It takes two to tango: a synergistic approach to human-machine decision making

Informazioni relative al progetto

TANGO

ID dell’accordo di sovvenzione: 101120763

DOI

10.3030/101120763

Data della firma CE 30 Giugno 2023

Data di avvio 1 Ottobre 2023

Data di completamento 30 Settembre 2027

Finanziato da

• Digital, Industry and Space

Costo totale

€ 7 008 798,75

Contributo UE

€ 7 008 798,75

Coordinato da

UNIVERSITA DEGLI STUDI DI TRENTO
Italy

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Websites, patent fillings, videos etc. (1)

Brand and comm. channels

Brand and communications channelsestablished and live.

Data Management Plan (2)

First data management plan

(First) Ethical, Gender, Legal, Security Compliance Framework for the data management lifecycle.

Second data management plan

(Second) Ethical, Gender, Legal, Security Compliance Framework for the data management lifecycle

Documents, reports (6)

Cognition-aware explanations for HML

Definition, design and development ofcognitive-aware explanations.

First exploitation strategy

First exploitation strategy and roadmap to market

Cognition-aware explanations for DM

Definition, design and development of theunified explanation-driven HDM process

First communication and dissemination report

Periodic report on C&D activities

Application guidelines

Document with guidelines for theimplementation and coordination of theapplications.

TANGO system specifications

Architectural specifications of the TANGObackend system.

Pubblicazioni

Conference proceedings (27)

Towards Logically Consistent Language Models via Probabilistic Reasoning

Autori: Calanzone, Diego; Teso, Stefano; Vergari, Antonio
Pubblicato in: 2024
Editore: ICLR 2024 Workshop on Reliable and Responsible Foundation Models
DOI: 10.48550/ARXIV.2404.12843

A Simple and Expressive Graph Neural Network Based Method for Structural Link Representation

Autori: Veronica Lachi, Francesco Ferrini, Antonio Longa, Bruno Lepri, Andrea Passerini
Pubblicato in: Proceedings of the GRaM Workshop at ICML 2024, 2024
Editore: PMLR

Uncertainty Matters: Stable Conclusions Under Unstable Assessment of Fairness Results

Autori: Ainhize Barrainkua, Paula Gordaliza, Jose A Lozano, Novi Quadrianto
Pubblicato in: Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS) 2024, Valencia, Spain. PMLR., 2024
Editore: Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS) 2024, Valencia, Spain. PMLR: Volume 238.

Ensemble Counterfactual Explanations forChurn Analysis

Autori: Samuele Tonati, Marzio Di Vece, Roberto Pellungrini, Fosca Giannotti
Pubblicato in: Lecture Notes in Computer Science, Discovery Science, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78980-9_21

Ensemble Counterfactual Explanations for Churn Analysis

Autori: Samuele Tonati, Marzio Di Vece, Roberto Pellungrini, Fosca Giannotti
Pubblicato in: Lecture Notes in Computer Science, Discovery Science, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78980-9_21

Preference Elicitation in Interactive and User-centered Algorithmic Recourse: an Initial Exploration

Autori: Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini, Katya Tentori, Massimo Zancanaro
Pubblicato in: Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, 2024
Editore: ACM
DOI: 10.1145/3627043.3659556

PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning

Autori: Luca Corbucci, Mikko A. Heikkilä, David Solans Noguero, Anna Monreale, Nicolas Kourtellis
Pubblicato in: Frontiers in Artificial Intelligence and Applications, ECAI 2024, 2024
Editore: IOS Press
DOI: 10.3233/FAIA240671

Sheaf Diffusion Goes Nonlinear: Enhancing GNNs with Adaptive Sheaf Laplacians

Autori: Olga Zaghen, Antonio Longa, Steve Azzolin, Lev Telyatnikov, Andrea Passerini, Pietro Lio
Pubblicato in: Proceedings of the GRaM Workshop at ICML 2024, 2024
Editore: PMLR

Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph

Autori: Marco Bronzini, Carlo Nicolini, Bruno Lepri, Jacopo Staiano, Andrea Passerini
Pubblicato in: Proceedings of COLM, 2024, 2024
Editore: openreview.net

Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs

Autori: Steve Azzolin, Antonio Longa, Stefano Teso, Andrea Passerini
Pubblicato in: Proceedings of ICLR, 2025
Editore: OpenReview

BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts

Autori: Marconato, Emanuele; Bortolotti, Samuele; van Krieken, Emile; Vergari, Antonio; Passerini, Andrea; Teso, Stefano
Pubblicato in: Proceedings of UAI, 2024
Editore: Proceedings of UAI, 2024

