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Liscio, E. (author)Human values are the abstract motivations that drive our opinions and actions. AI agents ought to align their behavior with our value preferences (the relative importance we ascribe to different values) to co-exist with us in our society. However, value preferences differ across individuals and are dependent on context. To reflect diversity in...doctoral thesis 2024
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Rijs, Joyce (author)<b>Background</b>: Undetected Intellectual Disability (ID) can lead to chronic stress due to overestimation by society. Chronic stress can cause stress-related health issues, like hypertension, chronic fatigue and abdominal complaints. When a physician (General Practitioner (GP) or medical specialist) does not recognize that a patient has ID,...master thesis 2024
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Foroughi, M. (author)This PhD thesis explores the evolving field of heritage planning, focusing on the cultural significance of heritage properties. It advocates for a value-based approach that recognizes the diverse perspectives of stakeholders, including experts, policymakers, and users. While participatory heritage aims to foster consensus-building, tensions may...doctoral thesis 2023
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Timmerman, Kirsten (author)When making decisions, people are automatically guided by their moral compass. However, AI agents need to be conditioned in order to be steered towards moral behaviour. An environment that can be used to train and test agents is the Jiminy Cricket environment. The Jiminy Cricket environment consists of a set of text-based narrative games, where...bachelor thesis 2023
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Lubbers, Rob (author)Nowadays Large Language Models are becoming more and more prevalent in today's society. These models act without a sense of morality however. They only prioritize accomplishing their goal. Currently, little research has been done evaluating these models. The current state of the art Reinforcement Learning models represent morality by a singular...bachelor thesis 2023
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Şerbănescu, Bianca (author)Morality is a fundamental concept that guides humans in the decision-making process. Given the rise of large language models in society, it is necessary to ensure that they adhere to human principles, among which morality is of substantial importance. While research has been done regarding artificial agents behaving morally, current state of the...bachelor thesis 2023
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Parankusam, Taneshwar Pranav (author)Federated Continual Learning (FCL) is a emerging field with strong roots in Image classification. However, limited research has been done on its potential in Natural Language Processing and Tabular datasets. With recent developments in A.I. with language models and the widespread use of mobile devices, it becomes relevant to consider FCL’s...bachelor thesis 2023
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de Kruif, Evan (author)In this research, a comparison between different Instance Attribution (IA) methods and k-Nearest Neighbors (kNN) via cosine similarity is conducted on a Natural Language Processing (NLP) machine learning model. The format in which the comparison is made is by way of a human survey and automated similarity comparisons of representative vectors....bachelor thesis 2023
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Shome, A. (author), Cruz, Luis (author), van Deursen, A. (author)Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive and cognitive process which demands a human-in-the-loop approach. Besides writing tests for the code base, bulk of the evaluation requires application of domain...conference paper 2023
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van Dinten, I. (author), Zaidman, A.E. (author), Panichella, A. (author)Test case prioritization techniques have emerged as effective strategies to optimize this process and mitigate the regression testing costs. Commonly, black-box heuristics guide optimal test ordering, leveraging information retrieval (e.g., cosine distance) to measure the test case distance and sort them accordingly. However, a challenge...conference paper 2023
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Szép, T. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)This paper proposes a new method to combine choice- and text data to infer moral motivations from people’s actions. To do this, we rely on moral rhetoric, in other words, extracting moral values from verbal expressions with Natural Language Processing techniques. We use moral rhetoric based on a well-established moral, psychological theory...journal article 2023
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Agiollo, A. (author), Cavalcante Siebert, L. (author), Murukannaiah, P.K. (author), Omicini, Andrea (author)Although popular and effective, large language models (LLM) are characterised by a performance vs. transparency trade-off that hinders their applicability to sensitive scenarios. This is the main reason behind many approaches focusing on local post-hoc explanations recently proposed by the XAI community. However, to the best of our knowledge,...conference paper 2023
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Al-Kaswan, Ali (author)Reverse engineering binaries is required to understand and analyse programs for which the source code is unavailable. Decompilers can transform the largely unreadable binaries into a more readable source code-like representation. However, many aspects of source code, such as variable names and comments, are lost during the compilation and...master thesis 2022
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Wang, Zhen (author)This thesis mainly studies the causality in natural language processing. Understanding causality is key to the success of NLP applications, especially in high-stakes domains. Causality comes in various perspectives such as enable and prevent that, despite their importance, have been largely ignored in the literature. In view of the lack of a...master thesis 2022
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van Woensel, Martijn (author)Commonsense knowledge based question answer- ing is a recent topic that has seen a surge in inter- est. Yet most models obtain general data, this pa- per looks at obtaining query-specific similar con- cepts using first and second-order proximity to- gether with BERT-based retrieval. Using these query-specific concepts new commonsense knowl- edge...bachelor thesis 2022
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Cosma, Bianca (author)<b>Motivation: </b>The development of automated protein function prediction models is essential in closing the gap between the large amount of protein sequence data available and the fraction of validly annotated data. Recent approaches to function prediction rely on unsupervised deep learning models, through which protein sequences are...bachelor thesis 2022
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Magyari, Reka (author)Clinical documentation takes up 40% of clinicians’ time. To ease the administrative burden of clinicians, digital scribes offer the potential to automate clinical note taking. Digital scribes are intelligent documentation softwares that combine automated speech recognition (ASR) and natural language processing (NLP). Digital scribes transcribe...master thesis 2022
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Izadi, M. (author)Users use Issue Tracking Systems to keep track and manage issue reports in their repositories. An issue is a rich source of software information that contains different reports including a problem, a request for new features, or merely a question about the software product. As the number of these issues increases, it becomes harder to manage...conference paper 2022
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Izadi, M. (author), Ahmadabadi, Martin Nili (author)NLP-based models have been increasingly incorporated to address SE problems. These models are either employed in the SE domain with little to no change, or they are greatly tailored to source code and its unique characteristics. Many of these approaches are considered to be outperforming or complementing existing solutions. However, an important...conference paper 2022
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Herzog, Rico (author)In the wake of more inclusive and sustainable cities, as targeted in the UN’s Sustainable Development Goal 11, public administrators and urban planners aspire to incorporate the pluralism of public values into decision making. Although theoretical work exists since the 1990, public values and their conflicts are yet to be empirically identified...master thesis 2021