Publications

@conference{	11568_1327816,

title = {WiC-ITA at EVALITA2023: Overview of the EVALITA2023 Word-in-Context for ITAlian Task},

author = {Pierluigi Cassotti and Lucia Siciliani and Lucia C. Passaro and Maristella Gatto and Pierpaolo Basile},

url = {https://www.aaccademia.it/customized/downloadfile.php?tipo=opera_completa&formato=pdf&id=1654},

isbn = {9791255000693},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian Final Workshop (EVALITA 2023)},

pages = {316–324},

publisher = {Lexis Compagnia Editoriale in Torino srl},

address = {Torino},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1205488,

title = {WiC-ITA at EVALITA2023: Overview of the EVALITA2023 Word-in-Context for ITAlian Task},

author = {Pierluigi Cassotti and Lucia Siciliani and Lucia C. Passaro and Maristella Gatto and And Pierpaolo Basile},

url = {https://ceur-ws.org/Vol-3473/paper46.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {EVALITA 2023 Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian},

volume = {3473},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1287867,

title = {We Understand Elliptical Sentences, and Language Models should Too: A New Dataset for Studying Ellipsis and its Interaction with Thematic Fit},

author = {Davide Testa and Emmanuele Chersoni and Alessandro Lenci},

url = {https://aclanthology.org/2023.acl-long.188},

doi = {10.18653/v1/2023.acl-long.188},

isbn = {978-1-959429-72-2},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},

pages = {3340–3353},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1287947,

title = {Simplifying Administrative Texts for Italian L2 Readers with Controllable Transformers Models: A Data-driven Approach},

author = {Martina Miliani and Fernando Alva-Manchego and Alessandro Lenci},

isbn = {9791255000846},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 9th Italian Conference on Computational Linguistics, CLiC-it 2023},

pages = {304–316},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1327827,

title = {MULTI-Fake-DetectiVE at EVALITA 2023: Overview of the MULTImodal Fake News Detection and VErification Task},

author = {Alessandro Bondielli and Pietro Dell’Oglio and Alessandro Lenci and Francesco Marcelloni and Lucia C. Passaro and Marco Sabbatini},

isbn = {9791255000693},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian},

pages = {227–234},

publisher = {Lexis Compagnia Editoriale in Torino srl},

address = {Torino},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1203668,

title = {MULTI-Fake-DetectiVE at EVALITA 2023: Overview of the MULTImodal Fake News Detection and VErification Task},

author = {Alessandro Bondielli and Pietro Dell’Oglio and Alessandro Lenci and Francesco Marcelloni and Lucia C. Passaro and Marco Sabbatini},

url = {https://ceur-ws.org/Vol-3473/paper32.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {EVALITA 2023: 8th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, Sep 7 – 8, Parma, IT},

volume = {3473},

pages = {1–8},

publisher = {CEUR-WS},

address = {Aachen},

abstract = {This paper introduces the MULTI-Fake-DetectiVE shared task for the EVALITA 2023 campaign. The task was aimed at exploring multimodality within the realm of fake news and intended to address the problem from two perspectives, represented by the two sub-tasks. In sub-task 1, we aimed to evaluate the effectiveness of multimodal fake news detection systems. In sub-task 2, we sought to gain insights into the interplay between text and images, specifically how they mutually influence the interpretation of content in the context of distinguishing between fake and real news. Both perspectives were framed as classification problems. 

The paper presents an overview of the task. In particular, we detail the key aspects of the task, including the creation of a new dataset for fake news detection in Italian, the evaluation methodology and criteria, the participant systems, and their results. In light of the obtained results, we argue that the problem is still open and propose some future directions.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1184107,

title = {Leveraging Sequence Mining for Robot Process Automation},

author = {Pietro Dell'Oglio and Alessandro Bondielli and Alessio Bechini and Francesco Marcelloni},

isbn = {978-3-031-35510-3},

year  = {2023},

date = {2023-01-01},

booktitle = {Intelligent Systems Design and Applications},

pages = {224–233},

publisher = {Springer Nature Switzerland},

abstract = {The automation of sequences of repetitive actions performed by human operators in interacting with software applications is crucial to prevent work from being perceived as alienating and boring. Robot applications can automatise these sequences once they have been identified. In this paper, we propose a two-step approach to mine sequences of actions that could be automated from log data produced by the interactions of a human operator with specific software applications. Since the number of possible sequences may be very high and not all the sequences are interesting to be automatised, we focus our mining process on sequences that meet precise patterns. First, Frequent Episode Mining algorithms are applied for extracting all the sequences of actions that occur with at least a minimum frequency. Then, we exploit fuzzy string matching based on the Levenshtein distance for filtering out the sequences that do not match established patterns. We evaluate the effectiveness of the approach using a benchmark dataset and present a case study on a real-world dataset of activity logs generated in the context of the AUTOMIA project.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1205447,

