8 citations · 16 across the 8 of their papers we have counts for
9 papers
The Pushback Paradox: A Two-Probe Diagnostic for Language Model Compliance
Stefan Bühler, David Exler, Markus Reischl +1
Are language models compliant with user instructions? A model that always complies can be stopped but also exploited, while one that always resists can be neither exploited nor sto…
TINY_SCHILLER: A Drop-In German Drama Corpus for Small Language Models
Mark Schutera
tiny_schiller closes the small-language-model prototyping, fine-tuning, education, and research gap for German literary text, providing a single-file, drop-in counterpart to Karpat…
!Imperio, smolVLA: The Implications of Data Poisoning on Open Source Robotics
Stefan Bühler, Mark Schutera
This work establishes that trigger-word data poisoning of vision language action models is practical, while at the same time the open-source robotics ecosystem holds trust assumpti…
Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters
David Exler, Mark Schutera, Markus Reischl +1
With the increasing prevalence of artificial intelligence, careful evaluation of inherent biases needs to be conducted to form the basis for alleviating the effects these predispos…
PERSONA: A Reproducible Testbed for Pluralistic Alignment
Louis Castricato, Nathan Lile, Rafael Rafailov +2
The rapid advancement of language models (LMs) necessitates robust alignment with diverse user values. However, current preference optimization approaches often fail to capture the…
Assessing Political Bias in Large Language Models
Luca Rettenberger, Markus Reischl, Mark Schutera
The assessment of bias within Large Language Models (LLMs) has emerged as a critical concern in the contemporary discourse surrounding Artificial Intelligence (AI) in the context o…
Defensive Perception: Estimation and Monitoring of Neural Network Performance under Deployment
Hendrik Vogt, Stefan Buehler, Mark Schutera
In this paper, we propose a method for addressing the issue of unnoticed catastrophic deployment and domain shift in neural networks for semantic segmentation in autonomous driving…
Distributed traffic light control at uncoupled intersections with real-world topology by deep reinforcement learning
Mark Schutera, Niklas Goby, Stefan Smolarek +1
This work examines the implications of uncoupled intersections with local real-world topology and sensor setup on traffic light control approaches. Control approaches are evaluated…
Transfer Learning versus Multi-agent Learning regarding Distributed Decision-Making in Highway Traffic
Mark Schutera, Niklas Goby, Dirk Neumann +1
Transportation and traffic are currently undergoing a rapid increase in terms of both scale and complexity. At the same time, an increasing share of traffic participants are being…