Publication

[1] Gabriele Masina, Giuseppe Spallitta, Roberto Sebastiani. On CNF Conversion for Disjoint SAT Enumeration. Proceedings of 26th International Conference on Theory and Applications of Satisfiability Testing -- SAT'23. July 2023.

[2] Giuseppe Spallitta, Gabriele Masina, Paolo Morettin, Andrea Passerini, Roberto Sebastiani. Enhancing SMT-based Weighted Model Integration by Structure Awareness. Accepted modulo major revisions at Artificial Intelligence Journal.

[3] Giuseppe Spallitta, Roberto Sebastiani, Armin Biere. Enumerating Disjoint Partial Models without Blocking Clauses. Under submission.

[4] Giuseppe Spallitta, Roberto Sebastiani, Armin Biere. Enumerating Disjoint Partial Models without Blocking Clauses.  Short version. Presented at Workshop on Counting and Sampling, SAT23. July 2023.

[5] Sibylle Möhle, Roberto Sebastiani, Armin Biere. On Enumerating Short Projected Models. 2023 Under journal submission.

[6] Paolo Morettin, Andrea Passerini, Roberto Sebastiani. A Unified Framework for Probabilistic Verification of AI Systems via Weighted Model Integration. 2023. Under submission.

[7] Paolo Morettin, Andrea Passerini, Roberto Sebastiani Towards a Unified Framework for Probabilistic Verification of AI Systems. Proc VeriLearn23, ECAI23 Workshop on Verifying Learning Systems.

[1] Alessandro Daniele, Tommaso Campari, Sagar Malhotra, Luciano Serafini: Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions. IJCAI 2023: 3597-3605 and NeSy 2023: 418-419

[2] Sagar Malhotra, Davide Bizzaro, Luciano Serafini: Lifted Inference beyond First-Order Logic. CoRR abs/2308.11738 (2023)

[3] Cancelli, E., Campari, T., Serafini, L., Chang, A. X., & Ballan, L. (2023). Exploiting Proximity-Aware Tasks for Embodied Social Navigation. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 10957-10967).

[4] Lamanna, L., Faridghasemnia, M., Gerevini, A., Saetti, A., Saffiotti, A., Serafini, L., & Traverso, P. (2023). Learning to Act for Perceiving in Partially Unknown Environments. In IJCAI 2023

[1] Wil M. P. van der Aalst, Riccardo De Masellis, Chiara Di Francescomarino, Chiara Ghidini, Humam Kourani: Discovering hybrid process models with bounds on time and complexity: When to be formal and when not? Information Systems. 116: 102214 (2023)

[2] Buliga, A., Di Francescomarino, C., Ghidini, C., and Maggi, F. M. (2023). Counter- factuals and ways to build them: Evaluating approaches in predictive process monitoring. In Advanced Information Systems Engineering - 35th International Conference, CAiSE 2023, Proceedings, volume 13901 of Lecture Notes in Computer Science, pages 558–574. Springer.

[3] Marco Roveri, Claudio Di Ciccio, Chiara Di Francescomarino, Chiara Ghidini: Computing unsatisfiable cores for LTLf specifications. CoRR abs/2203.04834 (2022) - under evaluation in a journal.

[4] Artale A., Geatti L., Gigante N., Mazzullo A., and Montanari A.: A singly exponential transformation of LTL[X, F] into pure past LTL, to appear in the Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning (KR2023)

[5] Artale A., Mazzullo A.: Non-Rigid Designators in Epistemic and Temporal Free Description Logics , submitted to the 36th International Workshop on Description Logics (DL2023) - under review.

[6] Branchi, S., Buliga, A., Di Francescomarino, C., Ghidini, C., Meneghello, F., and Ronzani M.,: Learning the optimal policy from temporal data: a white box approach. In preparation. 

[7] Buliga, A., Di Francescomarino, C., Ghidini, C., and Maggi, F. M.: Guiding the generation of counterfactuals explanations through temporal background knowledge for Predictive Process Monitoring. In preparation.

