137 citations · 241 across the 15 of their papers we have counts for
16 papers
From Structured Records to Patient Narratives: Preserving Clinical Alignment in LLM-Generated Health Summaries
Bayram Ayadi, Florian Geissler, Johanna Schmidhuber
As wearable and digital health systems increasingly generate longitudinal physiological records, communicating these observations in patient-accessible language remains a significa…
Towards Dependable Retrieval-Augmented Generation Using Factual Confidence Prediction
Florian Geissler, Francesco Carella, Laura Fieback +1
Incorporating specific knowledge into large language models via retrieval-augmented generation (RAG) is a widespread technique that fuels many of today's industry AI applications.…
Towards Automated Safety Requirements Derivation Using Agent-based RAG
Balahari Vignesh Balu, Florian Geissler, Francesco Carella +4
We study the automated derivation of safety requirements in a self-driving vehicle use case, leveraging LLMs in combination with agent-based retrieval-augmented generation. Convent…
BenchQC -- Scalable and modular benchmarking of industrial quantum computing applications
Florian Geissler, Eric Stopfer, Christian Ufrecht +19
We present BenchQC, a research project funded by the state of Bavaria, which promotes an application-centric perspective for benchmarking real-world quantum applications. Diverse u…
Concept-Guided LLM Agents for Human-AI Safety Codesign
Florian Geissler, Karsten Roscher, Mario Trapp
Generative AI is increasingly important in software engineering, including safety engineering, where its use ensures that software does not cause harm to people. This also leads to…
A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks
Florian Geissler, Syed Qutub, Michael Paulitsch +1
We present a highly compact run-time monitoring approach for deep computer vision networks that extracts selected knowledge from only a few (down to merely two) hidden layers, yet…
Large-Scale Application of Fault Injection into PyTorch Models -- an Extension to PyTorchFI for Validation Efficiency
Ralf Graafe, Qutub Syed Sha, Florian Geissler +1
Transient or permanent faults in hardware can render the output of Neural Networks (NN) incorrect without user-specific traces of the error, i.e. silent data errors (SDE). On the o…
BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture
Syed Sha Qutub, Neslihan Kose, Rafael Rosales +6
This paper introduces the Budding Ensemble Architecture (BEA), a novel reduced ensemble architecture for anchor-based object detection models. Object detection models are crucial i…
Hardware faults that matter: Understanding and Estimating the safety impact of hardware faults on object detection DNNs
Syed Qutub, Florian Geissler, Yang Peng +4
Object detection neural network models need to perform reliably in highly dynamic and safety-critical environments like automated driving or robotics. Therefore, it is paramount to…
Cooperative RADAR Sensors for the Digital Test Field A9 (KoRA9): Algorithmic Recap and Lessons Learned
Sören Kohnert, Julian Stähler, Reinhard Stolle +1
Infrastructure sensing systems in combination with Infrastructure-to-Vehicle communication can be used to enhance sensor data obtained from the perspective of a vehicle, only. This…
Fault-Tolerant Perception for Automated Driving A Lightweight Monitoring Approach
Cornelius Buerkle, Florian Geissler, Michael Paulitsch +1
While the most visible part of the safety verification process of automated vehicles concerns the planning and control system, it is often overlooked that safety of the latter cruc…
Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision
Florian Geissler, Syed Qutub, Sayanta Roychowdhury +6
Convolutional neural networks (CNNs) have become an established part of numerous safety-critical computer vision applications, including human robot interactions and automated driv…
A Plausibility-based Fault Detection Method for High-level Fusion Perception Systems
Florian Geissler, Alex Unnervik, Michael Paulitsch
Trustworthy environment perception is the fundamental basis for the safe deployment of automated agents such as self-driving vehicles or intelligent robots. The problem remains tha…
Optimized sensor placement for dependable roadside infrastructures
Florian Geissler, Ralf Graefe
We present a multi-stage optimization method for efficient sensor deployment in traffic surveillance scenarios. Based on a genetic optimization scheme, our algorithm places an opti…
Designing a Roadside Sensor Infrastructure to Support Automated Driving
Florian Geissler, Sören Kohnert, Reinhard Stolle
Automation of complex traffic scenarios is expected to rely on input from a roadside infrastructure to complement the vehicles' environment perception. We here explore design requi…
A Roadmap Towards Resilient Internet of Things for Cyber-Physical Systems
Denise Ratasich, Faiq Khalid, Florian Geissler +3
The Internet of Things (IoT) is a ubiquitous system connecting many different devices - the things - which can be accessed from the distance. The cyber-physical systems (CPS) monit…