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Philipp Brockmann, Sebastian Brulin, Ilia Roisman, Jeanette Hussong , "Enhancement of interfacial instabilities by solid particles during fast stretching of a liquid suspension bridge", Soft Matter, pp. 16, 2025.
AbstractIn this experimental study, the rapid stretching dynamics and interfacial instabilities of a suspension liquid bridge are investigated using a high-speed video system. The bridge is formed between two parallel plates with one plate remaining fixed, while the other propagates with a constant acceleration reaching up to 160 m/s2. In these experiments, the initial gap width ranges from 30 to 60 µm. Sizes of the solid particles within the suspensions...
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Riccardo Cadei and Christian Internó , "The Narcissus Hypothesis: Descending to the Rung of Illusion", NeurIPS 2025 Evaluating the Evolving LLM Lifecycle: Benchmarks, Emergent Abilities, and Scaling., 2025.
AbstractModern foundational models increasingly reflect not just world knowledge, but patterns of human preference embedded in their training data. We hypothesize that recursive alignment—via human feedback and model-generated corpora—induces a social desirability bias, nudging models to favor agreeable or flattering responses over objective reasoning. We refer to it as the Narcissus Hypothesis and test it across 31 models using standardized personality ...
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Nergiz Yuca, Nikolay Matyunin, Ektor Arzoglou, Nikolaos Athanasios Anagnostopoulos, Stefan Katzenbeisser , "A Survey on Privacy-Preserving Computing in the Automotive Domain", arXiv, 2025.
AbstractAs vehicles become increasingly connected and autonomous, they accumulate and manage various personal data, thereby presenting a key challenge in preserving privacy during data sharing and processing. This survey reviews applications of Secure Multi-Party Computation (MPC) and Homomorphic Encryption (HE) that address these privacy concerns in the automotive domain. First, we identify the scope of privacy-sensitive use cases for these technologie...
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Muhammad Ashfaq, Ahmed Sadik, Tommi Mikkonen, Muhammad Waseem, Niko Mäkitalo , "LLM-Enhanced Holonic Architecture for Self-Adaptive System of Systems", Springer book series - Communications in Computer and Information Science (CCIS), 2025.
AbstractAs modern system of systems (SoS) become increasingly adaptive and human-centred, traditional architectures often struggle to support interoperability, reconfigurability, and effective human-system interaction. This paper addresses these challenges by advancing the state-of-the-art holonic architecture for SoS, offering two main contributions to support these adaptive needs. First, we propose a layered architecture for holons, which includes rea...
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Simon Kohaut, Benedict Flade, Daniel Ochs, Devendra Dhami, Julian Eggert, Kristian Kersting , "Probabilistic Mission Design for Neuro-Symbolic Unmanned Aircraft Systems", Transactions on Intelligent Transportation Systems (Early Access), 2025.
AbstractAdvanced Air Mobility (AAM) is a growing field that demands accurate modeling of legal concepts and restrictions in navigating intelligent vehicles. Further, any implementation of AAM needs to face the challenges posed by inherently dynamic and uncertain human-inhabited spaces robustly. Nevertheless, the employment of Unmanned Aircraft Systems (UAS) beyond visual line of sight (BVLOS) is an endearing task that promises to enhance significantly to...
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Martina Hasenjäger and Christiane Wiebel , "On Utilizing Gaze Behavior to Predict Movement Transitions During Natural Human Walking on Different Terrains", PLoS One, vol. 20, no. 10, pp. e0334093, 2025.
AbstractUnderstanding and predicting human walk behavior is an important prerequisite for a proper design of physical assist robot control. One challenge for such systems is the accurate and timely prediction of walk transitions. To improve models based on gait behavior only, prior work has investigated the effect of exploiting visual sensor data. Only few works have included human visual behavior, even though gaze plays a significant role for successful...
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Tim Kochs, Andrea Castellani, Felix Lanfermann, Barbara Hammer , "Evaluating and Mitigating Fairness Risks in Machine Learning under Structured Missing Data", AEQUITAS 2025 , vol. 4147, pp. 17, 2025.
AbstractHandling missing values in machine learning presents significant challenges, impacting both model predictive performance and fairness. While unstructured missingness, where values are absent randomly, has been extensively studied, structured missingness remains relatively underexplored. Structured missingness occurs when the absence of one or more features correlates with or influences the absence of others. In this paper, we investigate the i...
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Faez Ahmed, Cyril Picard, Wei Chen, Christopher McComb, Pingfeng Wang, Ikjin Lee, Tino Stankovic, Douglas Allaire, Stefan Menzel , "Special Issue: Design by Data: Cultivating Datasets for Engineering Design", Journal of Mechanical Design, 2025.
AbstractThe transformative impact of data-driven methods, which have revolutionized fields like image and text analysis, relies on the availability of adequately large and diverse datasets. These datasets have fueled breakthroughs in deep learning, enabling the development of useful AI tools such as ChatGPT, Gemini, Llama, and Stable Diffusion. Similarly, in engineering design, data-driven methodologies are reshaping traditional paradigms—enhancing desig...
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Christian Internó, Robert Geirhos, Markus Olhofer, Sunny Liu, Barbara Hammer, David Klindt , "AI-Generated Video Detection via Perceptual Straightening", Neural Information Processing Systems (NeurIPS2025), 2025.
AbstractThe rapid advancement of generative AI enables highly realistic synthetic video, posing significant challenges for content authentication and raising urgent concerns about misuse. Existing detection methods often struggle with generalization and capturing subtle temporal inconsistencies. We propose ReStraV (Representation Straightening for Video), a novel approach to distinguish natural from AI-generated videos. Inspired by the “perceptual straig...
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Felix Ocker, Stefan Menzel, Ahmed Sadik, Thiago de Jesus de Araujo Rios , "From Idea to CAD: A Language Model-Driven Multi-Agent System for Collaborative Design ", arXiv, 2025.
AbstractCreating digital models using Computer Aided Design (CAD) is a process that requires in-depth expertise. In industrial product development, this process typically involves entire teams of engineers, spanning requirements engineering, CAD itself, and quality assurance. We present an approach that mirrors this team structure with a Vision Language Model (VLM)-based Multi Agent System, with access to parametric CAD tooling and tool documentation. Co...
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