arXiv subjects

Sebastian Maier

Publications and source records attributed to Sebastian Maier.

15 recordsLinked to original sources

arXiv2026

AutoSynthesis: An agentic system for automated meta-analysis

Evidence synthesis is crucial for turning primary research into reliable knowledge for science, medicine, education, and policy. Yet, quantitative evidence synthesis remains largely manual and difficult to scale. Here, we introduce AutoSynthesis, an end-to-end multi-agent system for automated meta-analysis. Given a research question in natural language, AutoSynthesis formulates a search strategy, retrieves scientific literature, screens candidate studies, assesses full-text eligibility, extracts quantitative statistics, computes standardized effect sizes, and finally performs random-effects meta-analysis. AutoSynthesis further supports heterogeneity analysis to examine how effect sizes vary across moderators, as well as risk-of-bias assessment. As output, AutoSynthesis produces a transparent report aligned with PRISMA guidelines. In our application, AutoSynthesis screened over 28 studies and extracted more than 20 quantitative claims. The pooled effect estimates produced by AutoSynthesis are similar to Hedges' $g$ of expert-conducted meta-analyses, indicating close agreement with manual evidence synthesis. Together, these results show that AutoSynthesis can make quantitative evidence synthesis more scalable, thereby supporting evidence-based decision-making across disciplines.

cs.AI↗

arXiv2026

A meta-analysis of the effect of generative AI on productivity and learning in programming

Generative artificial intelligence (GenAI) is increasingly used for programming, yet it remains unclear when and where GenAI tools lead to productivity gains. Evidence on the effects of GenAI on the long-term development of programming skills is similarly mixed. Here, we present a meta-analysis of $n = 23$ studies reporting $k = 27$ effect sizes to quantify the effect of GenAI-powered coding assistants on productivity and learning. We systematically searched (i) ACM, (ii) arXiv, (iii) Scopus, and (iv) Web of Science for studies published between 2019 and 2025. Studies were required to compare GenAI-assisted with unassisted programming using quantitative measures of (1) productivity (i.e., task completion time, commits, and lines of code) and (2) learning (i.e., exam performance). We assessed the risk of bias using RoB2 and ROBINS-I and compared standardized effect sizes using Hedges' $g$. We find a statistically significant, but moderate positive effect of GenAI assistance on developer productivity ($g = 0.33$, $95\%$ CI: $[0.09, 0.58]$), yet with substantial heterogeneity across settings. Notably, productivity gains tend to be larger in controlled experimental settings, while effects are smaller in open-source and enterprise contexts. In contrast, we find no statistically significant effect of GenAI assistance on learning outcomes ($g = 0.14$, $95\%$ CI: $[-0.18, 0.47]$). Overall, these results highlight that GenAI coding assistants can increase developer productivity, although these gains depend strongly on context. In educational settings, however, the use of GenAI does not consistently translate into improved learning or skill development, which highlights the need for careful integration of GenAI into computer science education.

cs.SE↗

arXiv2026

Supporting Effective Goal Setting with LLM-Based Chatbots

Each day, individuals set behavioral goals such as eating healthier, exercising regularly, or increasing productivity. While psychological frameworks (i.e., goal setting and implementation intentions) can be helpful, they often need structured external support, which interactive technologies can provide. We thus explored how large language model (LLM)-based chatbots can apply these frameworks to guide users in setting more effective goals. We conducted a preregistered randomized controlled experiment ($N = 543$) comparing chatbots with different combinations of three design features: guidance, suggestions, and feedback. We evaluated goal quality using subjective and objective measures. We found that, while guidance is already helpful, it is the addition of feedback that makes LLM-based chatbots effective in supporting participants' goal setting. In contrast, adaptive suggestions were less effective. Altogether, our study shows how to design chatbots by operationalizing psychological frameworks to provide effective support for reaching behavioral goals.

