no code implementations • SMM4H (COLING) 2022 • Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
This paper describes the models developed by the AILAB-Udine team for the SMM4H’22 Shared Task.
no code implementations • EMNLP (sustainlp) 2020 • Giuseppe Lancioni, Saida S.Mohamed, Beatrice Portelli, Giuseppe Serra, Carlo Tasso
Keyphrase Generation is the task of predicting Keyphrases (KPs), short phrases that summarize the semantic meaning of a given document.
1 code implementation • 22 Dec 2023 • Ali Abdari, Alex Falcon, Giuseppe Serra
Recently, the Metaverse is becoming increasingly attractive, with millions of users accessing the many available virtual worlds.
no code implementations • 15 Nov 2023 • Giuseppe Serra, Photios A. Stavrou, Marios Kountouris
In this paper, we study the computation of the rate-distortion-perception function (RDPF) for a multivariate Gaussian source under mean squared error (MSE) distortion and, respectively, Kullback-Leibler divergence, geometric Jensen-Shannon divergence, squared Hellinger distance, and squared Wasserstein-2 distance perception metrics.
1 code implementation • 6 Sep 2023 • Ali Abdari, Alex Falcon, Giuseppe Serra
Nowadays, many people frequently have to search for new accommodation options.
no code implementations • 27 Jun 2023 • Alex Falcon, Giuseppe Serra
In this report, we present the technical details of our submission to the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge 2023.
1 code implementation • 8 Jun 2023 • Simone Scaboro, Beatrice Portellia, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
Adverse Event (ADE) extraction is one of the core tasks in digital pharmacovigilance, especially when applied to informal texts.
no code implementations • 3 Apr 2023 • Zhao Xu, Daniel Onoro Rubio, Giuseppe Serra, Mathias Niepert
The resulting sparsity of a representation is not fixed, but fits to the observation itself under the pre-defined restriction.
1 code implementation • 21 Oct 2022 • Beatrice Portelli, Simone Scaboro, Enrico Santus, Hooman Sedghamiz, Emmanuele Chersoni, Giuseppe Serra
Medical term normalization consists in mapping a piece of text to a large number of output classes.
1 code implementation • 28 Sep 2022 • Giuseppe Serra, Mathias Niepert
Graph Neural Networks (GNNs) are a popular class of machine learning models.
1 code implementation • 22 Sep 2022 • Massimiliano Incudini, Daniele Lizzio Bosco, Francesco Martini, Michele Grossi, Giuseppe Serra, Alessandra Di Pierro
Quantum computing can empower machine learning models by enabling kernel machines to leverage quantum kernels for representing similarity measures between data.
no code implementations • 7 Sep 2022 • Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
This paper describes the models developed by the AILAB-Udine team for the SMM4H 22 Shared Task.
no code implementations • 6 Sep 2022 • Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
In the last decade, an increasing number of users have started reporting Adverse Drug Events (ADE) on social media platforms, blogs, and health forums.
1 code implementation • 3 Aug 2022 • Alex Falcon, Giuseppe Serra, Oswald Lanz
Data augmentation techniques were introduced to increase the performance on unseen test examples by creating new training samples with the application of semantics-preserving techniques, such as color space or geometric transformations on images.
no code implementations • 10 Jul 2022 • Bhushan Kotnis, Kiril Gashteovski, Julia Gastinger, Giuseppe Serra, Francesco Alesiani, Timo Sztyler, Ammar Shaker, Na Gong, Carolin Lawrence, Zhao Xu
With Human-Centric Research (HCR) we can steer research activities so that the research outcome is beneficial for human stakeholders, such as end users.
no code implementations • 22 Jun 2022 • Alex Falcon, Giuseppe Serra, Sergio Escalera, Oswald Lanz
This report presents the technical details of our submission to the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge 2022.
Ranked #3 on Multi-Instance Retrieval on EPIC-KITCHENS-100
1 code implementation • 27 Apr 2022 • Alex Falcon, Swathikiran Sudhakaran, Giuseppe Serra, Sergio Escalera, Oswald Lanz
We show that even if we carefully tuned the fixed margin, our technique (which does not have the margin as a hyper-parameter) would still achieve better performance.
Ranked #7 on Multi-Instance Retrieval on EPIC-KITCHENS-100
2 code implementations • 16 Mar 2022 • Alex Falcon, Giuseppe Serra, Oswald Lanz
Due to the amount of videos and related captions uploaded every hour, deep learning-based solutions for cross-modal video retrieval are attracting more and more attention.
Ranked #5 on Multi-Instance Retrieval on EPIC-KITCHENS-100
1 code implementation • WNUT (ACL) 2021 • Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
Adverse Drug Event (ADE) extraction models can rapidly examine large collections of social media texts, detecting mentions of drug-related adverse reactions and trigger medical investigations.
