Generative Image Inpainting for Retinal Images using Generative Adversarial Networks. - Lucie Charlotte Magister; Ognjen Arandjelovic (EMBC, 2021)

GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks. - Lucie Charlotte Magister; Dmitry Kazhdan; Vikash Singh; Pietro Liò (CoRR, 2021)

Encoding Concepts in Graph Neural Networks. - Lucie Charlotte Magister; Pietro Barbiero; Dmitry Kazhdan; Federico Siciliano; Gabriele Ciravegna; Fabrizio Silvestri; Pietro Liò; Mateja Jamnik (CoRR, 2022)

Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis. - Han Xuanyuan; Pietro Barbiero; Dobrik Georgiev; Lucie Charlotte Magister; Pietro Liò (AAAI, 2023)

Teaching Small Language Models to Reason. - Lucie Charlotte Magister; Jonathan Mallinson; Jakub Adámek; Eric Malmi; Aliaksei Severyn (ACL (2), 2023)

Interpretable Neural-Symbolic Concept Reasoning. - Pietro Barbiero; Gabriele Ciravegna; Francesco Giannini; Mateo Espinosa Zarlenga; Lucie Charlotte Magister; Alberto Tonda; Pietro Liò; Frédéric Precioso; Mateja Jamnik; Giuseppe Marra (NeSy, 2023)

Interpretable Graph Networks Formulate Universal Algebra Conjectures. - Francesco Giannini; Stefano Fioravanti; Oguzhan Keskin; Alisia Maria Lupidi; Lucie Charlotte Magister; Pietro Lió; Pietro Barbiero (NeurIPS, 2023)

Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach. - Oguzhan Keskin; Alisia Maria Lupidi; Stefano Fioravanti; Lucie Charlotte Magister; Pietro Barbiero; Pietro Lio; Francesco Giannini (TAG-ML, 2023)

Concept Distillation in Graph Neural Networks. - Lucie Charlotte Magister; Pietro Barbiero; Dmitry Kazhdan; Federico Siciliano; Gabriele Ciravegna; Fabrizio Silvestri; Mateja Jamnik; Pietro Liò (xAI (3), 2023)

GCI: A (G)raph (C)oncept (I)nterpretation Framework. - Dmitry Kazhdan; Botty Dimanov; Lucie Charlotte Magister; Pietro Barbiero; Mateja Jamnik; Pietro Liò (CoRR, 2023)

Deep Multiple Instance Learning with Distance-Aware Self-Attention. - Georg Wölflein; Lucie Charlotte Magister; Pietro Liò; David J. Harrison; Ognjen Arandjelovic (CoRR, 2023)

SHARCS: Shared Concept Space for Explainable Multimodal Learning. - Gabriele Dominici; Pietro Barbiero; Lucie Charlotte Magister; Pietro Liò; Nikola Simidjievski (CoRR, 2023)

Everybody Needs a Little HELP: Explaining Graphs via Hierarchical Concepts. - Jonas Jürß; Lucie Charlotte Magister; Pietro Barbiero; Pietro Liò; Nikola Simidjievski (CoRR, 2023)

Digital Histopathology with Graph Neural Networks: Concepts and Explanations for Clinicians. - Alessandro Farace di Villaforesta; Lucie Charlotte Magister; Pietro Barbiero; Pietro Liò (CoRR, 2023)

Explaining Hypergraph Neural Networks: From Local Explanations to Global Concepts. - Shiye Su; Iulia Duta; Lucie Charlotte Magister; Pietro Liò (CoRR, 2024)

On the Way to LLM Personalization: Learning to Remember User Conversations. - Lucie Charlotte Magister; Katherine Metcalf; Yizhe Zhang; Maartje ter Hoeve (CoRR, 2024)

Multimodal Attention-Aware Fusion for Diagnosing Distal Myopathy: Evaluating Model Interpretability and Clinician Trust. - Mohsen Abbaspour Onari; Lucie Charlotte Magister; Yaoxin Wu; Amalia Lupi; Dario Creazzo; Mattia Tordin; Luigi Di Donatantonio; Emilio Quaia; Chao Zhang 071; Isel Grau; Marco S. Nobile; Yingqian Zhang 001; et al. (CoRR, 2025)