[8] Meneghello, F., Di Francescomarino, C., and Ghidini, C.: Runtime Integration of Machine Learning and Simulation for Business Processes. To appear in the Proceedings of the 5th International Conference on Process Mining (ICPM 2023)

[9] Meneghello, F., Di Francescomarino, C., and Ghidini, C.: RimsTool: a Hybrid Simulator for Business Processes. To appear in the Proceedings of the 5th International Conference on Process Mining (ICPM 2023). Demo Session.

[10] Giorgini, P., Mazzullo, A., Robol, M., and Roveri, M..Towards Large Language Model Architectures for Knowledge Acquisition and Strategy Synthesis. To appear in 5th OVERLAY Workshop. Nov. 2023.

[11] Kherrour, A., Robol, M., Roveri, M., Giorgini, P.. Evaluating Heuristic Search Algorithms in Pathfinding: A Comprehensive Study on Performance Metrics and Domain Parameters. To appear in the AREA 2023 Workshop held in conjunction with ECAI 2023.

[12] Zanetti, A., Dal Moro, D. , Vreto, R. Robol. M., Roveri, M., and Giorgini, P.. Implementing BDI Continual Temporal Planning for Robotic Agents. To appear in the 22nd IEEE/WIC International Conference. 2023.

[13] Artale, A., Geatti, L., Gigante, N. and Mazzullo, A.. A Landscape of First-Order Linear Temporal Logics in Infinite-State Verification and Temporal Ontologies. To appear in 5th OVERLAY Workshop. Nov. 2023.

[1] S. Felipe dos Santos, R. Berriel, T. Oliveira-Santos, N. Sebe, and J. Almeida, Budget-Aware Pruning for Multi-Domain Learning, International Conference on Image Analysis and Processing, September 2023

[2] Y. Song, J. Zhang, N. Sebe, and W. Wang, Householder Projector for Unsupervised Latent Semantics Discovery, International Conference of Computer Vision, October 2023

[3] Z. Xu, E. Sangineto, and N. Sebe, StylerDALLE: Language-Guided Style Transfer Using a Vector-Quantized Tokenizer of a Large-Scale Generative Model, International Conference of Computer Vision, October 2023

[4] F. Betti, J. Staiano, L. Baraldi, L. Baraldi, R. Cucchiara, and N. Sebe, Let's ViCE! Mimicking Human Cognitive Behavior in Image Generation Evaluation, ACM International Conference on Multimedia, October 2023

[5] E. Peruzzo, W. Menapace, V. Goel, F. Arrigoni, H. Tang, X. Xue, A. Chopikyan, N. Orlov, Y. Hu, H. Shi, N. Sebe, and E. Ricci, Interactive Neural Painting, Computer Vision and Image Understanding, vol. 235, article 103778, October 2023.

[6] G.Zara, S.Roy, P., Rota, and E. Ricci.  2023. AutoLabel: CLIP-based framework for Open-set Video Domain Adaptation. IEEE International Conference on Computer Vision, June 2023

[7] G. Zara, A., Conti, S., Roy, S.  Lathuilière, P., Rota, and E. Ricci, 2023. The Unreasonable Effectiveness of Large Language-Vision Models for Source-free Video Domain Adaptation.  International Conference of Computer Vision, October 2023

[8] C. Saltori, F., Galasso, G., Fiameni, N., Sebe, F.  Poiesi, and E. Ricci,. Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, online first 2023.

[1] Dennis Fucci, Marco Gaido, Mauro Cettolo, Matteo Negri, Luisa Bentivogli. “No pitch left behind: addressing gender unbalance in automatic speech recognition through pitch manipulation”. In Proceedings of ASRU 2023.

[2] Marco Gaido, Dennis Fucci, Matteo Negri, Luisa Bentivogli. “How To Build Competitive Multi-gender Speech Translation Models For Controlling Speaker Gender Translation”. In Proceedings of CLIC-it 2023.

