6 papers
Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs
David Hartmann, Lena Pohlmann, Lelia Hanslik +3
Large Language Models (LLMs) exhibit systematic biases across demographic groups. Auditing is proposed as an accountability tool for black-box LLM applications, but suffers from re…
ProbLog4Fairness: A Neurosymbolic Approach to Modeling and Mitigating Bias
Rik Adriaensen, Lucas Van Praet, Jessa Bekker +3
Operationalizing definitions of fairness is difficult in practice, as multiple definitions can be incompatible while each being arguably desirable. Instead, it may be easier to dir…
ChocoLlama: Lessons Learned From Teaching Llamas Dutch
Matthieu Meeus, Anthony Rathé, François Remy +3
While Large Language Models (LLMs) have shown remarkable capabilities in natural language understanding and generation, their performance often lags in lower-resource, non-English…
Trans-Tokenization and Cross-lingual Vocabulary Transfers: Language Adaptation of LLMs for Low-Resource NLP
François Remy, Pieter Delobelle, Hayastan Avetisyan +3
The development of monolingual language models for low and mid-resource languages continues to be hindered by the difficulty in sourcing high-quality training data. In this study,…
OneLove beyond the field -- A few-shot pipeline for topic and sentiment analysis during the FIFA World Cup in Qatar
Christoph Rauchegger, Sonja Mei Wang, Pieter Delobelle
The FIFA World Cup in Qatar was discussed extensively in the news and on social media. Due to news reports with allegations of human rights violations, there were calls to boycott…
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
Xavier Suau, Pieter Delobelle, Katherine Metcalf +4
An important issue with Large Language Models (LLMs) is their undesired ability to generate toxic language. In this work, we show that the neurons responsible for toxicity can be d…