Typology
operator:
and / or
Language
operator:
and / or
Date
operator:
and / or
Rights
operator:
and / or
2023
Conference article
Open Access
Enhancing adversarial authorship verification with data augmentation
Corbara S., Moreo A.
It has been shown that many Authorship Identification systems are vulnerable to adversarial attacks, where an author actively tries to fool the classifier. We propose to tackle the adversarial Authorship Verification task by augmenting the training set with synthetic textual examples. In this ongoing study, we present preliminary results using two learning algorithms (SVM and Neural Network), and two generation strategies (based on language modeling and GAN training) for two generator models, on three datasets. We empirically show that data augmentation may help improve the performance of the classifier in an adversarial setup.Source: IIR 2023 - 13th Italian Information Retrieval Workshop, pp. 73–78, Pisa, Italy, 8-9/6/23.
Corbara S., Moreo A.
It has been shown that many Authorship Identification systems are vulnerable to adversarial attacks, where an author actively tries to fool the classifier. We propose to tackle the adversarial Authorship Verification task by augmenting the training set with synthetic textual examples. In this ongoing study, we present preliminary results using two learning algorithms (SVM and Neural Network), and two generation strategies (based on language modeling and GAN training) for two generator models, on three datasets. We empirically show that data augmentation may help improve the performance of the classifier in an adversarial setup.Source: IIR 2023 - 13th Italian Information Retrieval Workshop, pp. 73–78, Pisa, Italy, 8-9/6/23.
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
2022
Report
Open Access
AIMH research activities 2022
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2022 activities of the research group.Source: ISTI Annual reports, 2022
DOI: 10.32079/isti-ar-2022/002
Metrics:
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2022 activities of the research group.Source: ISTI Annual reports, 2022
DOI: 10.32079/isti-ar-2022/002
Metrics:
See at:
ISTI Repository | CNR ExploRA
2021
Report
Open Access
AIMH research activities 2021
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Coccomini D., Ciampi L., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2021 activities of the research group.Source: ISTI Annual Report, ISTI-2021-AR/003, pp.1–34, 2021
DOI: 10.32079/isti-ar-2021/003
Metrics:
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Coccomini D., Ciampi L., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2021 activities of the research group.Source: ISTI Annual Report, ISTI-2021-AR/003, pp.1–34, 2021
DOI: 10.32079/isti-ar-2021/003
Metrics:
See at:
ISTI Repository | CNR ExploRA
2020
Report
Open Access
MedLatin1 and MedLatin2: Two Datasets for the Computational Authorship Analysis of Medieval Latin Texts
Corbara S., Moreo A., Sebastiani F., Tavoni M.
We present and make available MedLatin1 and MedLatin2, two datasets of medieval Latin texts to be used in research on computational authorship analysis. MedLatin1 and MedLatin2 consist of 294 and 30 curated texts, respectively, labelled by author, with MedLatin1 texts being of an epistolary nature and MedLatin2 texts consisting of literary comments and treatises about various subjects. As such, these two datasets lend themselves to supporting research in authorship analysis tasks, such as authorship attribution, authorship verification, or same-author verification.Source: Research report, 2020
Corbara S., Moreo A., Sebastiani F., Tavoni M.
We present and make available MedLatin1 and MedLatin2, two datasets of medieval Latin texts to be used in research on computational authorship analysis. MedLatin1 and MedLatin2 consist of 294 and 30 curated texts, respectively, labelled by author, with MedLatin1 texts being of an epistolary nature and MedLatin2 texts consisting of literary comments and treatises about various subjects. As such, these two datasets lend themselves to supporting research in authorship analysis tasks, such as authorship attribution, authorship verification, or same-author verification.Source: Research report, 2020
See at:
arxiv.org | ISTI Repository | CNR ExploRA
2020
Report
Open Access
AIMH research activities 2020
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Carrara F., Casarosa V., Ciampi L., Concordia C., Corbara S., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Thanos C., Trupiano L., Vadicamo L., Vairo C.
