Teaching the Machine to Explain Itself using Domain Knowledge. - Vladimir Balayan; Pedro Saleiro; Catarina G. Belém; Ludwig Krippahl; Pedro Bizarro (CoRR, 2020)

How can I choose an explainer?: An Application-grounded Evaluation of Post-hoc Explanations. - Sérgio M. Jesus; Catarina G. Belém; Vladimir Balayan; João Bento 002; Pedro Saleiro; Pedro Bizarro; João Gama 001 (FAccT, 2021)

Weakly Supervised Multi-task Learning for Concept-based Explainability. - Catarina G. Belém; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro (CoRR, 2021)

ConceptDistil: Model-Agnostic Distillation of Concept Explanations. - João Bento Sousa; Ricardo Moreira; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro (CoRR, 2022)

On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods. - Kasun Amarasinghe; Kit T. Rodolfa; Sérgio M. Jesus; Valerie Chen; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro; Ameet Talwalkar; Rayid Ghani (AAAI, 2024)