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Utrecht University Repository: Recent submissions

  • AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks 
    Yang, Yimin; Mehrkanoon, Siamak (Institute of Electrical and Electronics Engineers Inc., 2022)
    Data driven modeling based approaches have recently gained a lot of attention in many challenging meteoro-logical applications including weather element forecasting. This paper introduces a novel data-driven predictive ...
  • A Computational Framework for Organizing and Querying Cultural Heritage Archives 
    de Mooij, Jan; Kurtan, Can; Baas, Jurian; Dastani, Mehdi (Association for Computing Machinery (ACM), 2022-09)
    Now that within the humanities more and more data sources have been created, a new opportunity is within reach: the searching of patterns spanning across data sources from archives, museums, and other cultural heritage ...
  • Towards Meaningful Paragraph Embeddings for Data-Scarce Domains: A Case Study in the Legal Domain 
    Herrewijnen, Elize; Craandijk, Dennis F. W. (CEUR-WS.org, 2023)
    Creating meaningful text embeddings using BERT-based language models involves pre-training on large amounts of data. For domain-specific use cases where data is scarce (e.g., the law enforcement domain) it might not be ...
  • Deep feature annotation by iterative meta-pseudo-labeling on 2D projections 
    Benato, Bárbara; Telea, Alex; Falcao, Alexandre (Elsevier, 2023-09)
    The absence of large annotated datasets to train deep neural networks (DNNs) is an issue since manual annotation is time-consuming, expensive, and error-prone. Semi-supervised learning techniques can address the problem ...
  • Post-Newtonian Gravitational and Scalar Waves in Scalar-Gauss-Bonnet Gravity 
    Shiralilou, Banafsheh; Hinderer, Tanja; Nissanke, Samaya M.; Witek, Helvi; Ortiz, Néstor (IOP PUBLISHING LTD, 2022)
    Gravitational waves emitted by black hole binary inspiral and mergers enable unprecedented strong-field tests of gravity, requiring accurate theoretical modelling of the expected signals in extensions of General Relativity. ...
  • Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans 
    Prather, James; Denny, Paul; Leinonen, Juho; Becker, Brett A.; Albluwi, Ibrahim; Caspersen, Michael E.; Craig, Michelle; Keuning, Hieke; Kiesler, Natalie; Kohn, Tobias; Luxton-Reilly, Andrew; MacNeil, Stephen; Petersen, Andrew; Pettit, Raymond; Reeves, Brent N.; Savelka, Jaromir (Association for Computing Machinery (ACM), 2023-06-29)
    The recent advent of highly accurate and scalable large language models (LLMs) has taken the world by storm. From art to essays to computer code, LLMs are producing novel content that until recently was thought only humans ...
  • Generating systems and representability for symplectic capacities 
    Joksimović, Dušan; Ziltener, Fabian (International Press of Boston, Inc., 2022)
    We consider the problem by K. Cieliebak, H. Hofer, J. Latschev, and F. Schlenk (CHLS) that is concerned with finding a minimal generating system for (symplectic) capacities on a given symplectic category. We show that under ...
  • Agglomerative Clustering of Growing Squares 
    Castermans, Thom; Speckmann, Bettina; Staals, Frank; Verbeek, Kevin (Springer New York, 2022)
    We study an agglomerative clustering problem motivated by interactive glyphs in geo-visualization. Consider a set of disjoint square glyphs on an interactive map. When the user zooms out, the glyphs grow in size relative ...
  • Using Evolutionary Algorithms to Target Complexity Levels in Game Economies 
    Rogers, Katja; Claire, Vincent Le; Frommel, Julian; Mandryk, Regan; Nacke, Lennart E. (Institute of Electrical and Electronics Engineers Inc., 2023-03-01)
    Game economies (GEs) describe how resources in games are created, transformed, or exchanged: They underpin most games and exist in different complexities. Their complexity may directly impact player difficulty. Nevertheless, ...
