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Protecting online privacy requires users to engage with and comprehend website privacy policies, but many policies are difficult and tedious to read. We present the first qualitative user study on Large Language Model (LLM)-driven privacy policy assessment. To this end, we build and evaluate an LLM-based privacy policy assessment browser extension, which helps users understand the essence of a lengthy, complex privacy policy while browsing. The tool integrates a dashboard and an LLM chat. In our qualitative user study (N=22), we evaluate usability, understandability of the information our tool provides, and its impacts on awareness. While providing a comprehensible quick overview and a chat for in-depth discussion improves privacy awareness, users note issues with building trust in the tool. From our insights, we derive important design implications to guide future policy analysis tools., Comment: 6 pages without appendices and references, 12 pages total, 3 figures, poster at CHI 2025. arXiv admin note: text overlap with arXiv:2501.16033

Biomechanical models allow for diverse simulations of user movements in interaction. Their performance depends critically on the careful design of reward functions, yet the interplay between reward components and emergent behaviours remains poorly understood. We investigate what makes a model "breathe" by systematically analysing the impact of rewarding effort minimisation, task completion, and target proximity on movement trajectories. Using a choice reaction task as a test-bed, we find that a combination of completion bonus and proximity incentives is essential for task success. Effort terms are optional, but can help avoid irregularities if scaled appropriately. Our work offers practical insights for HCI designers to create realistic simulations without needing deep reinforcement learning expertise, advancing the use of simulations as a powerful tool for interaction design and evaluation in HCI., Comment: 10 pages, 3 figures, 2 tables; CHI 25 LBW

Overtaking on country roads with possible opposing traffic is a dangerous maneuver and many proposed assistant systems assume car-to-car communication and sensors currently unavailable in cars. To overcome this limitation, we develop an assistant that uses simple in-car sensors to predict the required sight distance for safe overtaking. Our models predict this from vehicle speeds, accelerations, and 3D map data. In a user study with a Virtual Reality driving simulator (N=25), we compare two UI variants (monitoring-focused vs scheduling-focused). The results reveal that both UIs enable more patient driving and thus increase overall driving safety. While the monitoring-focused UI achieves higher System Usability Score and distracts drivers less, the preferred UI depends on personal preference. Driving data shows predictions were off at times. We investigate and discuss this in a comparison of our models to actual driving behavior and identify crucial model parameters and assumptions that significantly improve model predictions., Comment: 23 pages, 27 figures, 2 tables, ACM CHI 2025

Protecting online privacy requires users to engage with and comprehend website privacy policies, but many policies are difficult and tedious to read. We present PRISMe (Privacy Risk Information Scanner for Me), a novel Large Language Model (LLM)-driven privacy policy assessment tool, which helps users to understand the essence of a lengthy, complex privacy policy while browsing. The tool, a browser extension, integrates a dashboard and an LLM chat. One major contribution is the first rigorous evaluation of such a tool. In a mixed-methods user study (N=22), we evaluate PRISMe's efficiency, usability, understandability of the provided information, and impacts on awareness. While our tool improves privacy awareness by providing a comprehensible quick overview and a quality chat for in-depth discussion, users note issues with consistency and building trust in the tool. From our insights, we derive important design implications to guide future policy analysis tools., Comment: 30 pages

We present a systematic study of the nucleon-electron tensor-pseudotensor (Ne-TPT) interaction in candidate molecules for next-generation experimental searches for new sources of charge-parity violation. The considered molecules are all amenable to assembly from laser-cooled atoms, with the francium-silver (FrAg) molecule previously shown to be the most sensitive to the Schiff moment interaction in this set. Interelectron correlation effects are treated through relativistic general-excitation-rank configuration-interaction theory in the framework of the Dirac-Coulomb Hamiltonian. We find in FrAg the Ne-TPT interaction constant to be $W_T({\text{Fr}}) = 2.58 \pm 0.21 [\left<\Sigma\right>_A \mathrm{kHz}]$, considering the Francium atom as target of the measurement. Taking into account nuclear structure in a multi-source interpretation of a measured electric dipole moment, FrAg is found to be an excellent probe of physics beyond the Standard Model as this system will in addition to its sizeable Ne-TPT interaction constant greatly constrain fundamental parameters such as the quantum-chromo-dynamic $\bar{\theta}$ or the semileptonic four-fermion interaction $C_{lequ}$ from which nuclear and atomic ${\cal{CP}}$-violating properties arise., Comment: 15 pages, 0 figures

