Andrea Seveso

According to our database, Andrea Seveso authored at least 18 papers between 2019 and 2024.

Collaborative distances:

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

2024

Explainable AI for Text Classification: Lessons from a Comprehensive Evaluation of Post Hoc Methods.

Mirko Cesarini, Lorenzo Malandri, Filippo Pallucchini, Andrea Seveso, Frank Xing

Cogn. Comput., November, 2024

Model-contrastive explanations through symbolic reasoning.

Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso

Decis. Support Syst., January, 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

Disce aut Deficere: Evaluating LLMs Proficiency on the INVALSI Italian Benchmark.

Fabio Mercorio, Mario Mezzanzanica, Daniele Potertì, Antonio Serino, Andrea Seveso

CoRR, 2024

Augmenting XAI with LLMs: A Case Study in Banking Marketing Recommendation.

Alessandro Castelnovo, Roberto Depalmas, Fabio Mercorio, Nicolò Mombelli, Daniele Potertì, Antonio Serino, Andrea Seveso, Salvatore Sorrentino, Laura Viola

Proceedings of the Explainable Artificial Intelligence, 2024

2023

Leveraging Group Contrastive Explanations for Handling Fairness.

Alessandro Castelnovo, Nicole Inverardi, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso

Proceedings of the Explainable Artificial Intelligence, 2023

2022

ContrXT: Generating contrastive explanations from any text classifier.

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

Inf. Fusion, 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

Skills2Job: A recommender system that encodes job offer embeddings on graph databases.

Anna Giabelli, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso

Appl. Soft Comput., 2021

A Human-AI Teaming Approach for Incremental Taxonomy Learning from Text.

Andrea Seveso, Fabio Mercorio, Mario Mezzanzanica

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

Skills2Graph: Processing million Job Ads to face the Job Skill Mismatch Problem.

Anna Giabelli, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso

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

Skills2Job: A Recommender System that Encodes Job Offer Embeddings on Graph Databases (Student Abstract).

Andrea Seveso, Anna Giabelli, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica

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

NEO: A System for Identifying New Emerging Occupation from Job Ads.

Anna Giabelli, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso

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

2020

Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings.

Andrea Seveso, Andrea Campagner, Davide Ciucci, Federico Cabitza

BMC Medical Informatics Decis. Mak., 2020

NEO: A Tool for Taxonomy Enrichment with New Emerging Occupations.

Anna Giabelli, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso

Proceedings of the Semantic Web - ISWC 2020, 2020

eXDiL: A Tool for Classifying and eXplaining Hospital Discharge Letters.

Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso

Proceedings of the Machine Learning and Knowledge Extraction, 2020

Developing a Machine Learning Model for Predicting Postnatal Growth in Very Low Birth Weight Infants.

Andrea Seveso, Valentina Bozzetti, Paolo Tagliabue, Maria Luisa Ventura, Federico Cabitza

Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020), 2020

2019

Programmed Inefficiencies in DSS-Supported Human Decision Making.

Federico Cabitza, Andrea Campagner, Davide Ciucci, Andrea Seveso

Proceedings of the Modeling Decisions for Artificial Intelligence, 2019