UNITOR @ DANKMEMES: Combining Convolutional Models and Transformer-based architectures for accurate MEME management

This paper describes the UNITOR system that participated to the “multimoDal Artefacts recogNition Knowledge for MEMES” (DANKMEMES) task within the context of EVALITA 2020. UNITOR implements a neural model which combines a Deep Convolutional Neural Network to encode visual information of input images and a Transformer-based architecture to encode the meaning of the attached texts. UNITOR ranked first in all subtasks, clearly confirming the robustness of the investigated neural architectures and suggesting the beneficial impact of the proposed combination strategy

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)