36 citations · 44 across the 5 of their papers we have counts for
6 papers
Large Language Models and Knowledge Graphs: Opportunities and Challenges
Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo +13
Large Language Models (LLMs) have taken Knowledge Representation -- and the world -- by storm. This inflection point marks a shift from explicit knowledge representation to a renew…
Leveraging pre-trained language models for conversational information seeking from text
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 th…
PET: An Annotated Dataset for Process Extraction from Natural Language Text
Patrizio Bellan, Han van der Aa, Mauro Dragoni +2
Process extraction from text is an important task of process discovery, for which various approaches have been developed in recent years. However, in contrast to other information…
Machine Learning for Utility Prediction in Argument-Based Computational Persuasion
Ivan Donadello, Anthony Hunter, Stefano Teso +1
Automated persuasion systems (APS) aim to persuade a user to believe something by entering into a dialogue in which arguments and counterarguments are exchanged. To maximize the pr…
A Practical guide on Explainable AI Techniques applied on Biomedical use case applications
Adrien Bennetot, Ivan Donadello, Ayoub El Qadi +10
Last years have been characterized by an upsurge of opaque automatic decision support systems, such as Deep Neural Networks (DNNs). Although they have great generalization and pred…
Process Extraction from Text: Benchmarking the State of the Art and Paving the Way for Future Challenges
Patrizio Bellan, Mauro Dragoni, Chiara Ghidini +2
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…