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Alberto Barrón-Cedeño

10 accepted papers

2025

Dependency Parsing is More Parameter-Efficient with Normalization

NeurIPS 2025poster

Dependency parsing is the task of inferring natural language structure, often approached by modeling word interactions via attention through biaffine scoring. This mechanism works like self-attention in Transformers, where scores are calculated for every pair of words in a sentence. However, unlike…

Cited by 0SourcecodeScholar
2025

Untangling Hate Speech Definitions: A Semantic Componential Analysis Across Cultures and Domains

NAACL 2025findings

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 cross-cultural and cross-domain analysis of hate speech definitions. We create the first dataset of hate speech definit…

Cited by 1SourcePDFScholar
2024

A Corpus for Sentence-Level Subjectivity Detection on English News Articles

COLING 2024main

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 corpus of 638 objective and 411 subjective sentences extracted from English news articles on controversial topics. Our cor…

2024

Language is Scary when Over-Analyzed: Unpacking Implied Misogynistic Reasoning with Argumentation Theory-Driven Prompts

EMNLP 2024main

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 misogyny in both Italian and English. The central aim is to generate the missing reasoning link between a message and t…

Cited by 0SourcePDFScholar
2024

PejorativITy: Disambiguating Pejorative Epithets to Improve Misogyny Detection in Italian Tweets

COLING 2024main

Misogyny is often expressed through figurative language. Some neutral words can assume a negative connotation when functioning as pejorative epithets. Disambiguating the meaning of such terms might help the detection of misogyny. In order to address such task, we present PejorativITy, a novel corpus…

2024

The Challenges of Creating a Parallel Multilingual Hate Speech Corpus: An Exploration

COLING 2024main

Hate speech is infamously one of the most demanding topics in Natural Language Processing, as its multifacetedness is accompanied by a handful of challenges, such as multilinguality and cross-linguality. Hate speech has a subjective aspect that intensifies when referring to different cultures and di…

Cited by 5SourcePDFScholar
2022

The (Undesired) Attenuation of Human Biases by Multilinguality

EMNLP 2022main

Some human preferences are universal. The odor of vanilla is perceived as pleasant all around the world. We expect neural models trained on human texts to exhibit these kind of preferences, i.e. biases, but we show that this is not always the case. We explore 16 static and contextual embedding model…

2021

Automated Fact-Checking for Assisting Human Fact-Checkers

IJCAI 2021poster

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 and other key players enjoy direct access to their audiences through social media, bypassing the filters of official cable…

Cited by 281SourcePDFScholar
2020

A Survey on Computational Propaganda Detection

IJCAI 2020poster

Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda. They exploit the anonymity of the Internet, the micro-profiling ability of social networks, and the ease of automatically creating and managing coordinated networks of accounts, to reach million…

Cited by 0SourcePDFScholar