collect hundreds of measurements spanning various metric types (e.g., laboratory tests, cognitive/motor assessments, etc.) across 100s-1000s of subjects to evaluate the effect of a treatment, but…

Machine Learning · Computer Science 2024-06-25 Sayeri Lala , Niraj K. Jha

In large-scale automotive companies, various requirements engineering (RE) practices are used across teams. RE practices manifest in Requirements Information Models (RIM) that define what concepts and information should be captured for…

Software Engineering · Computer Science 2020-01-07 Rebekka Wohlrab , Eric Knauss , Patrizio Pelliccione

This paper demonstrates a methodology to help practitioners maximise the utility of complex multidisciplinary engineering models implemented as spreadsheets, an area presenting unique challenges. As motivation we investigate the expanding…

Software Engineering · Computer Science 2014-01-21 David Birch , Helen Liang , Paul H J Kelly , Glen Mullineux , Tony Field , Joan Ko , Alvise Simondetti

Metric elicitation is a recent framework for eliciting classification performance metrics that best reflect implicit user preferences based on the task and context. However, available elicitation strategies have been limited to linear (or…

Machine Learning · Statistics 2022-08-23 Gaurush Hiranandani , Jatin Mathur , Harikrishna Narasimhan , Oluwasanmi Koyejo

Robotic foundation models (RFMs) are emerging as a promising route towards flexible, instruction- and demonstration-driven robot control, however, a critical investigation of their industrial applicability is still lacking. This survey…

Robotics · Computer Science 2026-03-10 David Kube , Simon Hadwiger , Tobias Meisen

Reasoning has emerged as the next major frontier for language models (LMs), with rapid advances from both academic and industrial labs. However, this progress often outpaces methodological rigor, with many evaluations relying on…

Machine Learning · Computer Science 2025-10-08 Andreas Hochlehnert , Hardik Bhatnagar , Vishaal Udandarao , Samuel Albanie , Ameya Prabhu , Matthias Bethge

Over the last decade, researchers and engineers have developed a vast body of methodologies and technologies in requirements engineering for self-adaptive systems. Although existing studies have explored various aspects of this topic, few…

Software Engineering · Computer Science 2021-08-23 Zhuoqun Yang , Zhi Li , Zhi Jin

In this paper, we present a new algorithm that extends RRT* and RT-RRT* for online path planning in complex, dynamic environments. Sampling-based approaches often perform poorly in environments with narrow passages, a feature common to many…

Robotics · Computer Science 2021-09-10 Daniel Armstrong , André Jonasson