Epistemic Interaction – Tuning Interfaces to Provide Information for AI Support

Autori: Alan Dix, Ben Wilson Matt Roach, Tommaso Turchi, Alessio Malizia
Pubblicato in: SYNERGY 2024 – Designing and Building Hybrid Human-AI Systems 2024, 2024
Editore: SYNERGY 2024 – Designing and Building Hybrid Human-AI Systems 2024

One-Shot Clustering for Federated Learning

Autori: Maciej Krzysztof Zuziak, Roberto Pellungrini, Salvatore Rinzivillo
Pubblicato in: 2024 IEEE International Conference on Big Data (BigData), 2025
Editore: IEEE
DOI: 10.48550/arXiv.2503.04231

One-Shot Clustering for Federated Learning

Autori: Maciej Krzysztof Zuziak, Roberto Pellungrini, Salvatore Rinzivillo
Pubblicato in: 2024 IEEE International Conference on Big Data (BigData), 2025
Editore: IEEE
DOI: 10.1109/BIGDATA62323.2024.10825763

Designing for situated AI-human decision making: Lessons learned from a primary care deployment

Autori: Ben Wilson, Darren Scott, Matt Roach, Emily Nielsen, Berndt Muller
Pubblicato in: SYNERGY 2024 – Designing and Building Hybrid Human-AI Systems 2024, 2024
Editore: SYNERGY 2024 – Designing and Building Hybrid Human-AI Systems 2024

Interpretable and Fair Mechanisms for Abstaining Classifiers

Autori: Daphne Lenders, Andrea Pugnana, Roberto Pellungrini, Toon Calders, Dino Pedreschi, Fosca Giannotti
Pubblicato in: Lecture Notes in Computer Science, Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-70368-3_25

Enhancing Privacy and Utility in Federated Learning: A Hybrid P2P and Server-Based Approach with Differential Privacy Protection

Autori: Luca Corbucci, Anna Monreale, Roberto Pellungrini
Pubblicato in: Proceedings of the 21st International Conference on Security and Cryptography, 2024
Editore: SCITEPRESS - Science and Technology Publications
DOI: 10.5220/0012863600003767

Logically Consistent Language Models via Neuro-Symbolic Integration

Autori: Diego Calanzone, Stefano Teso, Antonio Vergari
Pubblicato in: International Conference on Learning Representations (ICLR), 2025

Disagreement-based Active Learning for Robustness Against Subpopulation Shifts

Autori: Yeat Jeng Ng, Viktoriia Sharmanska, Thomas Kehrenberg, Anastasia Pentina, Novi Quadrianto
Pubblicato in: Proceedings of the HLDM Workshop at ECML 2024, 2024
Editore: Proceedings of the HLDM Workshop @ ECML 2024

GLOR-FLEX: Local to Global Rule-Based EXplanations for Federated Learning

Autori: Rami Haffar, Francesca Naretto, David Snchez, Anna Monreale, Josep Domingo-Ferrer
Pubblicato in: 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2024
Editore: IEEE
DOI: 10.1109/FUZZ-IEEE60900.2024.10611878

A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts

Autori: Bortolotti, Samuele; Marconato, Emanuele; Carraro, Tommaso; Morettin, Paolo; van Krieken, Emile; Vergari, Antonio; Teso, Stefano; Passerini, Andrea
Pubblicato in: Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 2024
Editore: Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain

Autori: Burcu Sayin, Pasquale Minervini, Jacopo Staiano, Andrea Passerini
Pubblicato in: Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2024.clinicalnlp-1.19

Coordination in dynamic interactions by converging on tacitly agreed joint plans

Autori: Arthur Le Pargneux, Hossam Zeitoun, Emmanouil Konstantinidis, Nick Chater
Pubblicato in: 2024
Editore: Center for Open Science
DOI: 10.31234/osf.io/w2x3f

Interpretable andFair Mechanisms forAbstaining Classifiers

Autori: Daphne Lenders, Andrea Pugnana, Roberto Pellungrini, Toon Calders, Dino Pedreschi, Fosca Giannotti
Pubblicato in: Lecture Notes in Computer Science, Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
Editore: Springer Nature Switzerland
DOI: 10.48550/arXiv.2503.18826

A Frank System for Co-Evolutionary Hybrid Decision-Making

Autori: Federico Mazzoni, Riccardo Guidotti, Alessio Malizia
Pubblicato in: Lecture Notes in Computer Science, Advances in Intelligent Data Analysis XXII, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-58553-1_19

PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning

Autori: Luca Corbucci, Mikko A. Heikkil, David Solans Noguero, Anna Monreale, Nicolas Kourtellis
Pubblicato in: Frontiers in Artificial Intelligence and Applications, ECAI 2024, 2024
Editore: IOS Press
DOI: 10.3233/FAIA240671