Annual Report of the Artificial Intelligence for Media and Humanities laboratory (AIMH) research activities in 2020.Source: ISTI Annual Report, ISTI-2020-AR/001, 2020
DOI: 10.32079/isti-ar-2020/001
Metrics:
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Carrara F., Casarosa V., Ciampi L., Concordia C., Corbara S., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Thanos C., Trupiano L., Vadicamo L., Vairo C.
Annual Report of the Artificial Intelligence for Media and Humanities laboratory (AIMH) research activities in 2020.Source: ISTI Annual Report, ISTI-2020-AR/001, 2020
DOI: 10.32079/isti-ar-2020/001
Metrics:
See at:
ISTI Repository | CNR ExploRA
2019
Conference article
Open Access
The Epistle to Cangrande Through the Lens of Computational Authorship Verification
Corbara S., Moreo A., Sebastiani F., Tavoni M.
The Epistle to Cangrande is one of the most controversial among the works of Italian poet Dante Alighieri. For more than a hundred years now, scholars have been debating over its real paternity, i.e., whether it should be considered a true work by Dante or a forgery by an unnamed author. In this work we address this philological problem through the methodologies of (supervised) Computational Authorship Verification, by training a classifier that predicts whether a given work is by Dante Alighieri or not. We discuss the system we have set up for this endeavour, the training set we have assembled, the experimental results we have obtained, and some issues that this work leaves open.Source: International Conference on Image Analysis and Processing, pp. 148–158, Trento, Italia, 9-13 settembre, 2019
DOI: 10.1007/978-3-030-30754-7_15
Metrics:
Corbara S., Moreo A., Sebastiani F., Tavoni M.
The Epistle to Cangrande is one of the most controversial among the works of Italian poet Dante Alighieri. For more than a hundred years now, scholars have been debating over its real paternity, i.e., whether it should be considered a true work by Dante or a forgery by an unnamed author. In this work we address this philological problem through the methodologies of (supervised) Computational Authorship Verification, by training a classifier that predicts whether a given work is by Dante Alighieri or not. We discuss the system we have set up for this endeavour, the training set we have assembled, the experimental results we have obtained, and some issues that this work leaves open.Source: International Conference on Image Analysis and Processing, pp. 148–158, Trento, Italia, 9-13 settembre, 2019
DOI: 10.1007/978-3-030-30754-7_15
Metrics:
See at:
ISTI Repository | doi.org 
| link.springer.com | CNR ExploRA
2019
Conference article
Open Access
The Epistle to Cangrande through the Lens of computational authorship verification
Corbara S.
The Epistle to Cangrande is one of the most debated documents in the production of the Italian poet Dante Alighieri. For more than a hundred years scholars have been debating over its real paternity, whether it should be considered a work by Dante or a malicious forgery by an unnamed author. In this work, we try to address this philological problem through the methodologies of computational authorship verification and machine learning, by training a classifier on a dataset of medieval Latin prose texts and by using a set of authorship-related features. Although the project is still in a preliminary phase, the early results seem to confirm the hypothesis of a forgery.Source: FDIA 2019 - 9th PhD Symposium on Future Directions in Information Access co-located with 12th European Summer School in Information Retrieval (ESSIR 2019), pp. 29–35, Milan, Italy, July 17-18, 2019
Corbara S.
The Epistle to Cangrande is one of the most debated documents in the production of the Italian poet Dante Alighieri. For more than a hundred years scholars have been debating over its real paternity, whether it should be considered a work by Dante or a malicious forgery by an unnamed author. In this work, we try to address this philological problem through the methodologies of computational authorship verification and machine learning, by training a classifier on a dataset of medieval Latin prose texts and by using a set of authorship-related features. Although the project is still in a preliminary phase, the early results seem to confirm the hypothesis of a forgery.Source: FDIA 2019 - 9th PhD Symposium on Future Directions in Information Access co-located with 12th European Summer School in Information Retrieval (ESSIR 2019), pp. 29–35, Milan, Italy, July 17-18, 2019
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA