Searched for: subject%3A%22Explainable%255C+AI%22
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Brouwer, Lucie (author)
master thesis 2024
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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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Wang, Sunwei (author)
With the increasing development of artificial intelligence (AI), there is a more significant opportunity for humans and agents to collaborate in teamwork. In Human-Agent Teamwork (HAT) settings, collaboration requires communication, and the agent displaying emotion can impact how human teammates communicate and work together with the agent. This...
master thesis 2024
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Buzcu, Berk (author), Tessa, Melissa (author), Tchappi, Igor (author), Najjar, Amro (author), Hulstijn, Joris (author), Calvaresi, Davide (author), Aydoğan, Reyhan (author)
The awareness about healthy lifestyles is increasing, opening to personalized intelligent health coaching applications. A demand for more than mere suggestions and mechanistic interactions has driven attention to nutrition virtual coaching systems (NVC) as a bridge between human–machine interaction and recommender, informative, persuasive,...
journal article 2024
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Hu, M. (author), Yue, N. (author), Groves, R.M. (author)
With the increasing application of artificial intelligence (AI) techniques in the field of structural health monitoring (SHM), there is a growing interest in explaining the decision-making of the black-box models in deep learning-based SHM methods. In this work, we take explainability a step further by using it to improve the performance of...
journal article 2024
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Hu, M. (author), Yue, N. (author), Groves, R.M. (author)
With the improvements in computational power and advances in chip and sensor technology, the applications of machine learning (ML) technologies in structural health monitoring (SHM) are increasing rapidly. Compared with traditional methods, deep learning based SHM (Deep SHM) methods are more efficient and have a higher accuracy. However, due...
journal article 2024
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Katzy, J.B. (author)
Large language models have become increasingly utilized in programming contexts. However, due to the recent emergence of this trend, some aspects have been overlooked. We propose a research approach that investigates the inner mechanics of transformer networks, on a neuron, layer, and output representation level, to understand whether there...
conference paper 2024
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Corti, L. (author), Oltmans, R.F.A. (author), Jung, Jiwon (author), Balayn, A.M.A. (author), Wijsenbeek, Marlies (author), Yang, J. (author)
Clinicians increasingly pay attention to Artificial Intelligence (AI) to improve the quality and timeliness of their services. There are converging opinions on the need for Explainable AI (XAI) in healthcare. However, prior work considers explanations as stationary entities with no account for the temporal dynamics of patient care. In this work,...
conference paper 2024
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Wehner, Jan (author)
Learning rewards from humans is a promising approach to aligning AI with human values. However, methods are not able to consistently extract the correct reward functions from demonstrations or feedback. To allow humans to understand the limitations and misalignments of a learned reward function we adopt the technique of counterfactual...
master thesis 2023
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Hacipoğlu, Sara (author)
The complexity of deep neural rankers and large datasets make it increasingly more challenging to understand why a document is predicted as relevant to a given query. A growing body of work focuses on interpreting ranking models with different explainable AI methods. Instance attribution methods aim to explain individual predictions of machine...
master thesis 2023
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Zhou, Jing (author)
Explainable AI (XAI) has gained increasing attention from more and more researchers with an aim to improve human interaction with AI systems. In the context of human-agent teamwork (HAT), providing explainability to the agent helps to increase shared team knowledge and belief, therefore improving overall teamwork. With various backgrounds and...
master thesis 2023
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Karnani, Simran (author)
In recent years, there has been a growing interest among researchers in the explainability, fairness, and robustness of Computer Vision models. While studies have explored the usability of these models for end users, limited research has delved into the challenges and requirements faced by researchers investigating these requirements. This study...
master thesis 2023
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Polak, Max (author)
Incipient slip detection plays an important role in human and robotic grasping. With the growing use of deep learning in vision-based tactile sensing, the black-box nature of these deep neural networks (DNNs) makes it difficult to analyze, debug, and validate their behavior and learned patterns. To fill this gap, eXplainable AI (XAI) methods...
master thesis 2023
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Deb, Sreeparna (author)
A 2022 Harvard Business Review report critically examines the readiness of AI for real-world decision-making. The report cited several incidents, like an experimental healthcare chatbot suggesting a mock patient commit suicide in response to their distress or when a self-driving car experiment was called off after it resulted in the death of a...
master thesis 2023
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Cheng, Yuxing (author)
master thesis 2023
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Aishwarya, Nilay (author)
As AI is progressively incorporated into several spheres of society. This rapid growth has also brought a lot of challenges such as discriminating or skewed results and a lack of accountability. To address these challenges, there is a growing interest in Human-AI teams where AI-assisted decision-making includes humans in the loop. This approach...
master thesis 2023
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Germanov, Pavel (author)
Trust in negotiation agents plays a crucial role in their adoption and utilization. However, there is not enough research on what factors influence it. This paper aims to investigate how different explanations of a negotiation agent’s strategy affect human trust and decision-making. Specifically, it compares the effects of a truthful explanation...
bachelor thesis 2023
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Hasdemir, Deniz Tan (author)
Negotiations have an essential role in our lives as they help us to find mutually beneficial solutions and resolve conflicts. It leads to effective communication and collaboration between the involved parties. Negotiation among parties has high importance to have an outcome that is suitable for all. In such scenarios, negotiation agents can be...
bachelor thesis 2023
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Rajiv, Miny (author)
Responding to the trend of increasing use of artificial intelligence (AI), we need to ensure applications of AI are designed, implemented, utilised and evaluated in a careful manner. Explainable AI, or XAI, meaning; - given a certain audience, the details and reasons of both technical processes of the algorithm-support system and the reasoning...
master thesis 2023
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van Graft, Tijmen (author)
Metabolic engineering is an important field in biotechnology, aimed at optimizing cellular processes to produce desired compounds. In this thesis, we focus on predicting the metabolome from the proteome, as understanding this relationship is crucial for understanding cellular metabolism. We investigate the usage of additional biological...
master thesis 2023
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