450 citations · 653 across the 56 of their papers we have counts for
19 papers · 1 filter
The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data
Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey +4
Recent advances in generative models facilitate the creation of synthetic data to be made available for research in privacy-sensitive contexts. However, the analysis of synthetic d…
Exploring the Temperature-Dependent Phase Transition in Modern Hopfield Networks
Felix Koulischer, Cédric Goemaere, Tom van der Meersch +2
The recent discovery of a connection between Transformers and Modern Hopfield Networks (MHNs) has reignited the study of neural networks from a physical energy-based perspective. T…
BioLORD-2023: Semantic Textual Representations Fusing LLM and Clinical Knowledge Graph Insights
François Remy, Kris Demuynck, Thomas Demeester
In this study, we investigate the potential of Large Language Models to complement biomedical knowledge graphs in the training of semantic models for the biomedical and clinical do…
Training a Hopfield Variational Autoencoder with Equilibrium Propagation
Tom Van Der Meersch, Johannes Deleu, Thomas Demeester
On dedicated analog hardware, equilibrium propagation is an energy-efficient alternative to backpropagation. In spite of its theoretical guarantees, its application in the AI domai…
Flexible Model Interpretability through Natural Language Model Editing
Karel D'Oosterlinck, Thomas Demeester, Chris Develder +1
Model interpretability and model editing are crucial goals in the age of large language models. Interestingly, there exists a link between these two goals: if a method is able to s…
Zero-Shot Cross-Lingual Sentiment Classification under Distribution Shift: an Exploratory Study
Maarten De Raedt, Semere Kiros Bitew, Fréderic Godin +2
The brittleness of finetuned language model performance on out-of-distribution (OOD) test samples in unseen domains has been well-studied for English, yet is unexplored for multi-l…