An electronically variational approach to the calculation of atomic hyperfine structure transition energies under the influence of static external electric fields is presented. The method avoids the calculation of intermediate atomic states entirely and requires only the wavefunctions of the electronic states involved in the respective hyperfine levels. These wavefunctions are obtained through relativistic general-excitation-rank configuration interaction theory. The method also enables for calculations on atoms with the most complicated of shell structures. The initial applications include $^{87}$Rb and $^{133}$Cs where very good agreement of the approach with literature results is established. For $^{169}$Tm that is used in the development of atomic clocks the differential static electric dipole polarizability between ground levels $J=\frac{7}{2}$ and $J=\frac{5}{2}$ is calculated to be $\Delta\alpha = -0.23 \pm 0.11$ \au The hyperfine Stark coefficient for the hyperfine levels belonging to the ground term with $J=\frac{7}{2}$ is found to be $k = (1.3 \pm 1.0) \times 10^{-13}$ [Hz/((V/m)$^2$)]. This coefficient is several orders of magnitude smaller than the corresponding coefficients in $^{87}$Rb and $^{133}$Cs., Comment: 18 pages, no figures

This paper explores the integration of visual communication and musical interaction by implementing a robotic camera within a "Guided Harmony" musical game. We aim to examine co-creative behaviors between human musicians and robotic systems. Our research explores existing methodologies like improvisational game pieces and extends these concepts to include robotic participation using a PTZ camera. The robotic system interprets and responds to nonverbal cues from musicians, creating a collaborative and adaptive musical experience. This initial case study underscores the importance of intuitive visual communication channels. We also propose future research directions, including parameters for refining the visual cue toolkit and data collection methods to understand human-machine co-creativity further. Our findings contribute to the broader understanding of machine intelligence in augmenting human creativity, particularly in musical settings.

The increasing demand for energy storage solutions has spurred intensive research into next-generation battery technologies. Oxygen-ion batteries (OIBs), which leverage mixed ionic-electronic conducting (MIEC) oxides, have emerged as promising candidates due to their solid, non-flammable nature and potential for high power densities. This study investigates the use of over-stoichiometric La2NiO4+delta (L2NO4) as a cathode material for OIBs, exploring its capacity for electrochemical energy storage. Half-cell measurements reveal that L2NO4 with a closed-pore microstructure can store oxygen, achieving a volumetric charge of 63 mA.h.cm-3 at 400 {\deg}C with a current density of 3.6 uA.cm-2 and potentials up to 0.75 V vs. 1 bar O2. Additionally, a functional full cell combining over-stoichiometric L2NO4 and under-stoichiometric La0.5Sr0.5Cr0.2Mn0.8O3-delta (LSCrMn) has been successfully developed, demonstrating excellent cyclability and coulomb efficiency. The full cell reaches a maximum volumetric charge of 90 mA.h.cm-3 at 400 {\deg}C, 17.8 uA.cm-2, and a cut-off voltage of 1.8 V. This proof of concept underscores the viability of combining over- and under-stoichiometric MIEC materials in OIBs and provides critical insights into optimizing electrode materials and tuning oxygen content for improved performance. This research lays the groundwork for future advancements in OIB technology, aiming to develop materials with lower resistance and higher efficiency.

Automated biomechanical testing has great potential for the development of VR applications, as initial insights into user behaviour can be gained in silico early in the design process. In particular, it allows prediction of user movements and ergonomic variables, such as fatigue, prior to conducting user studies. However, there is a fundamental disconnect between simulators hosting state-of-the-art biomechanical user models and simulators used to develop and run VR applications. Existing user simulators often struggle to capture the intricacies of real-world VR applications, reducing ecological validity of user predictions. In this paper, we introduce SIM2VR, a system that aligns user simulation with a given VR application by establishing a continuous closed loop between the two processes. This, for the first time, enables training simulated users directly in the same VR application that real users interact with. We demonstrate that SIM2VR can predict differences in user performance, ergonomics and strategies in a fast-paced, dynamic arcade game. In order to expand the scope of automated biomechanical testing beyond simple visuomotor tasks, advances in cognitive models and reward function design will be needed., Comment: 23 pages, 10 figures, 1 tables; Supplementary Material: 5 pages, 4 figures, 1 table

