Publications

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, …

The maturity level of language models is now at a stage in which many companies rely on them to solve various tasks. However, while …

Current language technology is ubiquitous and directly influences individuals' lives worldwide. Given the recent trend in AI on …

Transformer-based Natural Language Processing models have become the standard for hate speech detection. However, the unconscious use …

Natural Language Processing (NLP) models risk overfitting to specific terms in the training data, thereby reducing their performance, …

Meaning is context-dependent, but many properties of language (should) remain the same even if we transform the context. For example, …

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 …

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 …