1 code implementation • 25 Jul 2021 • Kevin Roitero, Michael Soprano, Beatrice Portelli, Massimiliano De Luise, Damiano Spina, Vincenzo Della Mea, Giuseppe Serra, Stefano Mizzaro, Gianluca Demartini
Our results show that: workers are able to detect and objectively categorize online (mis)information related to COVID-19; both crowdsourced and expert judgments can be transformed and aggregated to improve quality; worker background and other signals (e. g., source of information, behavior) impact the quality of the data.
1 code implementation • 19 May 2021 • Beatrice Portelli, Daniele Passabì, Edoardo Lenzi, Giuseppe Serra, Enrico Santus, Emmanuele Chersoni
In recent years, Internet users are reporting Adverse Drug Events (ADE) on social media, blogs and health forums.
1 code implementation • EACL 2021 • Beatrice Portelli, Edoardo Lenzi, Emmanuele Chersoni, Giuseppe Serra, Enrico Santus
Pretrained transformer-based models, such as BERT and its variants, have become a common choice to obtain state-of-the-art performances in NLP tasks.
no code implementations • 22 Aug 2020 • Alex Falcon, Oswald Lanz, Giuseppe Serra
Video Question Answering (VideoQA) is a task that requires a model to analyze and understand both the visual content given by the input video and the textual part given by the question, and the interaction between them in order to produce a meaningful answer.
1 code implementation • 13 Aug 2020 • Kevin Roitero, Michael Soprano, Beatrice Portelli, Damiano Spina, Vincenzo Della Mea, Giuseppe Serra, Stefano Mizzaro, Gianluca Demartini
Misinformation is an ever increasing problem that is difficult to solve for the research community and has a negative impact on the society at large.
no code implementations • WS 2020 • Beatrice Portelli, Jason Zhao, Tal Schuster, Giuseppe Serra, Enrico Santus
We propose, instead, a model-agnostic framework that consists of two modules: (1) a span extractor, which identifies the crucial information connecting claim and evidence; and (2) a classifier that combines claim, evidence, and the extracted spans to predict the veracity of the claim.
no code implementations • 9 Oct 2019 • Marco Menardi, Alex Falcon, Saida S. Mohamed, Lorenzo Seidenari, Giuseppe Serra, Alberto del Bimbo, Carlo Tasso
To address this issue, in this paper we propose an approach capable of generating images starting from a given text using conditional GANs trained on uncaptioned images dataset.
no code implementations • 26 Sep 2019 • Marco Zamprogno, Marco Passon, Niki Martinel, Giuseppe Serra, Giuseppe Lancioni, Christian Micheloni, Carlo Tasso, Gian Luca Foresti
In this paper we consider the problem of video-based person re-identification, which is the task of associating videos of the same person captured by different and non-overlapping cameras.
no code implementations • WS 2018 • Marco Passon, Marco Lippi, Giuseppe Serra, Carlo Tasso
Internet users generate content at unprecedented rates.
no code implementations • RANLP 2017 • Marco Basaldella, Muhammad Helmy, Elisa Antolli, Mihai Horia Popescu, Giuseppe Serra, Carlo Tasso
On the five languages we analyzed, results show an improvement in performance when using a machine learning algorithm, even if such algorithm is not trained and tested on the same language.
no code implementations • 26 Jun 2017 • Marcella Cornia, Lorenzo Baraldi, Giuseppe Serra, Rita Cucchiara
Image captioning has been recently gaining a lot of attention thanks to the impressive achievements shown by deep captioning architectures, which combine Convolutional Neural Networks to extract image representations, and Recurrent Neural Networks to generate the corresponding captions.
Ranked #2 on Image Captioning on Flickr30k Captions test (using extra training data)
2 code implementations • 29 Nov 2016 • Marcella Cornia, Lorenzo Baraldi, Giuseppe Serra, Rita Cucchiara
Data-driven saliency has recently gained a lot of attention thanks to the use of Convolutional Neural Networks for predicting gaze fixations.
2 code implementations • 5 Sep 2016 • Marcella Cornia, Lorenzo Baraldi, Giuseppe Serra, Rita Cucchiara
Current state of the art models for saliency prediction employ Fully Convolutional networks that perform a non-linear combination of features extracted from the last convolutional layer to predict saliency maps.
no code implementations • 28 Jul 2016 • Stefano Alletto, Giuseppe Serra, Rita Cucchiara
To effectively register an egocentric video sequence under these conditions, we propose to tackle the source of the problem: the matching process.
no code implementations • 2 Jul 2014 • Lamberto Ballan, Marco Bertini, Giuseppe Serra, Alberto del Bimbo
Our approach exploits collective knowledge embedded in user-generated tags and web sources, and visual similarity of keyframes and images uploaded to social sites like YouTube and Flickr, as well as web sources like Google and Bing.