no code implementations • 11 Aug 2023 • Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, Damien Graux
Large Language Models (LLMs) have taken Knowledge Representation -- and the world -- by storm.
no code implementations • 31 Mar 2022 • Patrizio Bellan, Mauro Dragoni, Chiara Ghidini
Recent advances in Natural Language Processing, and in particular on the construction of very large pre-trained language representation models, is opening up new perspectives on the construction of conversational information seeking (CIS) systems.
no code implementations • 9 Mar 2022 • Patrizio Bellan, Han van der Aa, Mauro Dragoni, Chiara Ghidini, Simone Paolo Ponzetto
Therefore, to bridge this gap, we present the PET dataset, a first corpus of business process descriptions annotated with activities, gateways, actors, and flow information.
1 code implementation • 9 Dec 2021 • Ivan Donadello, Anthony Hunter, Stefano Teso, Mauro Dragoni
and (2) How can we identify for a new user the best utility function from amongst those that we have learned?
no code implementations • 13 Nov 2021 • Adrien Bennetot, Ivan Donadello, Ayoub El Qadi, Mauro Dragoni, Thomas Frossard, Benedikt Wagner, Anna Saranti, Silvia Tulli, Maria Trocan, Raja Chatila, Andreas Holzinger, Artur d'Avila Garcez, Natalia Díaz-Rodríguez
Last years have been characterized by an upsurge of opaque automatic decision support systems, such as Deep Neural Networks (DNNs).
BIG-bench Machine Learning Explainable artificial intelligence +2
2 code implementations • 7 Oct 2021 • Patrizio Bellan, Mauro Dragoni, Chiara Ghidini, Han van der Aa, Simone Paolo Ponzetto
The extraction of process models from text refers to the problem of turning the information contained in an unstructured textual process descriptions into a formal representation, i. e., a process model.
1 code implementation • LREC 2020 • Matteo Antonio Senese, Giuseppe Rizzo, Mauro Dragoni, Maurizio Morisio
In the last years, the state of the art of NLP research has made a huge step forward.
no code implementations • SEMEVAL 2018 • Mauro Dragoni
This paper describes the NeuroSent system that participated in SemEval 2018 Task 1.
no code implementations • SEMEVAL 2018 • Mauro Dragoni
This paper describes the NeuroSent system that participated in SemEval 2018 Task 3.
no code implementations • SEMEVAL 2018 • Mauro Dragoni
Discovering semantic relations within textual documents is a timely topic worthy of investigation.
no code implementations • LREC 2016 • Mauro Dragoni, Andrea Tettamanzi, C{\'e}lia da Costa Pereira
Opinion Mining is a topic which attracted a lot of interest in the last years.
no code implementations • LREC 2014 • Mauro Dragoni, Alessio Bosca, Matteo Casu, Andi Rexha
In the last decade, the need of having effective and useful tools for the creation and the management of linguistic resources significantly increased.