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2023
Conference article
Open Access
AIMH at MULTI-Fake-DetectIVE: system report
Puccetti G., Esuli A.
This report describes our contribution to the EVALITA 2023 shared task MULTI-Fake-DetectIVE which involves the classification of news including textual and visual components. To experiment on this task we focus on textual data augmentation, extending the Italian text and the Images available in the training set using machine translation models and image captioning ones. To train using different set of input features, we use different transformer encoders for each variant of text (Italian, English) and modality (Image). For Task 1, among the models we test, we find that using the Italian text together with its translation improves the model performance while the captions don't provide any improvement. We test the same architecture also on Task 2 although in this case we achieve less satisfactory resultsSource: EVALITA 2023 - Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, Parma, Italy, 7-9/09/2023
Project(s): SoBigData
Puccetti G., Esuli A.
This report describes our contribution to the EVALITA 2023 shared task MULTI-Fake-DetectIVE which involves the classification of news including textual and visual components. To experiment on this task we focus on textual data augmentation, extending the Italian text and the Images available in the training set using machine translation models and image captioning ones. To train using different set of input features, we use different transformer encoders for each variant of text (Italian, English) and modality (Image). For Task 1, among the models we test, we find that using the Italian text together with its translation improves the model performance while the captions don't provide any improvement. We test the same architecture also on Task 2 although in this case we achieve less satisfactory resultsSource: EVALITA 2023 - Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, Parma, Italy, 7-9/09/2023
Project(s): SoBigData
See at:
ceur-ws.org 
| ISTI Repository | CNR ExploRA
2023
Report
Open Access
AIMH Research Activities 2023
Aloia N., Amato G., Bartalesi V., Bianchi L., Bolettieri P., Bosio C., Carraglia M., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., De Martino C., Di Benedetto M., Esuli A., Falchi F., Fazzari E., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Puccetti G., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C., Versienti L.
The AIMH (Artificial Intelligence for Media and Humanities) laboratory is dedicated to exploring and pushing the boundaries in the field of Artificial Intelligence, with a particular focus on its application in digital media and humanities. This lab's objective is to enhance the current state of AI technology particularly on deep learning, text analysis, computer vision, multimedia information retrieval, multimedia content analysis, recognition, and retrieval. This report encapsulates the laboratory's progress and activities throughout the year 2023.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/001
Metrics:
Aloia N., Amato G., Bartalesi V., Bianchi L., Bolettieri P., Bosio C., Carraglia M., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., De Martino C., Di Benedetto M., Esuli A., Falchi F., Fazzari E., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Puccetti G., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C., Versienti L.
The AIMH (Artificial Intelligence for Media and Humanities) laboratory is dedicated to exploring and pushing the boundaries in the field of Artificial Intelligence, with a particular focus on its application in digital media and humanities. This lab's objective is to enhance the current state of AI technology particularly on deep learning, text analysis, computer vision, multimedia information retrieval, multimedia content analysis, recognition, and retrieval. This report encapsulates the laboratory's progress and activities throughout the year 2023.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/001
Metrics:
See at:
ISTI Repository | CNR ExploRA