This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks. - Adrian Hoffmann; Claudio Fanconi; Rahul Rade; Jonas Kohler (CoRR, 2021)

Natural Language Processing Methods to Identify Oncology Patients at High Risk for Acute Care with Clinical Notes. - Claudio Fanconi; Marieke M. van Buchem; Tina Hernandez-Boussard (CoRR, 2022)

This Reads Like That: Deep Learning for Interpretable Natural Language Processing. - Claudio Fanconi; Moritz Vandenhirtz; Severin Husmann; Julia E. Vogt (EMNLP, 2023)

Predicting Depression Risk in Patients with Cancer Using Multimodal Data. - Anne De Hond; Marieke M. van Buchem; Claudio Fanconi; Mohana Roy; Douglas W. Blayney; Ilse M. J. Kant; Ewout W. Steyerberg; Tina Hernandez-Boussard (MIE, 2023)

Discovering Preference Optimization Algorithms with and for Large Language Models. - Chris Lu 001; Samuel Holt; Claudio Fanconi; Alex J. Chan; Jakob N. Foerster; Mihaela van der Schaar; Robert T. Lange (NeurIPS, 2024)

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes. - Katarzyna Kobalczyk; Claudio Fanconi; Hao Sun 017; Mihaela van der Schaar (CoRR, 2024)

Applying natural language processing to patient messages to identify depression concerns in cancer patients. - Marieke M. van Buchem; Anne A. H. de Hond; Claudio Fanconi; Vaibhavi B. Shah; Max Schüssler; Ilse M. J. Kant; Ewout W. Steyerberg; Tina Hernandez-Boussard (J. Am. Medical Informatics Assoc., 2024)

Towards a Cascaded LLM Framework for Cost-effective Human-AI Decision-Making. - Claudio Fanconi; Mihaela van der Schaar (CoRR, 2025)