45 citations · 134 across the 21 of their papers we have counts for
23 papers
LLM Persuasion Is in the Eye of the Evaluation
Kamile Dementaviciute, Julija Vaitonyte, Tijl De Bie
Large language models (LLMs) have already been shown to match or exceed human experts in persuasion. While their persuasive capabilities hold promise for beneficial uses such as ed…
People Are Not Just Their Countries. Disentangling Social Determinants of LLM Value Alignment Across Europe
Maria-Louisa Wightman, Guillaume Bied, Tijl De Bie
As Large Language Models (LLMs) are increasingly used as a primary source of information and advice, understanding their alignment to humans in terms of values becomes a pressing c…
Grokipedia vs Wikipedia: An LLM-Based Audit of Political Neutrality along Ideologies
Filippos Vlahos, Guillaume Bied, Tijl De Bie
Online encyclopedias shape political opinion and, through it, democratic discourse. In late 2025, Grokipedia was released, an encyclopedia written entirely by the LLM Grok. One mot…
STEP: Career-Path Recommendation via Temporal and Educational Trajectory Modeling
Iman Johary, Guillaume Bied, Alexandru C. Mara +1
Career paths encode decades of skill acquisition, role transitions, and educational investment, and understanding them at scale underpins workforce planning, labor market policy, a…
JobHop v2: A Large-Scale Career Trajectory Dataset from Unstructured Resumes
Iman Johary, Guillaume Bied, Alexandru C. Mara +1
Large-scale, richly annotated career trajectory data underpins workforce planning, job recommendation, and labour market analysis, yet publicly available datasets are either small,…
TopoLedgerBERT: Topological Learning of Ledger Description Embeddings using Siamese BERT-Networks
Sander Noels, Sébastien Viaene, Tijl De Bie
This paper addresses a long-standing problem in the field of accounting: mapping company-specific ledger accounts to a standardized chart of accounts. We propose a novel solution,…
Content-Agnostic Moderation for Stance-Neutral Recommendation
Nan Li, Bo Kang, Tijl De Bie
Personalized recommendation systems often drive users towards more extreme content, exacerbating opinion polarization. While (content-aware) moderation has been proposed to mitigat…
Gaussian Embedding of Temporal Networks
Raphaël Romero, Jefrey Lijffijt, Riccardo Rastelli +2
Representing the nodes of continuous-time temporal graphs in a low-dimensional latent space has wide-ranging applications, from prediction to visualization. Yet, analyzing continuo…
Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms
Raphaël Romero, Maarten Buyl, Tijl De Bie +1
Dynamic Link Prediction (DLP) addresses the prediction of future links in evolving networks. However, accurately portraying the performance of DLP algorithms poses challenges that…
KamerRaad: Enhancing Information Retrieval in Belgian National Politics through Hierarchical Summarization and Conversational Interfaces
Alexander Rogiers, Maarten Buyl, Bo Kang +1
KamerRaad is an AI tool that leverages large language models to help citizens interactively engage with Belgian political information. The tool extracts and concisely summarizes ke…
fairret: a Framework for Differentiable Fairness Regularization Terms
Maarten Buyl, MaryBeth Defrance, Tijl De Bie
Current fairness toolkits in machine learning only admit a limited range of fairness definitions and have seen little integration with automatic differentiation libraries, despite…
Maximal Fairness
MaryBeth Defrance, Tijl De Bie
Fairness in AI has garnered quite some attention in research, and increasingly also in society. The so-called "Impossibility Theorem" has been one of the more striking research res…
SkillGPT: a RESTful API service for skill extraction and standardization using a Large Language Model
Nan Li, Bo Kang, Tijl De Bie
We present SkillGPT, a tool for skill extraction and standardization (SES) from free-style job descriptions and user profiles with an open-source Large Language Model (LLM) as back…
Inherent Limitations of AI Fairness
Maarten Buyl, Tijl De Bie
As the real-world impact of Artificial Intelligence (AI) systems has been steadily growing, so too have these systems come under increasing scrutiny. In response, the study of AI f…
Optimal Transport of Classifiers to Fairness
Maarten Buyl, Tijl De Bie
In past work on fairness in machine learning, the focus has been on forcing the prediction of classifiers to have similar statistical properties for people of different demographic…
An Earth Mover's Distance Based Graph Distance Metric For Financial Statements
Sander Noels, Benjamin Vandermarliere, Ken Bastiaensen +1
Quantifying the similarity between a group of companies has proven to be useful for several purposes, including company benchmarking, fraud detection, and searching for investment…
The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?
Robin Vandaele, Bo Kang, Tijl De Bie +1
Distances between data points are widely used in machine learning applications. Yet, when corrupted by noise, these distances -- and thus the models based upon them -- may lose the…
Automating Data Science: Prospects and Challenges
Tijl De Bie, Luc De Raedt, José Hernández-Orallo +3
Given the complexity of typical data science projects and the associated demand for human expertise, automation has the potential to transform the data science process. Key insight…
DeBayes: a Bayesian Method for Debiasing Network Embeddings
Maarten Buyl, Tijl De Bie
As machine learning algorithms are increasingly deployed for high-impact automated decision making, ethical and increasingly also legal standards demand that they treat all individ…
From acquaintance to best friend forever: robust and fine-grained inference of social tie strengths
Florian Adriaens, Tijl De Bie, Aristides Gionis +2
Social networks often provide only a binary perspective on social ties: two individuals are either connected or not. While sometimes external information can be used to infer the s…
Interesting Multi-Relational Patterns
Eirini Spyropoulou, Tijl De Bie
Mining patterns from multi-relational data is a problem attracting increasing interest within the data mining community. Traditional data mining approaches are typically developed…
Maximum entropy models and subjective interestingness: an application to tiles in binary databases
Tijl De Bie
Recent research has highlighted the practical benefits of subjective interestingness measures, which quantify the novelty or unexpectedness of a pattern when contrasted with any pr…
Reconstruction of Causal Networks by Set Covering
Nick Fyson, Tijl De Bie, Nello Cristianini
We present a method for the reconstruction of networks, based on the order of nodes visited by a stochastic branching process. Our algorithm reconstructs a network of minimal size…