Explainable AI in Time-Sensitive Scenarios: Prefetched Offline Explanation Model

Autori: Fabio Michele Russo, Carlo Metta, Anna Monreale, Salvatore Rinzivillo, Fabio Pinelli
Pubblicato in: Lecture Notes in Computer Science, Discovery Science, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78980-9_11

Peer reviewed articles (14)

Explaining the Explainers in Graph Neural Networks: a Comparative Study

Autori: Antonio Longa, Steve Azzolin, Gabriele Santin, Giulia Cencetti, Pietro Lio, Bruno Lepri, Andrea Passerini
Pubblicato in: ACM Computing Surveys, 2024, ISSN 0360-0300
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3696444

CERN for AI: a theoretical framework for autonomous simulation-based artificial intelligence testing and alignment

Autori: Ljubiša Bojić; Matteo Cinelli; Dubravko Ćulibrk; Boris Delibašić
Pubblicato in: European Journal of Futures Research, 2024, ISSN 2195-2248
Editore: European Journal of Futures Research
DOI: 10.48550/ARXIV.2312.09402

Futures

Autori: Bojic, Ljubisa
Pubblicato in: Futures, 2024, ISSN 0016-3287
Editore: Elsevier
DOI: 10.1016/J.FUTURES.2024.103383

Fostering effective hybrid human-LLM reasoning and decision making

Autori: Passerini, Andrea; Gema, Aryo; Minervini, Pasquale; Sayin, Burcu; Tentori, Katya
Pubblicato in: FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2025, ISSN 2624-8212
Editore: Frontiers Media SA
DOI: 10.3389/frai.2024.1464690

NeST: The neuro-symbolic transpiler

Autori: Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
Pubblicato in: International Journal of Approximate Reasoning, Numero 179, 2025, ISSN 0888-613X
Editore: Elsevier BV
DOI: 10.1016/J.IJAR.2025.109369

AI alignment: Assessing the global impact of recommender systems

Autori: Ljubisa Bojic
Pubblicato in: Futures, Numero 160, 2024, ISSN 0016-3287
Editore: Elsevier BV
DOI: 10.1016/J.FUTURES.2024.103383

Conversational technology and reactions to withheld information

Autori: Nikolos Gurney, George Loewenstein, Nick Chater
Pubblicato in: PLOS ONE, Numero 19, 2024, ISSN 1932-6203
Editore: Public Library of Science (PLoS)
DOI: 10.1371/journal.pone.0301382

Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields

Autori: Francesco Spinnato, Riccardo Guidotti, Anna Monreale, Mirco Nanni
Pubblicato in: IEEE Access, Numero 12, 2024, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/ACCESS.2024.3464743

Resource-rational contractualism: A triple theory of moral cognition

Autori: Sydney Levine, Nick Chater, Joshua B. Tenenbaum, Fiery Cushman
Pubblicato in: Behavioral and Brain Sciences, 2024, ISSN 0140-525X
Editore: Cambridge University Press (CUP)
DOI: 10.1017/S0140525X24001067

When rules are over-ruled: Virtual bargaining as a contractualist method of moral judgment

Autori: Sydney Levine, Max Kleiman-Weiner, Nick Chater, Fiery Cushman, Joshua B. Tenenbaum
Pubblicato in: Cognition, Numero 250, 2024, ISSN 0010-0277
Editore: Elsevier BV
DOI: 10.1016/J.COGNITION.2024.105790

Rethinking and Recomputing the Value of Machine Learning Models

Autori: Burcu Sayin; Jie Yang; Xinyue Chen; Andrea Passerini; Fabio Casati
Pubblicato in: Crossref, 2024, ISSN 1573-7462
Editore: Artificial Intelligence Review
DOI: 10.21203/RS.3.RS-4833578/V1

Generative Model for Decision Trees

Autori: Riccardo Guidotti; Anna Monreale; Mattia Setzu; Giulia Volpi
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, 2024, ISSN 2374-3468
Editore: Proceedings of the AAAI Conference on Artificial Intelligence
DOI: 10.1609/AAAI.V38I19.30104

Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields

Autori: Francesco Spinnato, Riccardo Guidotti, Anna Monreale, Mirco Nanni
Pubblicato in: IEEE Access, Numero 12, 2024, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/ACCESS.2024.3464743

Explainable AI for Time Series Classification: A Review, Taxonomy and Research Directions

Autori: Andreas Theissler, Francesco Spinnato, Udo Schlegel, Riccardo Guidotti
Pubblicato in: IEEE Access, Numero 10, 2022, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/ACCESS.2022.3207765

Monographic books (1)

Beyond the Face: Biometrics and Society

Autori: Bojan, Perkov; Jelena, Adamović; Duje, Kozomara; Mila, Bajić; Duje, Prkut
Pubblicato in: 2023
Editore: SHARE Foundation
DOI: 10.5281/ZENODO.13819768