23 citations · 30 across the 11 of their papers we have counts for
13 papers
LLMs Underperform Graph-Based Parsers on Supervised Relation Extraction for Complex Graphs
Paolo Gajo, Domenic Rosati, Hassan Sajjad +1
Relation extraction represents a fundamental component in the process of creating knowledge graphs, among other applications. Large language models (LLMs) have been adopted as a pr…
Dependency Parsing is More Parameter-Efficient with Normalization
Paolo Gajo, Domenic Rosati, Hassan Sajjad +1
Dependency parsing is the task of inferring natural language structure, often approached by modeling word interactions via attention through biaffine scoring. This mechanism works…
Hate Speech According to the Law: An Analysis for Effective Detection
Katerina Korre, John Pavlopoulos, Paolo Gajo +1
The issue of hate speech extends beyond the confines of the online realm. It is a problem with real-life repercussions, prompting most nations to formulate legal frameworks that cl…
Untangling Hate Speech Definitions: A Semantic Componential Analysis Across Cultures and Domains
Katerina Korre, Arianna Muti, Federico Ruggeri +1
Hate speech relies heavily on cultural influences, leading to varying individual interpretations. For that reason, we propose a Semantic Componential Analysis (SCA) framework for a…
Language is Scary when Over-Analyzed: Unpacking Implied Misogynistic Reasoning with Argumentation Theory-Driven Prompts
Arianna Muti, Federico Ruggeri, Khalid Al-Khatib +2
We propose misogyny detection as an Argumentative Reasoning task and we investigate the capacity of large language models (LLMs) to understand the implicit reasoning used to convey…
QueerBench: Quantifying Discrimination in Language Models Toward Queer Identities
Mae Sosto, Alberto Barrón-Cedeño
With the increasing role of Natural Language Processing (NLP) in various applications, challenges concerning bias and stereotype perpetuation are accentuated, which often leads to…
Let Guidelines Guide You: A Prescriptive Guideline-Centered Data Annotation Methodology
Federico Ruggeri, Eleonora Misino, Arianna Muti +3
We introduce the Guideline-Centered Annotation Methodology (GCAM), a novel data annotation methodology designed to report the annotation guidelines associated with each data sample…
PejorativITy: Disambiguating Pejorative Epithets to Improve Misogyny Detection in Italian Tweets
Arianna Muti, Federico Ruggeri, Cagri Toraman +6
Misogyny is often expressed through figurative language. Some neutral words can assume a negative connotation when functioning as pejorative epithets. Disambiguating the meaning of…
A Corpus for Sentence-level Subjectivity Detection on English News Articles
Francesco Antici, Andrea Galassi, Federico Ruggeri +5
We develop novel annotation guidelines for sentence-level subjectivity detection, which are not limited to language-specific cues. We use our guidelines to collect NewsSD-ENG, a co…
Automated Fact-Checking for Assisting Human Fact-Checkers
Preslav Nakov, David Corney, Maram Hasanain +6
The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism. Nowadays, politicians an…
SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
G. Da San Martino, A. Barrón-Cedeño, H. Wachsmuth +2
We present the results and the main findings of SemEval-2020 Task 11 on Detection of Propaganda Techniques in News Articles. The task featured two subtasks. Subtask SI is about Spa…
Prta: A System to Support the Analysis of Propaganda Techniques in the News
Giovanni Da San Martino, Shaden Shaar, Yifan Zhang +3
Recent events, such as the 2016 US Presidential Campaign, Brexit and the COVID-19 "infodemic", have brought into the spotlight the dangers of online disinformation. There has been…
A Context-Aware Approach for Detecting Check-Worthy Claims in Political Debates
Pepa Gencheva, Ivan Koychev, Lluís Màrquez +2
In the context of investigative journalism, we address the problem of automatically identifying which claims in a given document are most worthy and should be prioritized for fact-…