Publications

As 3rd-person pronoun usage shifts to include novel forms, e.g., neopronouns, we need more research on identity-inclusive NLP. …

Work on hate speech has made considering rude and harmful examples in scientific publications inevitable. This situation raises various …

Hate speech detection faces two significant challenges: 1) the limited availability of labeled data and 2) the high variability of hate …

We present the system proposed by the MilaNLP team for the Explainable Detection of Online Sexism (EDOS) shared task. We propose an …

In recent years, joint Vision-Language (VL) models have increased in popularity and capability. Very few studies have attempted to …

We present a cross-lingual study of homotransphobia on Twitter, examining the prevalence and forms of homotransphobic content in tweets …

Machine learning models are now able to convert user-written text descriptions into naturalistic images. These models are available to …

As Transformers are increasingly relied upon to solve complex NLP problems, there is an increased need for their decisions to be …

Scandinavian countries are perceived as role-models when it comes to gender equality. With the advent of pre-trained language models …

Machine learning models are now able to convert user-written text descriptions into naturalistic images. These models are available to …

Hate speech is a global phenomenon, but most hate speech datasets so far focus on English-language content. This hinders the …

Work on hate speech has made the consideration of rude and harmful examples in scientific publications inevitable. This raises various …

Language is constantly changing and evolving, leaving language models to quickly become outdated, both factually and linguistically. …

Many interpretability tools allow practitioners and researchers to explain Natural Language Processing systems. However, each tool …

Hate speech detection models are typically evaluated on held-out test sets. However, this risks painting an incomplete and potentially …

Online hate speech is a dangerous phenomenon that can (and should) be promptly counteracted properly. While Natural Language Processing …

In this paper, we describe the system proposed by the MilaNLP team for the Multimedia Automatic Misogyny Identification (MAMI) …

Detecting emotion in text allows social and computational scientists to study how people behave and react to online events. However, …

Reducing and counter-acting hate speech on Social Media is a significant concern. Most of the proposed automatic methods are conducted …

The task of Named Entity Recognition (NER) is aimed at identifying named entities in a given text and classifying them into pre-defined …

Language models have revolutionized the field of NLP. However, language models capture and proliferate hurtful stereotypes, especially …

The paper describes the MilaNLP team’s submission (Bocconi University, Milan) in the WASSA 2021 Shared Task on Empathy Detection and …

Sentiment analysis is a common task to understand people’s reactions online. Still, we often need more nuanced information: is …

We introduce a novel topic modeling method that can make use of contextulized embeddings (e.g., BERT) to do zero-shot cross-lingual …

Automatic Misogyny Identification (AMI) is a shared task proposed at the Evalita 2020 evaluation campaign. The AMI challenge, based on …

Topic models have been widely used to discover hidden topics in a collection of documents. In this paper, we propose to investigate the …

Hate speech may take different forms in online social environments. In this paper, we address the problem of automatic detection of …

Recently, Natural Language Processing (NLP) has witnessed an impressive progress in many areas, due to the advent of novel, pretrained …

In this paper we deal with complex attributed graphs which can exhibit rich connectivity patterns and whose nodes are often associated …

During the last years, the phenomenon of hate against women increased exponentially especially in online environments such as …

The huge amount of textual user-generated content on the Web has incredibly grown in the last decade, creating new relevant …

The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in …

Automatic Misogyny Identification (AMI) is a new shared task proposed for the first time at the Evalita 2018 evaluation campaign. The …

Mapping natural language terms to a Web knowledge base enriches information systems without additional context, with new relations and …

This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian tweets …

Knowledge Graphs (KG) are widely used abstractions to represent entity-centric knowledge. Approaches to embed entities, entity types …

Given the potential rise in the amount of user-generated content on social network, research efforts towards Information Extraction …

In the recent years, the amount of user generated contents shared on the Web has significantly increased, especially in social media …

Numerous state-of-the-art Named Entity Recognition (NER) systems use different classification schemas/ontologies. Comparisons and …

Sentiment Analysis is a broad task that involves the analysis of various aspect of the natural language text. However, most of the …

The automatic detection of figurative language, such as irony and sarcasm, is one of the most challenging tasks of Natural Language …

Real world applications of machine learning in natural language processing can span many different domains and usually require a huge …

The growing availability of social media platforms, in particular microblogs such as Twitter, opened new way to people for expressing …