title = {Inconsistency Detection in Natural Language Requirements using ChatGPT: a Preliminary Evaluation},

author = {Alessandro Fantechi and Stefania Gnesi and Lucia Passaro and Laura Semini},

url = {https://ieeexplore.ieee.org/document/10260964},

doi = {10.1109/RE57278.2023.00045},

isbn = {979-8-3503-2689-5},

year  = {2023},

date = {2023-01-01},

booktitle = {2023 IEEE 31st International Requirements Engineering Conference (RE)},

pages = {335–340},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1217988.2,

title = {CheckIT!: A Corpus of Expert Fact-checked Claims for Italian},

author = {J. Gili and L. Passaro and T. Caselli},

url = {https://ceur-ws.org/Vol-3596/paper27.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 9th Italian Conference on Computational Linguistics},

volume = {3596},

publisher = {CEUR-WS},

address = {Aachen},

abstract = {This paper introduces CheckIT!, a resource of expert fact-checked claims, filling a gap for the development of fact-checking pipelines in Italian. We further investigate the use of three state-of-the-art generative text models to create variations of claims in zero-shot settings as a data-augmentation strategy for the identification of previously fact-checked claims. Our results indicate that models struggles in varying the surface forms of the claims.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1218007.2,

title = {Challenging specialized transformers on zero-shot classification},

author = {S. Auriemma and M. Madeddu and M. Miliani and A. Bondielli and A. Lenci and L. Passaro},

url = {https://ceur-ws.org/Vol-3596/paper6.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 9th Italian Conference on Computational Linguistics},

volume = {3596},

publisher = {CEUR-WS},

address = {Aachen},

abstract = {This paper investigates the feasibility of employing basic prompting systems for domain-specific language models. The study focuses on bureaucratic language and uses the recently introduced BureauBERTo model for experimentation. The experiments reveal that while further pre-trained models exhibit reduced robustness concerning general knowledge, they display greater adaptability in modeling domain-specific tasks, even under a zero-shot paradigm. This demonstrates the potential of leveraging simple prompting systems in specialized contexts, providing valuable insights both for research and industry.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1205508,

title = {BureauBERTo: adapting UmBERTo to the Italian bureaucratic language},

author = {Serena Auriemma and Mauro Madeddu and Martina Miliani and Alessandro Bondielli and Lucia C. Passaro and Alessandro Lenci},

url = {https://ceur-ws.org/Vol-3486/42.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the Italia Intelligenza Artificiale - Thematic Workshops co-located with the 3rd CINI National Lab AIIS Conference on Artificial Intelligence (Ital IA 2023)},

volume = {3486},

pages = {240–248},

publisher = {CEUR-WS.org},

abstract = {In this work, we introduce BureauBERTo, the first transformer-based language model adapted to the Italian Public Administration (PA) and technical-bureaucratic domains. We further pre-trained the general-purpose Italian model UmBERTo on a corpus of PA, banking, and insurance documents, and we expanded UmBERTo’s vocabulary with domain-specific terms. We show that BureauBERTo benefitted from the adaptation by comparing it with UmBERTo in both an intrinsic and extrinsic evaluation. The intrinsic evaluation has been conducted through specific fill-mask experiments. The extrinsic one has been faced with a named entity recognition task on one of the sub-domains in BureauBERTo.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1287927,

title = {Assessing Language and Vision-Language Models on Event Plausibility},

author = {Maria Cassese and Alessando Bondielli and Alessandro Lenci},

isbn = {9791255000846},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 9th Italian Conference on Computational Linguistics, CLiC-it 2023},

pages = {121–128},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1287907,

title = {Are Language Models Sensitive to Semantic Attraction? A Study on Surprisal},

author = {Yan Cong and Emmanuele Chersoni and Yu-Yin Hsu and Alessandro Lenci},

url = {https://aclanthology.org/2023.starsem-1.13},

doi = {10.18653/v1/2023.starsem-1.13},

isbn = {978-1-959429-76-0},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)},

pages = {141–148},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1287887,

title = {Are Frequent Phrases Directly Retrieved like Idioms? An Investigation with Self-paced Reading and Language Models},

author = {Giulia Rambelli and Emmanuele Chersoni and Marco S. G. Senaldi and Philippe Blache and Alessandro Lenci},

url = {https://aclanthology.org/2023.mwe-1.13},

doi = {10.18653/v1/2023.mwe-1.13},

isbn = {978-1-959429-59-3},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 19th Workshop on Multiword Expressions (MWE 2023)},

