Measuring the Outcome of sXAI - Thommes, Kirsten (Social Explainable AI)
Abstract Quantitatively evaluating the benefits of eXplainable Artificial Intelligence (XAI) and social XAI for humans is not a trivial pursuit. Therefore, we categorize the potential measures in terms of subjective and objective outcomes and short- and long-term outcomes of interactive social XAI. When reviewing the current state of the art, we observed some measurement problems in the literature: (a) Researchers do not clearly state whether they want to measure the inner state of users, users’ behavioral response, or the overall AI-human collaborative performance. (b) Moreover, most measures implicitly assume that all humans either do not react or improve in attitudes or performance. Psychological reactance (feeling or doing the opposite) is usually not captured. (c) Many researchers invent their own scale when measuring psychological constructs, thereby jeopardizing the validity of their measures and slowing down progress in the field, because general evidence and subsequent learning can be achieved only by collecting many compatible pieces of evidence. (d) Most studies look into short-term outcomes and neglect that experiences in social interactions with XAI may evolve and have long-term outcomes not only for the individual but also for groups or society at large.

Operationalizing Social Interaction - Wachsmuth, Henning; Thommes, Kirsten; Alshomary, Milad (Social Explainable AI)
Abstract Explainable AI (XAI) aims to make the decisions and behavior of an AI understandable to the people interacting with it and to those affected by its outcomes. To make XAI social, real-world XAI systems need to simulate not only the ways in which human explainers behave within explanatory dialogs but also the ways in which such dialogs can successfully achieve the intended understanding on the explainee’s side. This, in turn, requires an operationalization of the three core aspects of social XAI: multimodality, incrementality, and patterns. This chapter lays the ground for this goal by defining a basic operational model of social interactions that can be refined and extended to account for the specificities of any explanatory real-world setting. This serves as a basis for summarizing and discussing existing ideas from explainability research and related areas in order to operationalize each core aspect. Selected examples and case studies illustrate how to concretely realize such an operationalization, thereby serving as a starting point for future research on social interaction with XAI.

Exploration of Explaining Content - Främling, Kary; Wrede, Britta; Thommes, Kirsten (Social Explainable AI)
Abstract This chapter examines key challenges and potential improvements in the areas of user interaction and dynamic explanations. It highlights the need for XAI systems to address context factors beyond their predefined scope, it points to the potential need to cocreate new concepts that are adapted to particular explainees, and it provides a clear overview of the XAI system’s underlying knowledge structure and interaction steps. Emphasis is placed on mixed-initiative interaction in which the system can lead or respond based on the context and the explainee’s reactions while asserting the importance of maintaining coherence across consecutive explanations. These advances aim to make XAI systems more flexible, interactive, and user-centric. An operationalization section outlines how such social XAI systems could be implemented based on the XAI capabilities provided by the Contextual Importance and Utility XAI method described in the previous chapter.

Interaction History in Social XAI - Thommes, Kirsten; Främling, Kary; Wrede, Britta; Kubler, Sylvain (Social Explainable AI)
Abstract Much research in XAI focuses on single, one-shot interactions, implicitly assuming that interactions have no past, no future, and no surroundings. Although this assumption may be necessary for many empirical research settings, it is overly simplifying and unrealistic. Whereas empirical research focuses on a world in which no social context exists, real applications are embedded in a temporal (past and future) and social context. Social science research shows that repeated interactions and secondhand knowledge in the social space massively affect human attitudes and behaviors. This chapter explains how not only repeated interactions between XAI and humans but also the social space and secondhand information may affect social XAI research.

Evaluation Principles - Thommes, Kirsten (Social Explainable AI)
Abstract In the past, there has been much research aiming to evaluate XAI practices—that is, explanations that can add to a user’s understanding of “why” or “why not.” However, because there is such a huge amount of diversity in social contexts, optimizing for the mean neglects the social dimensions of to whom, what, why, when, and where explanations are provided. Nonetheless, these dimensions matter. We give some brief examples on the accuracy of the mental model (as an example for who?), on measuring explanation practices (as an example of what?), on human motivation (as an example of why?), on repeated interactions (as an example of when), and on bystander effects (as an example of where?). Importantly, controlling for these factors (or randomizing them) is as important as attempting to perform external validations.

