activity
20232026
most citedDetecting Intentional AIS Shutdown in Open Sea Maritime Surveillance Using Self-Supervised Deep Learning

38 citations · 56 across the 20 of their papers we have counts for

collaborators
Showing cs.SEShow all

8 papers · 1 filter

cs.SE2026

Probabilistic Model Checking of Autoregressive Neural Sequence Models

Helge Spieker, Dennis Gross, Arnaud Gotlieb

Test-set accuracy is silent on two issues that matter when deploying autoregressive neural sequence models: how much probability mass the system under test (SUT) places on constrai…

cs.SE2026

Metamorphic Testing with the Rashomon Set: Explanation Faithfulness in Machine Learning

Helge Spieker, Jørn Eirik Betten, Arnaud Gotlieb

Multiple machine learning models can achieve near-equivalent predictive performance on the same task, yet provide divergent feature-based explanations. This is called the Rashomon…

cs.SE2025

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…

cs.SE2025★ 2 cited

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…

cs.SE2025★ 1 cited

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,…

cs.SE2025★ 3 cited

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…

cs.SE2024★ 3 cited

Evaluating Human Trajectory Prediction with Metamorphic Testing

Helge Spieker, Nassim Belmecheri, Arnaud Gotlieb +1

The prediction of human trajectories is important for planning in autonomous systems that act in the real world, e.g. automated driving or mobile robots. Human trajectory predictio…

cs.SE2024★ 7 cited

Testing for Fault Diversity in Reinforcement Learning

Quentin Mazouni, Helge Spieker, Arnaud Gotlieb +1

Reinforcement Learning is the premier technique to approach sequential decision problems, including complex tasks such as driving cars and landing spacecraft. Among the software va…