38 citations · 56 across the 20 of their papers we have counts for
9 papers · 1 filter
Optimizing Ethical Risk Reduction for Medical Intelligent Systems with Constraint Programming
Clotilde Brayé, Aurélien Bricout, Arnaud Gotlieb +2
Medical Intelligent Systems (MIS) are increasingly integrated into healthcare workflows, offering significant benefits but also raising critical safety and ethical concerns. Accord…
Verifying Memoryless Sequential Decision-making of Large Language Models
Dennis Gross, Helge Spieker, Arnaud Gotlieb
We introduce a tool for rigorous and automated verification of large language model (LLM)- based policies in memoryless sequential decision-making tasks. Given a Markov decision pr…
Bounded PCTL Model Checking of Large Language Model Outputs
Dennis Gross, Helge Spieker, Arnaud Gotlieb
In this paper, we introduce LLMCHECKER, a model-checking-based verification method to verify the probabilistic computation tree logic (PCTL) properties of an LLM text generation pr…
Rashomon in the Streets: Explanation Ambiguity in Scene Understanding
Helge Spieker, Jørn Eirik Betten, Arnaud Gotlieb +2
Explainable AI (XAI) is essential for validating and trusting models in safety-critical applications like autonomous driving. However, the reliability of XAI is challenged by the R…
Efficiently Ranking Software Variants with Minimal Benchmarks
Théo Matricon, Mathieu Acher, Helge Spieker +1
Benchmarking is a common practice in software engineering to assess the qualities and performance of software variants, coming from multiple competing systems or from configuration…
Metamorphic Testing of Multimodal Human Trajectory Prediction
Helge Spieker, Nadjib Lazaar, Arnaud Gotlieb +1
Context: Predicting human trajectories is crucial for the safety and reliability of autonomous systems, such as automated vehicles and mobile robots. However, rigorously testing th…
Prompting for Performance: Exploring LLMs for Configuring Software
Helge Spieker, Théo Matricon, Nassim Belmecheri +7
Software systems usually provide numerous configuration options that can affect performance metrics such as execution time, memory usage, binary size, or bitrate. On the one hand,…
Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
This paper investigates the integration of graph neural networks (GNNs) with Qualitative Explainable Graphs (QXGs) for scene understanding in automated driving. Scene understanding…
Policy Testing with MDPFuzz (Replicability Study)
Quentin Mazouni, Helge Spieker, Arnaud Gotlieb +1
In recent years, following tremendous achievements in Reinforcement Learning, a great deal of interest has been devoted to ML models for sequential decision-making. Together with t…