cs.HC↗

arXiv2025

A Meta-Analysis of the Persuasive Power of Large Language Models

Large language models (LLMs) are increasingly used for persuasion, such as in political communication and marketing, where they affect how people think, choose, and act. Yet, empirical findings on the effectiveness of LLMs in persuasion compared to humans remain inconsistent. The aim of this study was to systematically review and meta-analytically assess whether LLMs differ from humans in persuasive effectiveness. We identified $7$ studies with 17,422 participants primarily recruited from English-speaking countries and $12$ effect size estimates. Egger's test indicated potential small-study effects ($p = .018$), but the trim-and-fill analysis did not impute any missing studies, suggesting a low risk of publication bias. We then compute the standardized effect sizes based on Hedges' $g$. The results show no significant overall difference in persuasive performance between LLMs and humans ($g = 0.02$, $p = .530$). However, we observe substantial heterogeneity across studies ($I^2 = 75.97\%$), suggesting that persuasiveness strongly depends on contextual factors. In separate exploratory moderator analyses, no individual factor (e.g., LLM model, conversation design, or domain) reached statistical significance, which may be due to the limited number of studies. When considered jointly in a combined model, these factors explained a large proportion of the between-study variance ($R^2 = 81.93\%$), and residual heterogeneity is low ($I^2 = 35.51\%$). Although based on a small number of studies, this suggests that differences in LLM model, conversation design, and domain are important contextual factors in shaping persuasive performance, and that single-factor tests may understate their influence. Our results highlight that LLMs can match human performance in persuasion, but their success depends strongly on how they are implemented and embedded in communication contexts.

cs.HC↗

arXiv2025

Partnering with Generative AI: Experimental Evaluation of Human-Led and Model-Led Interaction in Human-AI Co-Creation

Large language models (LLMs) show strong potential to support creative tasks, but the role of the interface design is poorly understood. In particular, the effect of different modes of collaboration between humans and LLMs on co-creation outcomes is unclear. To test this, we conducted a randomized controlled experiment ($N = 486$) comparing: (a) two variants of reflective, human-led modes in which the LLM elicits elaboration through suggestions or questions, against (b) a proactive, model-led mode in which the LLM independently rewrites ideas. By assessing the effects on idea quality, diversity, and perceived ownership, we found that the model-led mode substantially improved idea quality but reduced idea diversity and users' perceived idea ownership. The reflective, human-led mode also improved idea quality, yet while preserving diversity and ownership. We independently validated the findings in a different context ($N = 640$). Our findings highlight the importance of designing interactions with generative AI systems as reflective thought partners that complement human strengths and augment creative processes.

cs.HC↗

arXiv2025

Generative AI and Creativity: A Systematic Literature Review and Meta-Analysis

Generative artificial intelligence (GenAI) is increasingly used to support a wide range of human tasks, yet empirical evidence on its effect on creativity remains scattered. Can GenAI generate ideas that are creative? To what extent can it support humans in generating ideas that are both creative and diverse? In this study, we conduct a meta-analysis to evaluate the effect of GenAI on the performance in creative tasks. For this, we first perform a systematic literature search, based on which we identify n = 28 relevant studies (m = 8214 participants) for inclusion in our meta-analysis. We then compute standardized effect sizes based on Hedges' g. We compare different outcomes: (i) how creative GenAI is; (ii) how creative humans augmented by GenAI are; and (iii) the diversity of ideas by humans augmented by GenAI. Our results show no significant difference in creative performance between GenAI and humans (g = -0.05), while humans collaborating with GenAI significantly outperform those working without assistance (g = 0.27). However, GenAI has a significant negative effect on the diversity of ideas for such collaborations between humans and GenAI (g = -0.86). We further analyze heterogeneity across different GenAI models (e.g., GPT-3.5, GPT-4), different tasks (e.g., creative writing, ideation, divergent thinking), and different participant populations (e.g., laypeople, business, academia). Overall, our results position GenAI as an augmentative tool that can support, rather than replace, human creativity-particularly in tasks benefiting from ideation support.

cs.HC↗

arXiv2025

Assortment optimization given basket shopping behavior using the Ising model

In markets where customers tend to purchase baskets of products rather than single products, assortment optimization is a major challenge for retailers. Removing a product from a retailer's assortment can result in a severe drop in aggregate demand if this product is a complement to other products. Therefore, accounting for the complementarity effect is essential when making assortment decisions. In this paper, we develop a modeling framework designed to address this problem. We model customers' choices using a Markov random field -- in particular, the Ising model -- which captures pairwise demand dependencies as well as the individual attractiveness of each product. Using the Ising model allows us to leverage existing methodologies for various purposes including parameter estimation and efficient simulation of customer choices. We formulate the assortment optimization problem under this model and show that it is APX-hard. We also provide multiple theoretical insights into the structure of the optimal assortments based on the graphical representation of the Ising model, and propose several heuristic algorithms that can be used to obtain high-quality solutions to the assortment optimization problem. Our numerical analysis demonstrates that the developed simulated annealing procedure leads to an expected profit gain of 15% compared to offering an unoptimized assortment (where all products are included) and around 5% compared to using a revenue-ordered heuristic algorithm.

