153 citations · 351 across the 22 of their papers we have counts for
26 papers
Quantifying Query Fairness Under Unawareness
Thomas Jaenich, Alejandro Moreo, Alessandro Fabris +4
Traditional ranking algorithms are designed to retrieve the most relevant items for a user's query, but they often inherit biases from data that can unfairly disadvantage vulnerabl…
Detecting Images Generated by Diffusers
Davide Alessandro Coccomini, Andrea Esuli, Fabrizio Falchi +2
This paper explores the task of detecting images generated by text-to-image diffusion models. To evaluate this, we consider images generated from captions in the MSCOCO and Wikimed…
Unravelling Interlanguage Facts via Explainable Machine Learning
Barbara Berti, Andrea Esuli, Fabrizio Sebastiani
Native language identification (NLI) is the task of training (via supervised machine learning) a classifier that guesses the native language of the author of a text. This task has…
Transformer-Based Multi-modal Proposal and Re-Rank for Wikipedia Image-Caption Matching
Nicola Messina, Davide Alessandro Coccomini, Andrea Esuli +1
With the increased accessibility of web and online encyclopedias, the amount of data to manage is constantly increasing. In Wikipedia, for example, there are millions of pages writ…
LeQua@CLEF2022: Learning to Quantify
Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
LeQua 2022 is a new lab for the evaluation of methods for "learning to quantify" in textual datasets, i.e., for training predictors of the relative frequencies of the classes of in…
Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach
Alessandro Fabris, Andrea Esuli, Alejandro Moreo +1
Algorithms and models are increasingly deployed to inform decisions about people, inevitably affecting their lives. As a consequence, those in charge of developing these models mus…
QuaPy: A Python-Based Framework for Quantification
Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani
QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estimation), written in Python. Quantification is the task of training quantifiers via…
Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders
Nicola Messina, Giuseppe Amato, Andrea Esuli +3
Despite the evolution of deep-learning-based visual-textual processing systems, precise multi-modal matching remains a challenging task. In this work, we tackle the task of cross-m…
Transformer Reasoning Network for Image-Text Matching and Retrieval
Nicola Messina, Fabrizio Falchi, Andrea Esuli +1
Image-text matching is an interesting and fascinating task in modern AI research. Despite the evolution of deep-learning-based image and text processing systems, multi-modal matchi…
Word-Class Embeddings for Multiclass Text Classification
Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani
Pre-trained word embeddings encode general word semantics and lexical regularities of natural language, and have proven useful across many NLP tasks, including word sense disambigu…
Cross-Lingual Sentiment Quantification
Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
\emph{Sentiment Quantification} (i.e., the task of estimating the relative frequency of sentiment-related classes -- such as \textsf{Positive} and \textsf{Negative} -- in a set of…
Building Automated Survey Coders via Interactive Machine Learning
Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
Software systems trained via machine learning to automatically classify open-ended answers (a.k.a. verbatims) are by now a reality. Still, their adoption in the survey coding indus…
Learning to Weight for Text Classification
Alejandro Moreo Fernández, Andrea Esuli, Fabrizio Sebastiani
In information retrieval (IR) and related tasks, term weighting approaches typically consider the frequency of the term in the document and in the collection in order to compute a…
Funnelling: A New Ensemble Method for Heterogeneous Transfer Learning and its Application to Cross-Lingual Text Classification
Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
Cross-lingual Text Classification (CLC) consists of automatically classifying, according to a common set C of classes, documents each written in one of a set of languages L, and do…
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments
Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani
This paper introduces PyDCI, a new implementation of Distributional Correspondence Indexing (DCI) written in Python. DCI is a transfer learning method for cross-domain and cross-li…
Traj2User: exploiting embeddings for computing similarity of users mobile behavior
Andrea Esuli, Lucas May Petry, Chiara Renso +1
Semantic trajectories are high level representations of user movements where several aspects related to the movement context are represented as heterogeneous textual labels. With t…
A Recurrent Neural Network for Sentiment Quantification
Andrea Esuli, Alejandro Moreo Fernández, Fabrizio Sebastiani
Quantification is a supervised learning task that consists in predicting, given a set of classes C and a set D of unlabelled items, the prevalence (or relative frequency) p(c|D) of…
JaTeCS an open-source JAva TExt Categorization System
Andrea Esuli, Tiziano Fagni, Alejandro Moreo Fernandez
JaTeCS is an open source Java library that supports research on automatic text categorization and other related problems, such as ordinal regression and quantification, which are o…
Exploring epoch-dependent stochastic residual networks
Fabio Carrara, Andrea Esuli, Fabrizio Falchi +1
The recently proposed stochastic residual networks selectively activate or bypass the layers during training, based on independent stochastic choices, each of which following a pro…
On the Impact of Entity Linking in Microblog Real-Time Filtering
Giacomo Berardi, Diego Ceccarelli, Andrea Esuli +1
Microblogging is a model of content sharing in which the temporal locality of posts with respect to important events, either of foreseeable or unforeseeable nature, makes applica-…
Picture It In Your Mind: Generating High Level Visual Representations From Textual Descriptions
Fabio Carrara, Andrea Esuli, Tiziano Fagni +2
In this paper we tackle the problem of image search when the query is a short textual description of the image the user is looking for. We choose to implement the actual search pro…
Sentiment-enhanced Multidimensional Analysis of Online Social Networks: Perception of the Mediterranean Refugees Crisis
Mauro Coletto, Claudio Lucchese, Cristina Ioana Muntean +4
We propose an analytical framework able to investigate discussions about polarized topics in online social networks from many different angles. The framework supports the analysis…
Utility-Theoretic Ranking for Semi-Automated Text Classification
Giacomo Berardi, Andrea Esuli, Fabrizio Sebastiani
\emph{Semi-Automated Text Classification} (SATC) may be defined as the task of ranking a set of automatically labelled textual documents in such a way that, if a huma…
Optimizing Text Quantifiers for Multivariate Loss Functions
Andrea Esuli, Fabrizio Sebastiani
We address the problem of \emph{quantification}, a supervised learning task whose goal is, given a class, to estimate the relative frequency (or \emph{prevalence}) of the class in…