activity
20232026
most citedTwenty-Four Years of Empirical Research on Trust in AI: A Bibliometric Review of Trends, Overlooked Issues, and Future Directions

59 citations · 61 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

I Don't Miss You, but I Do: Self-Explanation Faithfulness of Modality Missingness in Vision-Language Models

Aydin Javadov, Daniel Schoess, Florian von Wangenheim

Vision-language models are increasingly used in settings where some input modalities may be unavailable, yet we know little about whether they can faithfully explain how such missi…

cs.IR2026

MESSY STREETS: A Benchmark for Geocoding Real-World Addresses

Edward Gaere, Florian von Wangenheim

We introduce MESSY STREETS, a benchmark for evaluating geocoders on verbatim web addresses, with existence verification and controlled measurement of surface-form divergence. Unlik…

cs.LG2026

NeuReasoner: Theory-grounded Mapping of Reasoning Elicitation Boundaries

Aydin Javadov, Shyngys Aitkazinov, Tobias Hoesli +3

A growing body of work suggests that the reasoning capabilities of large language models are largely latent in their base form, with post-training primarily amplifying rather than…

cs.HC2026

Detecting Drunk Driving Using Off-the-Shelf Smartwatches

Robin Deuber, Lanlan Yang, Michal Bechny +9

Alcohol-impaired driving remains a major yet preventable cause of road traffic injury and death, with many drivers underestimating their level of intoxication. Compared to in-vehic…

stat.ME2026

Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects

Joel Persson, Jurriën Bakker, Dennis Bohle +2

Heterogeneous treatment effects (HTEs) are increasingly estimated using machine learning models that produce highly personalized predictions of treatment effects. In practice, howe…

cs.LG2025

RAxSS: Retrieval-Augmented Sparse Sampling for Explainable Variable-Length Medical Time Series Classification

Aydin Javadov, Samir Garibov, Tobias Hoesli +4

Medical time series analysis is challenging due to data sparsity, noise, and highly variable recording lengths. Prior work has shown that stochastic sparse sampling effectively han…