math.OC↗

arXiv2024

Simulation of the impact of an additional corrugated structure impedance on the bursting dynamics in an electron storage ring

In the case of single-digit picosecond bunch length, synchrotron light sources produce intense coherent radiation up to the THz range. The reduction of the bunch length by lowering the momentum compaction factor (low-$\alpha$) gives rise to the micro-bunching instability, which is on one hand a crucial roadblock in the X-ray range during to the resulting effective bunch lengthening but on the other hand also an opportunity for the generation of intense THz radiation if it can be controlled appropriately. In the KIT storage ring KARA (Karlsruhe Research Accelerator), two parallel plates with periodic rectangular corrugations are planned to be installed in an electron storage ring. These plates create an additional longitudinal impedance based on their geometry, which can affect the beam dynamics. The resulting impedance manipulation will be used to study and control the longitudinal electron beam dynamics and the emitted coherent synchrotron radiation (CSR). This paper presents the results of systematic studies in simulation of the impact of additional corrugated plate impedances on the longitudinal beam dynamics using the example of the KARA storage ring. If the periodicity of the wake function of the corrugated plates matches the size of the substructures in the longitudinal bunch profile, the instability threshold can be effectively manipulated. This extends intense THz radiation to different beam current regimes.

physics.acc-ph↗

arXiv2021

Detuning Properties of RF Phase Modulation in an Electron Storage Ring

In electron storage rings, it is possible to increase the bunch length by applying phase modulation to the radio frequency accelerating field by choosing appropriate parameters for the modulation. Such a bunch lengthening effect improves beam parameters such as beam lifetime, which can help us achieve better beam stability. It is well known that the modulation frequency around the double synchrotron frequency is effective in lengthening the bunch. The dependence of bunch lengthening on modulation frequency, the so-called detuning property, has a peak around the double synchrotron frequency with a frequency width that depends on the modulation amplitude. Nonlinear effects due to phase modulation lead to a peak frequency shift in a negative direction from the double synchrotron frequency, accompanied by an asymmetric peak shape. Beam current also affects the properties of the detuning condition of such bunch lengthening. We investigated the detuning property using a theoretical model and systematic measurements at the electron storage ring KARA, and we verified the qualitative agreement between the experiments and the theoretical model. The macro-particle simulations have confirmed the agreement.

physics.acc-ph↗

arXiv2016

Deterministic implementation of a bright, on-demand single photon source with near-unity indistinguishability via quantum dot imaging

Deterministic techniques enabling the implementation and engineering of bright and coherent solid-state quantum light sources are key for the reliable realization of a next generation of quantum devices. Such a technology, at best, should allow one to significantly scale up the number of implemented devices within a given processing time. In this work, we discuss a possible technology platform for such a scaling procedure, relying on the application of nanoscale quantum dot imaging to the pillar microcavity architecture, which promises to combine very high photon extraction efficiency and indistinguishability. We discuss the alignment technology in detail, and present the optical characterization of a selected device which features a strongly Purcell-enhanced emission output. This device, which yields an extraction efficiency of $η=(49\pm4)~\%$, facilitates the emission of photons with $(94\pm2.7)~\%$ indistinguishability.

physics.optics↗

arXiv2015

Highly indistinguishable on-demand resonance fluorescence photons from a deterministic quantum dot micropillar device with 75 $\%$ extraction efficiency

The implementation and engineering of bright and coherent solid state quantum light sources is key for the realization of both on chip and remote quantum networks. Despite tremendous efforts for more than 15 years, the combination of these two key prerequisites in a single, potentially scalable device is a major challenge. Here, we report on the observation of bright and coherent single photon emission generated via pulsed, resonance fluorescence conditions from a single quantum dot (QD) deterministically centered in a micropillar cavity device via cryogenic optical lithography. The brightness of the QD fluorescence is greatly enhanced on resonance with the fundamental mode of the pillar, leading to an overall device efficiency of $η=(74\pm4)~\%$ for a single photon emission as pure as $g^{(2)}(0)=0.0092\pm0.0004$. The combination of large Purcell enhancement and resonant pumping conditions allows us to observe a two-photon wave packet overlap up to $ν=(88\pm3)~\%$

quant-ph↗

arXiv2015

Deterministic generation of bright single resonance fluorescence photons from a Purcell-enhanced quantum dot-micropillar system

