Search Results for author: Marco Brambilla

Found 9 papers, 6 papers with code

Content-based Stance Classification of Tweets about the 2020 Italian Constitutional Referendum

1 code implementation NAACL (SocialNLP) 2021 Marco Di Giovanni, Marco Brambilla

Finally, we discuss the discrepancy between the magnitudes of tweets expressing a specific stance, obtained using both the hashtag-based approach and our trained classifier, and the real outcome of the referendum: the referendum was approved by 70% of the voters, while the number of tweets against the referendum is four times greater than the number of tweets supporting it.

Stance Classification

A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities

1 code implementation17 Oct 2022 Andrea Tocchetti, Lorenzo Corti, Agathe Balayn, Mireia Yurrita, Philip Lippmann, Marco Brambilla, Jie Yang

Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption.

Exploiting Twitter as Source of Large Corpora of Weakly Similar Pairs for Semantic Sentence Embeddings

1 code implementation EMNLP 2021 Marco Di Giovanni, Marco Brambilla

Semantic sentence embeddings are usually supervisedly built minimizing distances between pairs of embeddings of sentences labelled as semantically similar by annotators.

Semantic Textual Similarity Sentence +1

EFSG: Evolutionary Fooling Sentences Generator

no code implementations12 Oct 2020 Marco Di Giovanni, Marco Brambilla

Large pre-trained language representation models (LMs) have recently collected a huge number of successes in many NLP tasks.

Adversarial Attack Binary Classification +3

Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread

1 code implementation10 Oct 2020 Alessandro Paticchio, Tommaso Scarlatti, Marios Mattheakis, Pavlos Protopapas, Marco Brambilla

Studying the dynamics of COVID-19 is of paramount importance to understanding the efficiency of restrictive measures and develop strategies to defend against upcoming contagion waves.

Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning

no code implementations8 Apr 2019 Alessandro Bianchi, Moreno Raimondo Vendra, Pavlos Protopapas, Marco Brambilla

To solve this issue, we propose a transfer learning approach optimized to keep into account that in each layer of a CNN some filters are more susceptible to image distortion than others.

Classification General Classification +2

T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling

2 code implementations20 Nov 2018 Giorgia Ramponi, Pavlos Protopapas, Marco Brambilla, Ryan Janssen

Results show that classifiers trained on T-CGAN-generated data perform the same as classifiers trained on real data, even with very short time series and small training sets.

Data Augmentation Generative Adversarial Network +2

A User Modeling Pipeline for Studying Polarized Political Events in Social Media

1 code implementation25 Jul 2018 Roberto Napoli, Ali Mert Ertugrul, Alessandro Bozzon, Marco Brambilla

In the scope of this work, our proposed pipeline is applied to two referendum scenarios (independence of Catalonia in Spain and autonomy of Lombardy in Italy) in order to assess the performance of the approach with respect to the capability of collecting correct insights on the demographics of social media users and of predicting the poll results based on the opinions shared by the users.

Social and Information Networks Computers and Society

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