Förderung sozial-emotionaler Kompetenzen von Kindern für das kooperative Lernen im diversitätssensiblen Mathematikunterricht der Grundschule (soko-M). Posterpräsentation auf der 13. Tagung der Gesellschaft für Empirische Bildungsforschung (GEBF). Thema: „Bildungsforschung für technologiebedingte gesellschaftliche Entwicklungen“. - Knickenberg, Margarita; Löper, Marwin Felix; Grosche, Michael; Grüßing, Meike; Hellmich, Frank

NeMo.bil - Individualisierter öffentlicher Personennahverkehr - iÖV - Marten, Thorsten; Ostermann, Moritz; Behm, Jonathan; Leitenmaier, Samuel (Berufsbildung - Zeitschrift für Theorie-Praxis-Dialog)

Möglichkeiten der Förderung der sozialen Partizipation in der inklusiven Grundschule. Workshop auf dem 10. Paderborner Grundschultag. Thema: „Zukunft gemeinsam gestalten – Bildung für nachhaltige Entwicklung von Anfang an“. - Hellmich, Frank; Löper, Marwin Felix; Görel, Gamze

Fast Multi-Tau Correlators on FPGA with Context Switching From and to High- Bandwidth Memory - Tareen, Abdul Rehman; Plessl, Christian; Kenter, Tobias (2025 International Conference on Field Programmable Technology (ICFPT))
Various methods to measure the dynamic behavior of particles require the calculation of autocorrelation functions. For this purpose, fast multi-tau correlators have been developed in dedicated hardware, in software, and on FPGAs. However, for methods such as X-ray Photon Correlation Spectroscopy (XPCS), which requires to calculate the autocorrelation function independently for hundreds of thousands to millions of pixels from high-resolution detectors, current approaches rely on offline processing after data acquisition. Moreover, the internal pipeline state of so many independent correlators is far too large to keep it on-chip. In this work, we propose a design approach on FPGAs, where pipeline contexts are stored in off-chip HBM memory. Each compute unit iteratively loads the state for a single pixel, processes a short time series for this pixel, and afterwards writes back the context in a dataflow pipeline. We have implemented the required compute kernels with Vitis HLS and analyze resulting designs on an Alveo U280 card. The design achieves the expected performance and for the first time provides sufficient throughput for current high-end detectors used in XPCS.

Components of an explanation for co-constructive sXAI - Vollmer, Anna-Lisa; Buhl, Heike M.; Alami, Rachid; Främling, Kary; Grimminger, Angela; Booshehri, Meisam; Ngonga Ngomo, Axel-Cyrille (Social Explainable AI)

Models of the situation, the explanandum, and the interaction partner - Buhl, Heike M.; Vollmer, Anna-Lisa; Alami, Rachid; Booshehri, Meisam; Främling, Kary (Social explainable AI)

Adaptation - Buhl, Heike M.; Wrede, Britta; Fisher, Josephine Beryl; Matarese, Marco (Social Explainable AI)

Optimal Control of Voltage-Forming Grid Inverters by Model Predictive Control and Reinforcement Learning - Weber, Daniel; Schmies, Dominik; Lange, Jarren H.; Schenke, Maximilian; Wallscheid, Oliver (IEEE Access)

Reinforcement Learning-Based Control of Voltage-Forming Grid Inverters With Arbitrary Loads - Weber, Daniel; Lange, Jarren; Wallscheid, Oliver (IEEE Journal of Emerging and Selected Topics in Industrial Electronics)

Comparison of fixture-based and manual fiber integration in adhesive joints: Effects on strain signal quality - Hermelingmeier, Lucas; Beule, Felix; Teutenberg, Dominik; Meschut, Gerson (International Journal of Adhesion and Adhesives)

Toward integrated sensors for optimized optical coherence tomography with undetected photons - Roeder, Franz; Pollmann, René; Quiring, Viktor; Eigner, Christof; Brecht, Benjamin; Silberhorn, Christine (Physical Review Applied)
The development of practical sensors for optical coherence tomography (OCT) with undetected photons requires miniaturization via integration. To be practical, these sensors must exhibit a large spectral bandwidth and a high brightness, which are linked to a high axial resolution and a sufficient signal-to-noise ratio, respectively. Here, we combine these requirements in a scheme for OCT measurements with undetected photons based on nonlinear <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi>Ti</a:mi> <a:mo>:</a:mo> <a:msub> <a:mrow> <a:mi>Li</a:mi> <a:mi>Nb</a:mi> <a:mi mathvariant="normal">O</a:mi> </a:mrow> <a:mn>3</a:mn> </a:msub> </a:math> waveguides. We investigate the performance benchmarks of the commonly used SU(1,1) scheme in comparison to an induced-coherence scheme and find that the latter is actually better suited when implementing measurements with undetected photons in integrated systems. In both schemes, we perform pump-gain optimization and OCT measurements with undetected photons with an axial resolution as low as <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" display="inline"> <d:mn>28</d:mn> <d:mspace width="0.2em"/> <d:mtext fontfamily="times">μ</d:mtext> <d:mrow> <d:mi mathvariant="normal">m</d:mi> </d:mrow> </d:math> .