Leptoquark models may explain deviations from the Standard Model observed in decay processes involving heavy quarks at high-energy colliders. Such models give rise to low-energy parity- and time-reversal-violating phenomena in atoms and molecules. One of the leading effects among these phenomena is the nucleon-electron tensor-pseudotensor interaction when the low-energy experimental probe uses a quantum state of an atom or molecule predominantly characterized by closed electron shells. In the present paper the molecular interaction constant for the nucleon-electron tensor-pseudotensor interaction in the thallium-fluoride molecule -- used as such a sensitive probe by the CeNTREX collaboration [Quantum Sci. Technol., 6:044007, 2021] -- is calculated employing highly-correlated relativistic many-body theory. Accounting for up to quintuple excitations in the wavefunction expansion the final result is $W_T({\text{Tl)}} = -6.25 \pm 0.31\, $[$10^{-13} {\langle\Sigma\rangle}_A$ a.u.] Interelectron correlation effects on the tensor-pseudotensor interaction are studied for the first time in a molecule, and a common framework for the calculation of such effects in atoms and molecules is presented., Comment: 16 pages, 2 figures

We systematically study a set of strongly polar heteronuclear diatomic molecules composed of laser-coolable atoms for their suitability as sensitive probes of new charge-parity violation in the hadron sector of matter. Using relativistic general-excitation-rank configuration interaction theory we single out the molecule francium-silver (FrAg) as the most promising system in this set and calculate its nuclear Schiff-moment interaction constant to $W^\mathrm{FrAg}_{SM}(\mathrm{Fr}) = 30168 \pm 2504\mathrm{a.u.}$ for the target nucleus Fr. Our work includes the development of system-tailored atomic Gaussian basis sets for the target atom in each respective molecule., Comment: 16 pages, 10 tables

Constitutive equations are used in electromagnetic field simulations to model a material response to applied fields or forces. The $B(H)$ characteristic of iron laminations depends on thermal and mechanical stresses that may have occurred during the manufacturing process. Data-driven modelling and updating of the $B(H)$ characteristic are therefore well known necessities. In this work the $B(H)$ curve of an iron yoke of an accelerator magnet is updated based on observed magnetic flux density data by solving a non-linear inverse problem. The inverse problem is regularized by restricting the solution to the function space that is spanned by the truncated Karhunen Loeve expansion of a stochastic $B(H)$-curve model based on material measurements. It is shown that this method is able to retrieve a previously selected ground truth $B(H)$-curve. With the update of the $B(H)$ characteristic, the numerical model gains predictive capacities for excitation currents that were not included in the data.

Accelerator magnets made from blocks of permanent magnets in a zero-clearance configuration are known as Halbach arrays. The objective of this work is the fusion of knowledge from different measurement sources (material and field) and domain knowledge (magnetostatics) to obtain an updated magnet model of a Halbach array. From Helmholtz-coil measurements of the magnetized blocks, a prior distribution of the magnetization is estimated. Measurements of the magnetic flux density are used to derive, by means of Bayesian inference, a posterior distribution. The method is validated on simulated data and applied to measurements of a dipole of the FASER detector. The updated magnet model of the FASER dipole describes the magnetic flux density one order of magnitude better than the prior magnet model.

Research in the past years introduced Steered Mixture-of-Experts (SMoE) as a framework to form sparse, edge-aware models for 2D- and higher dimensional pixel data, applicable to compression, denoising, and beyond, and capable to compete with state-of-the-art compression methods. To circumvent the computationally demanding, iterative optimization method used in prior works an autoencoder design is introduced that reduces the run-time drastically while simultaneously improving reconstruction quality for block-based SMoE approaches. Coupling a deep encoder network with a shallow, parameter-free SMoE decoder enforces an efficent and explainable latent representation. Our initial work on the autoencoder design presented a simple model, with limited applicability to compression and beyond. In this paper, we build on the foundation of the first autoencoder design and improve the reconstruction quality by expanding it to models of higher complexity and different block sizes. Furthermore, we improve the noise robustness of the autoencoder for SMoE denoising applications. Our results reveal that the newly adapted autoencoders allow ultra-fast estimation of parameters for complex SMoE models with excellent reconstruction quality, both for noise free input and under severe noise. This enables the SMoE image model framework for a wide range of image processing applications, including compression, noise reduction, and super-resolution.

