:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Belmecheri, Nassim, Gotlieb, Arnaud, Lazaar, Nadjib, Spieker, Helge
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence
Online Access:	https://arxiv.org/abs/2403.16908
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations
by: Belmecheri, Nassim, et al.
Published: (2024)

Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks
by: Belmecheri, Nassim, et al.
Published: (2025)

Rashomon in the Streets: Explanation Ambiguity in Scene Understanding
by: Spieker, Helge, et al.
Published: (2025)

Evaluating Human Trajectory Prediction with Metamorphic Testing
by: Spieker, Helge, et al.
Published: (2024)

Metamorphic Testing of Multimodal Human Trajectory Prediction
by: Spieker, Helge, et al.
Published: (2025)

Optimizing Ethical Risk Reduction for Medical Intelligent Systems with Constraint Programming
by: Brayé, Clotilde, et al.
Published: (2025)

Verifying Memoryless Sequential Decision-making of Large Language Models
by: Gross, Dennis, et al.
Published: (2025)

Bounded PCTL Model Checking of Large Language Model Outputs
by: Gross, Dennis, et al.
Published: (2025)

Enhancing Manufacturing Quality Prediction Models through the Integration of Explainability Methods
by: Gross, Dennis, et al.
Published: (2024)

Prompting for Performance: Exploring LLMs for Configuring Software
by: Spieker, Helge, et al.
Published: (2025)

Semi-supervised CAPP Transformer Learning via Pseudo-labeling
by: Gross, Dennis, et al.
Published: (2026)

Constraint-Guided Test Execution Scheduling: An Experience Report at ABB Robotics
by: Gotlieb, Arnaud, et al.
Published: (2023)

Probabilistic Model Checking of Stochastic Reinforcement Learning Policies
by: Gross, Dennis, et al.
Published: (2024)

Co-Activation Graph Analysis of Safety-Verified and Explainable Deep Reinforcement Learning Policies
by: Gross, Dennis, et al.
Published: (2025)

Testing for Fault Diversity in Reinforcement Learning
by: Mazouni, Quentin, et al.
Published: (2024)

Policy Testing with MDPFuzz (Replicability Study)
by: Mazouni, Quentin, et al.
Published: (2025)

Efficiently Ranking Software Variants with Minimal Benchmarks
by: Matricon, Théo, et al.
Published: (2025)

Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanations
by: Palacio, David N., et al.
Published: (2024)

Translating the Rashomon Effect to Sequential Decision-Making Tasks
by: Gross, Dennis, et al.
Published: (2025)

Efficient Milling Quality Prediction with Explainable Machine Learning
by: Gross, Dennis, et al.
Published: (2024)

Mutation‐Guided Metamorphic Testing of Optimality in AI Planning
by: Quentin Mazouni, et al.
Published: (2024)

On Trustworthy Rule-Based Models and Explanations
by: Siala, Mohamed, et al.
Published: (2025)

Towards Understanding the Influence of Training Samples on Explanations
by: Artelt, André, et al.
Published: (2024)

Toward Automated and Trustworthy Scientific Analysis and Visualization with LLM-Generated Code
by: Chakroborti, Apu Kumar, et al.
Published: (2025)

PONTE: Personalized Orchestration for Natural Language Trustworthy Explanations
by: Vineis, Vittoria, et al.
Published: (2026)

Faithful and Stable Neuron Explanations for Trustworthy Mechanistic Interpretability
by: Yan, Ge, et al.
Published: (2025)

Towards Trustworthy Legal AI through LLM Agents and Formal Reasoning
by: Chen, Linze, et al.
Published: (2025)

Microeconomic Foundations of Multi-Agent Learning
by: Helou, Nassim
Published: (2026)

Exploration of the Rashomon Set Assists Trustworthy Explanations for Medical Data
by: Kobylińska, Katarzyna, et al.
Published: (2023)

Understanding LLM Scientific Reasoning through Promptings and Model's Explanation on the Answers
by: Rueda, Alice, et al.
Published: (2025)

Driving with Regulation: Trustworthy and Interpretable Decision-Making for Autonomous Driving with Retrieval-Augmented Reasoning
by: Cai, Tianhui, et al.
Published: (2024)

Regularizing Explanations in Bayesian Convolutional Neural Networks
by: Bekkemoen, Yanzhe, et al.
Published: (2021)

Towards Holistic Surgical Scene Understanding
by: Valderrama, Natalia, et al.
Published: (2022)

Tuning for Trustworthiness -- Balancing Performance and Explanation Consistency in Neural Network Optimization
by: Hinterleitner, Alexander, et al.
Published: (2025)

Simulator Ensembles for Trustworthy Autonomous Driving Testing
by: Sorokin, Lev, et al.
Published: (2025)

Forms of Understanding for XAI-Explanations
by: Buschmeier, Hendrik, et al.
Published: (2023)

Towards Verified and Targeted Explanations through Formal Methods
by: Wang, Hanchen David, et al.
Published: (2026)

Context-Aware Autoencoders for Anomaly Detection in Maritime Surveillance
by: Acharya, Divya, et al.
Published: (2026)

Automated Explanation Selection for Scientific Discovery
by: Iser, Ashlin
Published: (2024)

Function Words as Statistical Cues for Language Learning
by: Yang, Xiulin, et al.
Published: (2026)