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We introduces a category-theoretic framework for modelling trust as applied to trusted computation systems and remote attestation. By formalizing elements, claims, results, and decisions as objects within a category, and the processes of…

Cryptography and Security · Computer Science 2026-02-13 Ian Oliver , Pekka Kuure

Physical reasoning requires forward prediction: the ability to forecast what will happen next given some initial world state. We study the performance of state-of-the-art forward-prediction models in the complex physical-reasoning tasks of…

Machine Learning · Computer Science 2021-03-31 Rohit Girdhar , Laura Gustafson , Aaron Adcock , Laurens van der Maaten

Measuring testability early in the development life cycle especially at design phase is a criterion of crucial importance to software designers, developers, quality controllers and practitioners. However, most of the mechanism available for…

Software Engineering · Computer Science 2015-03-19 M. H. Khan Abdullah , Reena Srivastava

Model checking has been successfully used in many computer science fields, including artificial intelligence, theoretical computer science, and databases. Most of the proposed solutions make use of classical, point-based temporal logics,…

Logic in Computer Science · Computer Science 2016-01-25 A. Molinari , A. Montanari , A. Peron

Pathology foundation models have shown strong retrospective performance, but whether such systems can support clinically relevant use remains unclear. This challenge is particularly important in breast cancer, where pathological assessment…

This article proposes the use of temporal logic for an analysis of instrumentality inspired by the work of G.H. von Wright. The first part of the article contains the philosophical foundations. We discuss von Wright's general theory of…

Logic · Mathematics 2023-02-24 Kees van Berkel , Tim S. Lyon , Matteo Pascucci

Vision transformers (ViTs) have emerged as a significant area of focus, particularly for their capacity to be jointly trained with large language models and to serve as robust vision foundation models. Yet, the development of trustworthy…

Machine Learning · Computer Science 2024-11-04 Hengyi Wang , Shiwei Tan , Hao Wang

This paper aims to question the suitability of the Turing Test, for testing machine intelligence, in the light of advances made in the last 60 years in science, medicine, and philosophy of mind. While the main concept of the test may seem…

Artificial Intelligence · Computer Science 2019-06-27 Aladdin Ayesh

Trajectory inference seeks to recover the temporal dynamics of a population from snapshots of its (uncoupled) temporal marginals, i.e. where observed particles are not tracked over time. Prior works addressed this challenging problem under…

Machine Learning · Computer Science 2025-02-27 Anming Gu , Edward Chien , Kristjan Greenewald

Multiple Object Tracking (MOT) has gained increasing attention due to its academic and commercial potential. Although different approaches have been proposed to tackle this problem, it still remains challenging due to factors like abrupt…

Computer Vision and Pattern Recognition · Computer Science 2022-02-14 Wenhan Luo , Junliang Xing , Anton Milan , Xiaoqin Zhang , Wei Liu , Tae-Kyun Kim

Continued adoption of agricultural robots postulates the farmer's trust in the reliability, robustness and safety of the new technology. This motivates our work on safety assurance of agricultural robots, particularly their ability to…

Robotics · Computer Science 2025-06-25 Mustafa Adam , Kangfeng Ye , David A. Anisi , Ana Cavalcanti , Jim Woodcock , Robert Morris

We introduce the Multiplicative Quasi-Instrumental Variable (MQIV) model, a framework for causal inference with unmeasured confounding that leverages an instrument that may be imperfectly exogenous. We allow the candidate quasi-instrument…

Methodology · Statistics 2026-05-13 Jiewen Liu , Chan Park , David Richardson , Eric J. Tchetgen Tchetgen

Partial Differential Equations (PDEs) are the bedrock for modern computational sciences and engineering, and inherently computationally expensive. While PDE foundation models have shown much promise for simulating such complex…

We make some general observations about partial orders on quotient spaces, and explore their use in music theory, in two different contexts. In the first, we show that many of the most familiar chord and scale types in Western music appear…

General Mathematics · Mathematics 2012-11-02 Marcus Pendergrass

Quantitative metrics are central to evaluating computer vision (CV) models, but they often fail to capture real-world performance due to protocol inconsistencies and ground-truth noise. While visual perception studies can complement these…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Ashkan Ganj , Yiqin Zhao , Tian Guo

Models are centrally important in many scientific fields. A model is a representation of a selected part of the world, which is the model s target system. Here, a system consists of a software portion as a component among many others.…

Software Engineering · Computer Science 2020-05-22 Sabah Al-Fedaghi

Optical systems are becoming increasingly important by resolving many bottlenecks in today's communication, electronics, and biomedical systems. However, given the continuous nature of optics, the inability to efficiently analyze optical…

Logic in Computer Science · Computer Science 2014-03-13 Sanaz Khan-Afshar , Umair Siddique , Mohamed Yousri Mahmoud , Vincent Aravantinos , Ons Seddiki , Osman Hasan , Sofiene Tahar

The Isabelle/PIDE platform addresses the question whether proof assistants of the LCF family are suitable as technological basis for educational tools. The traditionally strong logical foundations of systems like HOL, Coq, or Isabelle have…

Logic in Computer Science · Computer Science 2012-02-23 Makarius Wenzel , Burkhart Wolff

Experimental program review in our field may benefit from a more quantitative framework within which to quantitatively discuss the scientific merit of a proposed program of research, and to assess the scientific merit of a particular…

Data Analysis, Statistics and Probability · Physics 2007-12-24 Bruce Knuteson

Jackknife instrumental variable estimation (JIVE) is a classic method to leverage many weak instrumental variables (IVs) to estimate linear structural models, overcoming the bias of standard methods like two-stage least squares. In this…

Statistics Theory · Mathematics 2024-10-08 Aurélien Bibaut , Nathan Kallus , Apoorva Lal