22 citations · 47 across the 6 of their papers we have counts for
8 papers
RobBERT-2022: Updating a Dutch Language Model to Account for Evolving Language Use
Pieter Delobelle, Thomas Winters, Bettina Berendt
Large transformer-based language models, e.g. BERT and GPT-3, outperform previous architectures on most natural language processing tasks. Such language models are first pre-traine…
RobBERTje: a Distilled Dutch BERT Model
Pieter Delobelle, Thomas Winters, Bettina Berendt
Pre-trained large-scale language models such as BERT have gained a lot of attention thanks to their outstanding performance on a wide range of natural language tasks. However, due…
Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
Kristen Scott, Pieter Delobelle, Bettina Berendt
We classify seven months' worth of Belgian COVID-related Tweets using multilingual BERT and relate them to their governments' COVID measures. We classify Tweets by their stated opi…
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning
Pieter Delobelle, Paul Temple, Gilles Perrouin +3
Machine learning is being integrated into a growing number of critical systems with far-reaching impacts on society. Unexpected behaviour and unfair decision processes are coming u…
Bias in Data-driven AI Systems -- An Introductory Survey
Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju +20
AI-based systems are widely employed nowadays to make decisions that have far-reaching impacts on individuals and society. Their decisions might affect everyone, everywhere and any…
RobBERT: a Dutch RoBERTa-based Language Model
Pieter Delobelle, Thomas Winters, Bettina Berendt
Pre-trained language models have been dominating the field of natural language processing in recent years, and have led to significant performance gains for various complex natural…