Every interaction of a living organism with its environment involves the placement of a bet. Armed with partial knowledge about a stochastic world, the organism must decide its next step or near-term strategy, an act that implicitly or explicitly involves the assumption of a model of the world. Better information about environmental statistics can improve the bet quality, but in practice resources for information gathering are always limited. We argue that theories of optimal inference dictate that ``complex'' models are harder to infer with bounded information and lead to larger prediction errors. Thus, we propose a principle of ``playing it safe'' where, given finite information gathering capacity, biological systems should be biased towards simpler models of the world, and thereby to less risky betting strategies. In the framework of Bayesian inference, we show that there is an optimally safe adaptation strategy determined by the Bayesian prior. We then demonstrate that, in the context of stochastic phenotypic switching by bacteria, implementation of our principle of ``playing it safe'' increases fitness (population growth rate) of the bacterial collective. We suggest that the principle applies broadly to problems of adaptation, learning and evolution, and illuminates the types of environments in which organisms are able to thrive., Comment: 23 pages, 10 figures; replotted figs S1-S3; corrected typos; added references

The traditional user-centered design process can hardly keep up with the ever faster technical development and increasingly diverse user preferences. As a solution, we propose to augment the tried-and-tested approach of conducting user studies with simulation and optimization of the entire human-computer interaction loop. This approach allows to better understand phenomena through explicit modeling, build virtual prototypes through simulation, and improve interaction techniques through optimization. Building predictive user models also supports the creation and validation of HCI theories, and constitutes a decisive step towards new, intelligent, and adaptive user interfaces. We report our experience in virtually developing new interaction techniques on the example of acoustic levitation, and present our optimization-based framework for HCI. With this, we strive to gain a better understanding of interaction and at the same time feed the discussion on questions such as which tools and tutorials are necessary to make virtual prototyping more accessible to different audiences., Comment: 8 pages, 3 figures. Submitted as extended abstract to CHI 2023 workshop on "Future of Computational Approaches for Understanding & Adapting User Interfaces"

A method for highly accurate calculations of atomic electric quadrupole moments (EQM) is presented, using relativistic general-excitation-rank configuration interaction wavefunctions based on Dirac spinors. Application to the clock transition states of the thulium atom employing up to full Quadruple excitations for the atomic wavefunction yields a final value of $Q_{zz}({^2F}_{7/2}) = 0.07 \pm 0.07$ a.u., establishing that the thulium electronic ground state has an exceptionally small EQM. A detailed analysis of this result is presented which has implications for EQMs of other atoms with unpaired $f$ electrons., Comment: 16 pages, 1 figure

Complex, multivariable systems are often analyzed by grouping their constituent units into components, sometimes referred to as latent features, which afford physical or biological interpretation. However, a priori many different types of latent features and data decompositions can be defined, and one typically uses a trial and error approach to determine a decomposition that is natural to the system and its data. It is highly desirable to develop principled understanding of which decomposition is appropriate for given a data set. In this work, we take a step in this direction and argue that sample-sample correlations in the data carry important information to this effect. For this we construct a generative random latent feature matrix model of large data based on linear mixing of latent features. Key ingredient of our model is that we allow for statistical dependence between the mixing coefficients and argue that the model captures characteristic properties found in many types of natural data. Latent dimensionality and correlation patterns of the data are controlled by only two model parameters. The model's data patterns include (overlapping) clusters, sparse mixing, and constrained (non-negative) mixing. We describe the characteristic correlation and eigenvalue distributions of each pattern. Finally, we fit the model on correlation data from natural images and find a near perfect match with the sparse mixing regime of our model. This finding is in line with the well-known sparse coding structure in natural scene images and provides information about the appropriate data decomposition, namely a sparse coding scheme. We believe that our work will deliver similar insights for diverse data of biological systems., Comment: 15 pages, 8 figures

Steered-Mixtures-of-Experts (SMoE) models provide sparse, edge-aware representations, applicable to many use-cases in image processing. This includes denoising, super-resolution and compression of 2D- and higher dimensional pixel data. Recent works for image compression indicate that compression of images based on SMoE models can provide competitive performance to the state-of-the-art. Unfortunately, the iterative model-building process at the encoder comes with excessive computational demands. In this paper we introduce a novel edge-aware Autoencoder (AE) strategy designed to avoid the time-consuming iterative optimization of SMoE models. This is done by directly mapping pixel blocks to model parameters for compression, in spirit similar to recent works on "unfolding" of algorithms, while maintaining full compatibility to the established SMoE framework. With our plug-in AE encoder, we achieve a quantum-leap in performance with encoder run-time savings by a factor of 500 to 1000 with even improved image reconstruction quality. For image compression the plug-in AE encoder has real-time properties and improves RD-performance compared to our previous works.