pages = {87–98},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288049,

title = {Does BERT Recognize an Agent? Modeling Dowty's Proto-Roles with Contextual Embeddings},

author = {Mattia Proietti and Gianluca E. Lebani and Alessandro Lenci},

url = {https://aclanthology.org/2022.coling-1.360},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the 29th International Conference on Computational Linguistics},

pages = {4101–4112},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1171485,

title = {Compositionality as an Analogical Process: Introducing ANNE},

author = {Giulia Rambelli and Emmanuele Chersoni and Philippe Blache and Alessandro Lenci},

url = {https://aclanthology.org/2022.cogalex-1.10},

isbn = {978-1-959429-01-2},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the Workshop on Cognitive Aspects of the Lexicon},

pages = {78–96},

publisher = {Association for Computational Linguistics},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1154540,

title = {Bias Discovery within Human Raters: A Case Study of the Jigsaw Dataset},

author = {Marta MARCHIORI MANERBA and Riccardo Guidotti and Lucia Passaro and Salvatore Ruggieri},

url = {https://aclanthology.org/2022.nlperspectives-1.4.pdf},

isbn = {979-10-95546-98-6},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the LREC 2022 workshop on Perspectivist Approaches to Disagreement in NLP (NLPerspectives)},

pages = {26–31},

publisher = {European Language Resources Association (ELRA)},

address = {Paris},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1139416,

title = {A Self-Paced Reading study on Processing Constructions with different degrees of Compositionality},

author = {Alessandro Lenci and Philippe Blache},

year  = {2022},

date = {2022-01-01},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288050,

title = {Word Order Matters When You Increase Masking},

author = {Karim Lasri and Alessandro Lenci and Thierry Poibeau},

url = {https://aclanthology.org/2022.emnlp-main.118},

doi = {10.18653/v1/2022.emnlp-main.118},

isbn = {978-1-959429-40-1},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing},

pages = {1808–1815},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{miliani2022understanding,

title = {Understanding Italian Administrative Texts: A Reader-Oriented Study for Readability Assessment and Text Simplification.},

author = {Martina Miliani and Marco SG Senaldi and Gianluca Lebani and Alessandro Lenci and others},

year  = {2022},

date = {2022-01-01},

booktitle = {AIxPA@ AI* IA},

pages = {71–87},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288048,

title = {Subject Verb Agreement Error Patterns in Meaningless Sentences: Humans vs. BERT},

author = {Karim Lasri and Olga Seminck and Alessandro Lenci and Thierry Poibeau},

url = {https://aclanthology.org/2022.coling-1.4},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the 29th International Conference on Computational Linguistics},

number = {1},

pages = {37–43},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1141986,

title = {Responsible Artificial Intelligence as a Driver of Innovation in Society and Industry},

author = {Alessio Bechini and Alessandro Bondielli and Pietro Ducange and Francesco Marcelloni and Alessandro Renda},

year  = {2022},

date = {2022-01-01},

booktitle = {Atti del Secondo Convegno Nazionale CINI sull'Intelligenza Artificiale},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288047,

title = {Probing for the Usage of Grammatical Number},

author = {Karim Lasri and Tiago Pimentel and Alessandro Lenci and Thierry Poibeau and Ryan Cotterell},

url = {https://aclanthology.org/2022.acl-long.603},

doi = {10.18653/v1/2022.acl-long.603},

isbn = {978-1-955917-21-6},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},

pages = {8818–8831},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Nozza2022,

title = {Preface to the Sixth Workshop on Natural Language for Artificial Intelligence (NL4AI)},

author = {D. Nozza and L. Passaro and M. Polignano},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143284743&partnerID=40&md5=4f360c53680288347416d49999ee161e},

year  = {2022},

date = {2022-01-01},

journal = {CEUR Workshop Proceedings},

volume = {3287},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288031,

title = {Pragmatic and Logical Inferences in NLI Systems: The Case of Conjunction Buttressing},

author = {Paolo Pedinotti and Emmanuele Chersoni and Enrico Santus and Alessandro Lenci},

url = {https://aclanthology.org/2022.unimplicit-1.2},

doi = {10.18653/v1/2022.unimplicit-1.2},

isbn = {978-1-955917-92-6},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the Second Workshop on Understanding Implicit and Underspecified Language},

pages = {8–16},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1141976,

title = {Online Monitoring of Stance from Tweets: The case of Green Pass in Italy},

author = {Alessandro Bondielli and Giuseppe CANCELLO TORTORA and Pietro Ducange and Armando Macrì and Francesco Marcelloni and Alessandro Renda},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of IEEE EAIS 2022 (International Conference on Evolving and Adaptive Intelligent Systems)},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288087,

title = {Neural Readability Pairwise Ranking for Sentences in Italian Administrative Language},

