Fiche du document
11 mai 2021
- doi: 10.4000/books.aaccademia.7250
- eisbn: 9791280136329
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Mots-clés
EVALITA COVID-19 Infodemic linguistica computazionale Automatic Misogyny Identification Misogyny on Twitter Posts AlBERTo Convolutional Neural Network BERT Model Hate Speech Detection Multimodal Meme Detection MEME management Language Game ``La Ghigliottina'' Language & Linguistics LAN000000 CBXSujets proches
Generation Procreation Pangenesis AmphimixisCiter ce document
De Mattei Lorenzo et al., « CHANGE-IT @ EVALITA 2020: Change Headlines, Adapt News, GEnerate », Accademia University Press, ID : 10.4000/books.aaccademia.7250
Métriques
Partage / Export
Résumé
We propose a generation task for Italian – more specifically, a style transfer task for headlines of Italian newspapers. This is the first shared task on generation included in the EVALITA evaluation framework. Indeed, one of the reasons to have this task is to stimulate more research on generation within the Italian community. With this aim in mind, we release to the participating teams not only training data, but also a baseline sequence to sequence model that performs the task in order to help everyone get started, even when not accustomed to Natural Language Generation (NLG) approaches. Contextually, we explore the complex issue of automatic evaluation of generated text, which is receiving particular attention in the NLG community.