[3] Beatrice Savoldi, Marco Gaido, Matteo Negri, Luisa Bentivogli. “Test Suites Task: Evaluation of Gender Fairness in MT with MuST-SHE and INES”. In Proceedings of WMT 2023.

[4] Andrea Zaninello, Sofia Brenna, Bernardo Magnini. Textual Entailment with Natural Language Explanations: The Italian e-RTE-3 Dataset, CliC-it 2023.

[5] Silvia Casola, Tiziano Labruna, Alberto Lavelli, Bernardo Magnini. Testing ChatGPT for Stability and Reasoning: A Case Study Using Italian Medical Specialization Tests,  CliC-it 2023,

[6] Tiziano Labruna, Sofia Brenna, Andrea Zaninello, Bernardo Magnini. Unraveling ChatGPT: A Critical Analysis of AI-Generated Goal-Oriented Dialogues and Annotations, AIxIA 2023.

[7] Roberto Zanoli, Alberto Lavelli, Daniel Verdi do Amarante, Daniele Toti. Assessment of the E3C corpus for the recognition of disorders in clinical texts, Journal Natural Language Engineering, 2023.

[8] Begoña Altuna, Goutham Karunakaran, Alberto Lavelli, Bernardo Magnini, Manuela Speranza, Roberto Zanoli. CLinkaRT at EVALITA 2023: Overview of the Task on Linking a Lab Result to its Test Event in the Clinical Domain. Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. CEUR 2023.

[9] Begoña Altuna, Rodrigo Agerri, Lidia Salas-Espejo, José Javier Saiz, Alberto Lavelli, Bernardo Magnini, Manuela Speranza, Roberto Zanoli, Goutham Karunakaran. Overview of TESTLINK at IberLEF 2023: Linking Results to Clinical Laboratory Tests and Measurements, Procesamiento del Lenguaje Natural, 2023.

[10] Sara Papi, Marco Gaido, Alina Karakanta, Mauro Cettolo, Matteo Negri and Marco Turchi. “Direct Speech Translation for Automatic Subtitling”. To be published in Transactions of the Association for Computational Linguistics (TACL).

[11] Silvia Alma Piazzolla, Beatrice Savoldi, Luisa Bentivogli. "Good, but not always Fair: An Evaluation of Gender Bias for three commercial Machine Translation Systems". To be published in Hermes Journal

[12] Dennis Fucci, Marco Gaido, Mauro Cettolo, Matteo Negri, Luisa Bentivogli. “Integrating Language Models into Direct Speech Translation: An Inference-Time Solution to Control Gender Inflection”. To be published in Proceedings of EMNLP 2023.

[13] Andrea Piergentili, Beatrice Savoldi, Dennis Fucci, Matteo Negri, Luisa Bentivogli. "Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus". To be published in Proceedings of EMNLP 2023.[1] 

[1] Esfahani S., De Toni G., Lepri B., Passerini A.,Tentori K., Zancanaro M.  Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration. submitted to 29th ACM Conference on Intelligent User Interfaces (ACM IUI).

[2] Bizzaro P.G., Della Valentina E., Mana N., Zancanaro M. Annotation and Classification of Relevant Clauses in Terms-and-Conditions Contracts. Submitted to Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

[3] Mousavi, S.M., Tanaka, S., Roccabruna, G., Yoshino, K., Nakamura, S. and Riccardi, G., 2023, July. What’s New? Identifying the Unfolding of New Events in a Narrative. In Proceedings of the The 5th Workshop on Narrative Understanding (pp. 1-10).

[4] Mousavi. M. S., Caldarella S. and Riccardi G., “ Response Generation in Longitudinal Dialogues: Which Knowledge Representation Helps? ” ACL, Proc. 5th Workshop on NLP for Conversational AI, 2023.

[5] Roccabruna G., Mousavi. M. S. and Riccardi G., “ Understanding Emotion Valence is a Joint Deep Learning Task” ACL, Proc. 13th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis 2023.