We present a method to simulate movement in interaction with computers, using Model Predictive Control (MPC). The method starts from understanding interaction from an Optimal Feedback Control (OFC) perspective. We assume that users aim to minimize an internalized cost function, subject to the constraints imposed by the human body and the interactive system. In contrast to previous linear approaches used in HCI, MPC can compute optimal controls for nonlinear systems. This allows us to use state-of-the-art biomechanical models and handle nonlinearities that occur in almost any interactive system. Instead of torque actuation, our model employs second-order muscles acting directly at the joints. We compare three different cost functions and evaluate the simulated trajectories against user movements in a Fitts' Law type pointing study with four different interaction techniques. Our results show that the combination of distance, control, and joint acceleration cost matches individual users' movements best, and predicts movements with an accuracy that is within the between-user variance. To aid HCI researchers and designers, we introduce CFAT, a novel method to identify maximum voluntary torques in joint-actuated models based on experimental data, and give practical advice on how to simulate human movement for different users, interaction techniques, and tasks., Comment: 34 pages, 17 figures, two appendices. Submitted to TOCHI

The TaO$^+$ cation is an attractive molecular species to search for parity- and time-reversal-violating interactions, in particular of hadronic origin. For the spectroscopic detection and preparation of TaO$^+$ cation in a desired state detailed knowledge of spectroscopic and electric properties in excited states is essential information. In this work we present spectroscopy constants for TaO$^+$ in the electronic ground and 29 excited states calculated with relativistic configuration interaction theory. The equilibrium bond lengths ($R_\mathrm{e}$), harmonic vibrational frequencies ($\omega_\mathrm{e}$), transition dipole moments (TDM), vertical excitation energies and static molecular dipole moments (PDM) are summarized. We include a detailed characterization of all electronic states in terms of their spinor occupations. This work supports the realization of experiments using TaO$^+$ ions to search for new physics beyond the standard model of elementary particles.

Static electric dipole moments of nondegenerate systems probe mass scales for physics beyond the Standard Model well beyond those reached directly at high energy colliders. Discrimination between different physics models, however, requires complementary searches in atomic-molecular-and-optical, nuclear and particle physics. In this report, we discuss the current status and prospects in the near future for a compelling suite of such experiments, along with developments needed in the encompassing theoretical framework., Comment: Contribution to Snowmass 2021; updated with community edits and endorsements

We present relativistic many-body calculations of atomic and molecular Schiff-moment interaction constants including interelectron correlation effects using atomic Gaussian basis sets specifically optimized for the Schiff interaction. Our present best results employing a Gaussian nuclear density function are $\alpha_{\text{SM}} = (0.364 \pm 0.025) \times 10^{-17} \frac{e \text{cm}}{e \text{fm}^3}$ for atomic $^{129}$Xe, $\alpha_{\text{SM}} = (-2.40 \pm 0.24) \times 10^{-17} \frac{e \text{cm}}{e \text{fm}^3}$ for atomic $^{199}$Hg, and $W_{\text{SM}} = (39967\pm 3600)$ a.u. for the thallium nucleus in the molecule $^{205}$TlF. We discuss agreements and discrepancies between our present results and those from earlier calculations on the atoms $^{129}$Xe and $^{199}$Hg. Using the most recent measurements of ${\cal{P,T}}$-odd electric dipole moments and the present interaction constants reliable upper bounds on the Schiff moments of the $^{199}$Hg and $^{205}$Tl nuclei are determined in the context of a single-source assumption., Comment: 24 pages, 1 figure

Acoustic levitation has recently demonstrated the ability to create volumetric content by trapping and quickly moving particles along reference paths to reveal shapes in mid-air. However, the problem of specifying physically feasible trap trajectories to display desired shapes remains unsolved. Even if only the final shape is of interest to the content creator, the trap trajectories need to determine where and when the traps need to be, for the particle to reveal the intended shape. We propose OptiTrap, the first structured numerical approach to compute trap trajectories for acoustic levitation displays. Our approach generates trap trajectories that are physically feasible and nearly time-optimal, and reveal generic mid-air shapes, given only a reference path (i.e., a shape with no time information). We provide a multi-dimensional model of the acoustic forces around a trap to model the trap-particle system dynamics and compute optimal trap trajectories by formulating and solving a non-linear path following problem. We formulate our approach and evaluate it, demonstrating how OptiTrap consistently produces feasible and nearly optimal paths, with increases in size, frequency, and accuracy of the shapes rendered, allowing us to demonstrate larger and more complex shapes than ever shown to date., Comment: 14 pages, 9 figures, 4 tables. To appear in the ACM Transaction on Graphics journal