Quantum-limited detection of the arrival time and the carrier frequency of time-dependent signals - Folge, Patrick Fabian; Serino, Laura Maria; Mišta, Ladislav; Brecht, Benjamin; Silberhorn, Christine; Řeháček, Jaroslav; Hradil, Zdeněk (Optica)
Precise measurements of both the arrival time and carrier frequency of light pulses are essential for time–frequency-encoded quantum technologies. Quantum mechanics, however, imposes fundamental limits on the simultaneous determination of these quantities. In this work, we derive and experimentally verify the quantum uncertainty bounds governing joint time–frequency measurements. We show that when detection is restricted to finite time windows, the problem is naturally described by a quantum rotor, rendering the commonly used Heisenberg uncertainty relation inapplicable. We further propose an optimal detection scheme that saturates these fundamental limits. By sampling the Q -function, we demonstrate the reconstruction of the Wigner function beyond the harmonic oscillator. Using an experimental implementation based on a quantum pulse gate, we confirm that the proposed scheme approaches the ultimate quantum limit for simultaneous time–frequency measurements. These results provide a framework for joint time–frequency detection with direct implications for precision measurements and quantum information processing.

Molecular lithography with DNA nanostructures: Methods and applications - Keller, Adrian Clemens; Linko, Veikko (Journal of Physics D: Applied Physics)
Abstract Lithographic surface patterning is a cornerstone of modern materials and device fabrication. Although the available lithography techniques are constantly being advanced to push the feature sizes down to the few-nanometer scale, such developments are associated with many technological and economic challenges. Combining established top-down lithography with bottom-up self-assembly strategies has the potential to overcome those challenges and enable the manipulation of matter with molecular precision. One of the most exciting approaches in this regard is to harness the programmability of DNA self-assembly to create precise DNA nanostructure masks to be used in the lithographic patterning of diverse substrates. DNA nanotechnology has provided us with a versatile toolbox for the high-yield synthesis of 2D and 3D nanostructures with complex, user-defined shapes at unprecedented molecular accuracy. Consequently, the last decade has seen intense research efforts aimed at transferring such DNA nanostructure shapes into functional organic and inorganic materials and we have now arrived at a point where sophisticated molecular lithography approaches utilize DNA nanostructure masks for the fabrication of plasmonic surfaces for metamaterials and sensing applications. This review summarizes how the spatial information of such DNA nanostructure masks can be transferred into various organic and inorganic materials through selective etching and deposition steps. The review also discusses recent developments toward all-purpose molecular lithography schemes and highlights promising extensions of the discussed methods toward new materials systems and application fields.

Cayley Commutator-free Methods for Krotov-Type Algorithms in Quantum Optimal Control - Wembe, Boris; Ali, Usman; Meier, Torsten; Ober-Blöbaum, Sina
This paper presents a class of structure-preserving numerical methods for quantum optimal control problems, based on commutator-free Cayley integrators. Starting from the Krotov framework, we reformulate the forward and backward propagation steps using Cayley-type schemes that preserve unitarity and symmetry at the discrete level. This approach eliminates the need for matrix exponentials and commutators, leading to significant computational savings while maintaining higher-order accuracy. We first recall the standard linear setting and then extend the formulation to nonlinear Schrödinger and Gross-Pitaevskii equations using a Cayley-polynomial interpolation strategy. Numerical experiments on state-transfer problems illustrate that the CF-Cayley method achieves the same accuracy as high-order exponential or Cayley-Magnus schemes at substantially lower cost, especially for longtime or highly oscillatory dynamics. In the nonlinear regime, the structure-preserving properties of the method ensure stability and norm conservation, making it a robust tool for large-scale quantum control simulations. The proposed framework thus bridges geometric integration and optimal control, offering an efficient and reliable alternative to existing exponential-based propagators.

Practical considerations for assignment of photon numbers with SNSPDs - Schapeler, Timon; Mischke, Isabell; Schlue, Fabian; Stefszky, Michael; Brecht, Benjamin; Silberhorn, Christine; Bartley, Tim (APL Quantum)
Superconducting nanowire single-photon detectors (SNSPDs) can enable photon-number resolution (PNR) based on accurate measurements of the detector’s response time to few-photon optical pulses. In this work, we investigate the impact of the optical pulse shape and duration on the accuracy of this method. We find that Gaussian temporal pulse shapes yield cleaner arrival-time histograms and, thus, more accurate PNR, compared to bandpass-filtered pulses of equal bandwidth. For low system jitter and an optical pulse duration comparable to the other jitter contributions, photon numbers can be discriminated in our system with a commercial SNSPD. At 60 ps optical pulse duration, photon-number discrimination is significantly reduced. Furthermore, we highlight the importance of using the correct arrival-time histogram model when analyzing photon-number assignment. Using exponentially modified Gaussian distributions, instead of the commonly used Gaussian distributions, we can more accurately determine photon-number misidentification probabilities. Finally, we reconstruct the positive operator-valued measures of the detector, revealing sharp features that indicate the intrinsic PNR capabilities.