author = {Martina Miliani and Serena Auriemma and Fernando Alva-Manchego and Alessandro Lenci},

url = {https://aclanthology.org/2022.aacl-main.63},

doi = {10.18653/v1/2022.aacl-main.63},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},

pages = {849–866},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Sucameli2022153,

title = {MATE, a Meta Layer Between Natural Language and Database},

author = {I. Sucameli and A. Bondielli and L. C. Passaro and E. Annunziata and G. Lucherini and A. Romei and A. Lenci},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143255453&partnerID=40&md5=e7f485b53eb50ec26f8851dd8cefd181},

year  = {2022},

date = {2022-01-01},

journal = {CEUR Workshop Proceedings},

volume = {3287},

pages = {153-163},

abstract = {Nowadays, the knowledge of query languages like SQL is mandatory for accessing the most relevant information concerning a company's business, stored in richly structured databases. The advancement of Natural Language Processing and Deep Learning research has made it possible to develop different models for the conversion of natural language questions into formalized queries. Although the performance of these models is very satisfactory on internationally established benchmarks for the English language, it is undoubtedly necessary to investigate their portability with respect to the types of databases and natural languages used for formulating the questions. For this reason, we realised Mate (Meta lAyer between naTural language and databasE), a framework for interfacing humans and databases, thus facilitating the access in natural language to the data stored in databases. Indeed, Mate is developed with the aim of accessing information in a very simple way, from the perspective of a human-centered AI. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1327847,

title = {GQA-it: Italian Question Answering on Image Scene Graphs},

author = {Danilo Croce and Lucia C. Passaro and Alessandro Lenci and Roberto Basili},

url = {https://books.openedition.org/aaccademia/10535},

doi = {10.4000/books.aaccademia.10535},

isbn = {9791280136947},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021},

pages = {92–99},

publisher = {Accademia University Press},

address = {Torino},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288067,

title = {From Speed to Car and Back: An Exploratory Study about Associations between Abstract Nouns and Images},

author = {Ludovica Cerini and Eliana DI PALMA and Alessandro Lenci},

url = {https://aclanthology.org/2022.clasp-1.9},

isbn = {978-1-955917-67-4},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the 2022 CLASP Conference on (Dis)embodiment},

pages = {80–88},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288107,

title = {FANCY: A Diagnostic Data-Set for NLI Models},

author = {Guido Rocchietti and Flavia Achena and Giuseppe Marziano and Sara Salaris and Alessandro Lenci},

doi = {10.4000/books.aaccademia.10804},

isbn = {9791280136947},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021},

pages = {287–292},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1160772,

title = {Evaluating Pre-Trained Transformers on Italian Administrative Texts},

author = {S. Auriemma and M. Miliani and A. Bondielli and L. C. Passaro and A. Lenci},

url = {https://ceur-ws.org/Vol-3285/paper4.pdf},

year  = {2022},

date = {2022-01-01},

booktitle = {Proceedings of 1st Workshop on AI for Public Administration},

volume = {3285},

pages = {54–70},

publisher = {CEUR-WS},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1288032,

title = {Does BERT really agree ? Fine-grained Analysis of Lexical Dependence on a Syntactic Task},

author = {Karim Lasri and Alessandro Lenci and Thierry Poibeau},

url = {https://aclanthology.org/2022.findings-acl.181},

doi = {10.18653/v1/2022.findings-acl.181},

isbn = {978-1-955917-25-4},

year  = {2022},

date = {2022-01-01},

booktitle = {Findings of the Association for Computational Linguistics: ACL 2022},

pages = {2309–2315},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1113570,

title = {Preface to the fifth Workshop on Natural Language for Artificial Intelligence (NL4AI)},

author = {Elena Cabrio and Danilo Croce and Lucia C. Passaro and Rachele Sprugnoli},

url = {http://ceur-ws.org/Vol-3015/xpreface.pdf},

year  = {2021},

date = {2021-01-01},

booktitle = {Proceedings of the Fifth Workshop on Natural Language for Artificial Intelligence (NL4AI 2021) co-located with 20th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2021)},

volume = {3015},

publisher = {RWTH Aachen University},

address = {Aachen},

abstract = {Preface to the fifth Workshop on Natural Language for Artificial Intelligence (NL4AI)},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{	11568_1134768,

title = {PIHKers at CMCL 2021 Shared Task: Cosine Similarity and Surprisal to Predict Human Reading Patterns},

author = {Lavinia Salicchi and Alessandro Lenci},

isbn = {978-1-954085-35-0},

year  = {2021},

date = {2021-01-01},

booktitle = {Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics},

pages = {102–107},

publisher = {Association for Computational Linguistics},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}