[6] Yin M., Roccabruna G., Azad A. and Riccardi G., “ Let's Give a Voice to Conversational Agents in Virtual Reality” Proc. INTERSPEECH, Demo Paper, Dublin, 2023.

[1] Antonucci, A., Bevilacqua, P., Leonardi, S. et al. Humans as path-finders for mobile robots using teach-by-showing navigation. Auton Robot (2023). https://doi.org/10.1007/s10514-023-10125-5

[2] When Prolog meets generative models: a new approach for managing knowledge and planning in robotic applications E Saccon, A Tikna, D De Martini, E Lamon, M Roveri, L Palopoli arXiv preprint arXiv:2309.15049, 2023•arxiv.org

[3] Elena Merlo, Marta Lagomarsino, Edoardo Lamon, Arash Ajoudani, Automatic Interaction and Unsupervised Activity Recognition from Videos of Human Manual Demonstrations with Application to Anomaly Detection, A., IEEE International Conference on Robot & Human Interactiv Communication (RO-MAN), 2023 

[4] R Bussola, M Focchi, A Del Prete, D Fontanelli, L Palopoli, Efficient Reinforcement Learning for Jumping MonopodsarXiv preprint arXiv:2309.07038, 2023•arxiv.org

[5] Placido Falqueto; Alessandro Antonucci; Luigi Palopoli; Daniele Fontanelli Humanising robot-assisted navigation,  Intelligent service robots (in PRESS)

[6] L Beber, E Lamon, D Nardi, D Fontanelli, M Saveriano, L Palopoli, A Passive Variable Impedance Control Strategy with Viscoelastic Parameters Estimation of Soft Tissues for Safe Ultrasonography, arXiv preprint arXiv:2309.14893, 2023•arxiv.org

[1] Burcu Sayin, Jie Yang, Xinyue Chen, Andrea Passerini, Fabio Casati. Rethinking and Recomputing the Value of ML Models. Submitted to the Journal of Artificial Intelligence Research.

[2] Burcu Sayin, Jie Yang, Xinyue Chen, Andrea Passerini, Fabio Casati. Value Based Hybrid Intelligence. HHAI 2023: Augmenting Human Intellect, 2023.

[3] Burcu Sayin, Jie Yang, Xinyue Chen, Andrea Passerini, Fabio Casati. Value-Aware Active Learning. HHAI 2023: Augmenting Human Intellect, 2023.

[4] Giovanni De Toni, Paolo Viappiani, Stefano Teso, Bruno Lepri, Andrea Passerini. Personalized Algorithmic Recourse with Preference Elicitation. In preparation for TMLR, 2023.

[5] Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini, Katya Tentori, Massimo Zancanaro. Exploiting Preference Elicitation in Interactive and User-centric Algorithmic Recourse: An Initial Exploration. Submitted to IUI, 2023.

[6] Giovanni De Toni, Martin Pawelczyk, Stefano Teso, Bruno Lepri, Andrea Passerini. Temporal Algorithmic Recourse. In preparation for ICML, 2024.

[7] Massimiliano Luca, Luca Pappalardo, Bruno Lepri, Gianni Barlacchi. Trajectory Test-Train Overlap in Next-Location Prediction Datasets. Machine Learning - journal track of ECML-PKDD 2023.\

[8] Sebastiano Bontorin, Simone Centellegher, Riccardo Gallotti, Luca Pappalardo, Manlio De Domenico, Bruno Lepri, Massimiliano Luca. Interplay of Individual and Collective Mobility to Enhance Predictability. In preparation for Nature Communications.

[9] Emanuele Marconato, Stefano Teso, Andrea Passerini. Neuro-Symbolic Reasoning Shortcuts: Mitigation Strategies and their Limitations. NeurIPS, 2023.

[10] Emanuele Marconato, Gianpaolo Bontempo, Elisa Ficarra, Simone Calderara, Andrea Passerini, Stefano Teso. Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts, and Concept Rehearsal. ICML, 2023.