1 citations · 2 across the 17 of their papers we have counts for
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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…
Automated Testing of LLM-Based Post Hoc Explainers Using Model Checking as an Oracle
Dennis Gross, Helge Spieker
Large language models (LLMs) are used as post hoc explainers of sequential decision-making policies, producing natural-language explanations of why an action was chosen. However, L…
Gimitest: A Comprehensive Tool for Testing Reinforcement Learning Policies
Dennis Gross, Quentin Mazouni, Helge Spieker +1
Reinforcement learning (RL) policies can be unsafe and vulnerable to attacks. Ensuring their reliability is often a pain point as existing automated testing methods target only sel…
COOL-MC: Verifying and Explaining RL Policies for Multi-bridge Network Maintenance
Dennis Gross
Aging bridge networks require proactive, verifiable, and interpretable maintenance strategies, yet reinforcement learning (RL) policies trained solely on reward signals provide no…
COOL-MC: Verifying and Explaining RL Policies for Platelet Inventory Management
Dennis Gross
Platelets expire within five days. Blood banks face uncertain daily demand and must balance ordering decisions between costly wastage from overstocking and life-threatening shortag…
Semi-supervised CAPP Transformer Learning via Pseudo-labeling
Dennis Gross, Helge Spieker, Arnaud Gotlieb +3
High-level Computer-Aided Process Planning (CAPP) generates manufacturing process plans from part specifications. It suffers from limited dataset availability in industry, reducing…