Tesista sobre un tema social interesante en un proyecto de investigacion!
Nov 1, 2024

Multicultural Bias Recognition to Detect and Mitigate Racism, Xenophobia and Geographic Inequalities in Multilingual Large Language Models.
Oct 26, 2024

Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis.
Aug 15, 2024

Findings of the shared task on Empathy, Personality, and Emotion Detection from the WASSA workshop @ ACL.
Jul 1, 2024

We've created the Touché23-ValueEval dataset, a large collection of over 9,300 arguments annotated with 54 human values, to help develop methods for analyzing the values that make arguments persuasive. Our dataset, which more than doubles the size of its predecessor, has already been used to achieve state-of-the-art results in identifying human values behind arguments, and has shown promising performance with large language models like Llama-2-7B.
May 1, 2024

Current bias detection methods in machine learning have their own biases and limitations, so we've developed a new approach that directly tests fine-tuned classifiers on real-world data to identify potential biases. Our method, which involves creating counterfactual examples by modifying named entities in target data, revealed significant biases in multilingual models, including sentiment analysis and stance recognition models, and shed light on the complex interactions between names, languages, and model predictions. Current models tend to prefer names from the countries speaking the language of the sentence, impulsing for the name IA Xenophobia.
May 1, 2024

A technique for explanability in LLM, allowing to break a complex task into subtasks formulated as binary questions in natural language, and represent any samples using the output of a binary classifier on these subtasks.
Dec 1, 2023

Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis.
Jul 14, 2023

Findings of the shared task on Empathy, Personality, and Emotion Detection from the WASSA workshop @ ACL.
Jul 1, 2023

We've developed a machine learning approach to automatically recognize the opinions of citizens in online public consultations, using three datasets to train a model that can classify stances on various topics. Our work experiments with different methods, including self-supervised learning, and makes several annotated datasets available for others to use. This work was used in the Touché shared task of CLEF 2023.
Apr 1, 2023