MEET: A Method for Embeddings Evaluation for Taxonomic Data. - Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani (ICDM (Workshops), 2020)

A Method for Taxonomy-Aware Embeddings Evaluation (Student Abstract). - Navid Nobani; Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica (AAAI, 2021)

GRASP: Graph-based Mining of Scientific Papers. - Navid Nobani; Mauro Pelucchi; Matteo Perico; Andrea Scrivanti; Alessandro Vaccarino (DATA, 2021)

Towards an Explainer-agnostic Conversational XAI. - Navid Nobani; Fabio Mercorio; Mario Mezzanzanica (IJCAI, 2021)

TaxoRef: Embeddings Evaluation for AI-driven Taxonomy Refinement. - Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani (ECML/PKDD (3), 2021)

MEET-LM: A method for embeddings evaluation for taxonomic data in the labour market. - Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani (Comput. Ind., 2021)

The Good, the Bad, and the Explainer: A Tool for Contrastive Explanations of Text Classifiers. - Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani; Andrea Seveso (IJCAI, 2022)

Embeddings Evaluation Using a Novel Measure of Semantic Similarity. - Anna Giabelli; Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani (Cogn. Comput., 2022)

ContrXT: Generating contrastive explanations from any text classifier. - Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani; Andrea Seveso (Inf. Fusion, 2022)

A survey on XAI and natural language explanations. - Erik Cambria; Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani (Inf. Process. Manag., 2023)

ConvXAI: a System for Multimodal Interaction with Any Black-box Explainer. - Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Navid Nobani (Cogn. Comput., 2023)

An approach to Evaluative AI through Large Language Models. - Andrea Ermellino; Lorenzo Malandri; Fabio Mercorio; Navid Nobani; Antonio Serino (MAI-XAI@ECAI, 2024)

XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Models. - Erik Cambria; Lorenzo Malandri; Fabio Mercorio; Navid Nobani; Andrea Seveso (CoRR, 2024)

eXplainable AI for Word Embeddings: A Survey. - Roberto Boselli; Simone D'Amico; Navid Nobani (Cogn. Comput., 2025)