  • There and Back Again: On the Reconstructability and Rediscoverability of Typed Jackson Nets 
    Barenholz, Daniël; Montali, Marco; Polyvyanyy, Artem; Reijers, Hajo; Rivkin, Andrey; van der Werf, Jan Martijn (Springer, 2023)
    A process discovery algorithm aims to construct a model from data generated by historical system executions such that the model describes the system well. Consequently, one desired property of a process discovery algorithm ...
  • Varieties of specification: Redefining over-and under-specification 
    Chen, Guanyi; van Deemter, Kees (Elsevier, 2023-10)
    A long tradition of research in theoretical, experimental and computational pragmatics has investigated over-specification and under-specification in referring expressions. Along broadly Gricean lines, these studies compare ...
  • Taking the Law More Seriously by Investigating Design Choices in Machine Learning Prediction Research 
    Steging, Cor; Renooij, Silja; Verheij, Bart (CEUR WS, 2023)
    Approaches to court case prediction using machine learning differ widely with varying levels of success and legal reasonableness. In part this is due to some aspects of law, such as justification, being inherently difficult ...
  • Computational Modelling of Quantifier Use: Corpus, Models, and Evaluation 
    Chen, Guanyi; van Deemter, Kees (Morgan Kaufmann Publishers, Inc., 2023-05-30)
    A prominent strand of work in formal semantics investigates the ways in which human languages quantify the elements of a set, as when we say All A are B, Few A are B, and so on. Building on a growing body of empirical ...
  • An Experimental Evaluation of Grouping Definitions for Moving Entities 
    Wiratma, Lionov; van Kreveld, Marc; Löffler, Maarten; Staals, Frank (The National Center for Geographic Information and Analysis (NCGIA), 2022)
    One important pattern analysis task for trajectory data is to find a group: a set of entities that travel together over a period of time. In this paper, we compare four definitions of groups by conducting extensive experiments ...
  • Outsider Writing: The Healing Art of Robert Walser 
    Brillenburg Wurth, C.A.W. (2021)
    I approach Robert Walser’s miniature pencil scripts (known as the Bleistiftgebiet) not as the symptom of a disordered mind, but as the graphic archive of a healing process: a meticulous and repetitive, meditative activity; ...
  • Visualizing High-Dimensional Functions with Dense Maps 
    Espadoto, Mateus; Rodrigues, Francisco; Hirata, Nina; Telea, Alex (Springer Nature Singapore, 2023-05)
    Multivariate functions have a central place in the development of techniques present many domains, such as machine learning and optimization research. However, only a few visual techniques exist to help users understand ...
  • Shortest Paths in Portalgons 
    Löffler, Maarten; Ophelders, Tim; Silveira, Rodrigo I.; Staals, Frank (Dagstuhl Publishing, 2023-06-01)
    Any surface that is intrinsically polyhedral can be represented by a collection of simple polygons (fragments), glued along pairs of equally long oriented edges, where each fragment is endowed with the geodesic metric ...
  • Does ChatGPT have Theory of Mind? 
    Holterman, Bart; van Deemter, Kees (arXiv, 2023-05-23)
    Theory of Mind (ToM) is the ability to understand human thinking and decision-making, an ability that plays a crucial role in social interaction between people, including linguistic communication. This paper investigates ...
  • Using Agent-Based Simulations to Evaluate Bayesian Networks for Criminal Scenarios 
    Leeuwen, van, Ludi; Verheij, Bart; Verbrugge, Rineke; Renooij, Silja (ACM Press, 2023-06-19)
    Scenario-based Bayesian networks (BNs) have been proposed as a tool for the rational handling of evidence. The proper evaluation of existing methods requires access to a ground truth that can be used to test the quality ...
  • Non-neural Models Matter: A Re-evaluation of Neural Referring Expression Generation Systems 
    Same, Fahime; Chen, Guanyi; van Deemter, Kees (ACL Anthology, 2022-05)
    In recent years, neural models have often outperformed rule-based and classic Machine Learning approaches in NLG. These classic approaches are now often disregarded, for example when new neural models are evaluated. We ...