We report on the observation of bright emission of single photons under pulsed resonance fluorescence conditions from a single quantum dot (QD) in a micropillar cavity. The brightness of the QD fluorescence is greatly enhanced via the coupling to the fundamental mode of a micropillar, allowing us to determine a single photon extraction efficiency of $(20.7\pm0.8)~\%$ per linear polarization basis. This yields an overall extraction efficiency of $(41.4\pm1.5)~\%$ in our device. We observe the first Rabi-oscillation in a weakly coupled quantum dot-micropillar system under coherent pulsed optical excitation, which enables us to deterministically populate the excited QD state. In this configuration, we probe the single photon statistics of the device yielding $g^{(2)}(0)=0.072\pm0.011$ at a QD-cavity detuning of $75~μ$eV.

quant-ph↗

arXiv2015

Observation of resonance fluorescence and the Mollow-triplet from a coherently driven site-controlled quantum dot

Resonant excitation of solid state quantum emitters has the potential to deterministically excite a localized exciton while ensuring a maximally coherent emission. In this work, we demonstrate the coherent coupling of an exciton localized in a lithographically positioned, site-controlled semiconductor quantum dot to an external resonant laser field. For strong continuous-wave driving we observe the characteristic Mollow triplet and analyze the Rabi splitting and sideband widths as a function of driving strength and temperature. The sideband widths increase linearly with temperature and the square of the driving strength, which we explain via coupling of the exciton to longitudinal acoustic phonons. We also find an increase of the Rabi splitting with temperature, which indicates a temperature induced delocalization of the excitonic wave function resulting in an increase of the oscillator strength. Finally, we demonstrate coherent control of the exciton excited state population via pulsed resonant excitation and observe a damping of the Rabi oscillations with increasing pulse area, which is consistent with our exciton-photon coupling model. We believe that our work outlines the possibility to implement fully scalable platforms of solid state quantum emitters. The latter is one of the key prerequisites for more advanced, integrated nanophotonic quantum circuits.

quant-ph↗

arXiv2015

A charged quantum dot micropillar system for deterministic light matter interactions

Quantum dots (QDs) are semiconductor nanostructures in which a three dimensional potential trap produces an electronic quantum confinement, thus mimicking the behaviour of single atomic dipole-like transitions. However unlike atoms, QDs can be incorporated into solid state photonic devices such as cavities or waveguides that enhance the light-matter interaction. A near unit efficiency light-matter interaction is essential for deterministic, scalable quantum information (QI) devices. In this limit, a single photon input into the device will undergo a large rotation of the polarization of the light field due to the strong interaction with the QD. In this paper we measure a macroscopic ($\sim6^o$) phase shift of light as a result of the interaction with a negatively charged QD coupled to a low quality-factor (Q$\sim290$) pillar microcavity. This unexpectedly large rotation angle demonstrates this simple low Q-factor design would enable near deterministic light-matter interactions.

quant-ph↗

arXiv2013

Downconversion quantum interface for a single quantum dot spin and 1550-nm single-photon channel

Long-distance quantum communication networks require appropriate interfaces between matter qubit-based nodes and low-loss photonic quantum channels. We implement a downconversion quantum interface, where the single photons emitted from a semiconductor quantum dot at 910 nm are downconverted to 1560 nm using a fiber-coupled periodically poled lithium niobate waveguide and a 2.2-$μ$m pulsed pump laser. The single-photon character of the quantum dot emission is preserved during the downconversion process: we measure a cross-correlation $g^{(2)}(τ= 0) = 0.17$ using resonant excitation of the quantum dot. We show that the downconversion interface is fully compatible with coherent optical control of the quantum dot electron spin through the observation of Rabi oscillations in the downconverted photon counts. These results represent a critical step towards a long-distance hybrid quantum network in which subsystems operating at different wavelengths are connected through quantum frequency conversion devices and 1.5-$μ$m quantum channels.

quant-ph↗