Navid Nobani

According to our database, Navid Nobani authored at least 18 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Categorical variable encoding methods for tabular data: a benchmarking study.

Federico Clerici, Navid Nobani

Int. J. Data Sci. Anal., December, 2026

Synthetic data generation: A tertiary study.

Navid Nobani, Giovanni Officioso, Filippo Pallucchini, Giancarlo Sperlì, Fabio Mercorio

Inf. Process. Manag., 2026

Learning across modalities: a systematic survey of multimodal models for financial analysis.

Simone D'Amico, Fabio Mercorio, Navid Nobani, Giancarlo Sperlì, Carmine Ventre

Inf. Fusion, 2026

SkiLLens: Recognising and Mapping Novel Skills from Millions of Job Ads Across Europe Using Language Models.

Alessia De Santo, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

2025

eXplainable AI for Word Embeddings: A Survey.

Roberto Boselli, Simone D'Amico, Navid Nobani

Cogn. Comput., February, 2025

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

An approach to Evaluative AI through Large Language Models.

Andrea Ermellino, Lorenzo Malandri, Fabio Mercorio, Navid Nobani, Antonio Serino

MAI-XAI@ECAI, 2024

2023

ConvXAI: a System for Multimodal Interaction with Any Black-box Explainer.

Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani

Cogn. Comput., March, 2023

A survey on XAI and natural language explanations.

Erik Cambria, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani

Inf. Process. Manag., 2023

2022

ContrXT: Generating contrastive explanations from any text classifier.

Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani, Andrea Seveso

Inf. Fusion, 2022

Embeddings Evaluation Using a Novel Measure of Semantic Similarity.

Anna Giabelli, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani

Cogn. Comput., 2022

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

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

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

TaxoRef: Embeddings Evaluation for AI-driven Taxonomy Refinement.

Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Towards an Explainer-agnostic Conversational XAI.

Navid Nobani, Fabio Mercorio, Mario Mezzanzanica

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

GRASP: Graph-based Mining of Scientific Papers.

Navid Nobani, Mauro Pelucchi, Matteo Perico, Andrea Scrivanti, Alessandro Vaccarino

Proceedings of the 10th International Conference on Data Science, 2021

A Method for Taxonomy-Aware Embeddings Evaluation (Student Abstract).

Navid Nobani, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

MEET: A Method for Embeddings Evaluation for Taxonomic Data.

Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani

Proceedings of the 20th International Conference on Data Mining Workshops, 2020