6 citations · 21 across the 12 of their papers we have counts for
12 papers
WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain
Matthias De Lange, Warre Veys, Federico Retyk +16
Today's evolving labor markets rely increasingly on recommender systems for hiring, talent management, and workforce analytics, with natural language processing (NLP) capabilities…
Unified Work Embeddings: Contrastive Learning of a Bidirectional Multi-task Ranker
Matthias De Lange, Jens-Joris Decorte, Jeroen Van Hautte
Applications in labor market intelligence demand specialized NLP systems for a wide range of tasks, characterized by extreme multi-label target spaces, strict latency constraints,…
Multilingual JobBERT for Cross-Lingual Job Title Matching
Jens-Joris Decorte, Matthias De Lange, Jeroen Van Hautte
We introduce JobBERT-V3, a contrastive learning-based model for cross-lingual job title matching. Building on the state-of-the-art monolingual JobBERT-V2, our approach extends supp…
Efficient Text Encoders for Labor Market Analysis
Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder +1
Labor market analysis relies on extracting insights from job advertisements, which provide valuable yet unstructured information on job titles and corresponding skill requirements.…
On the Biased Assessment of Expert Finding Systems
Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder +1
In large organisations, identifying experts on a given topic is crucial in leveraging the internal knowledge spread across teams and departments. So-called enterprise expert retrie…
SkillMatch: Evaluating Self-supervised Learning of Skill Relatedness
Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester +1
Accurately modeling the relationships between skills is a crucial part of human resources processes such as recruitment and employee development. Yet, no benchmarks exist to evalua…
Career Path Prediction using Resume Representation Learning and Skill-based Matching
Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu +2
The impact of person-job fit on job satisfaction and performance is widely acknowledged, which highlights the importance of providing workers with next steps at the right time in t…
Extreme Multi-Label Skill Extraction Training using Large Language Models
Jens-Joris Decorte, Severine Verlinden, Jeroen Van Hautte +3
Online job ads serve as a valuable source of information for skill requirements, playing a crucial role in labor market analysis and e-recruitment processes. Since such ads are typ…
Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction
Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu +2
Skills play a central role in the job market and many human resources (HR) processes. In the wake of other digital experiences, today's online job market has candidates expecting t…
JobBERT: Understanding Job Titles through Skills
Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester +1
Job titles form a cornerstone of today's human resources (HR) processes. Within online recruitment, they allow candidates to understand the contents of a vacancy at a glance, while…
Leveraging the Inherent Hierarchy of Vacancy Titles for Automated Job Ontology Expansion
Jeroen Van Hautte, Vincent Schelstraete, Mikaël Wornoo
Machine learning plays an ever-bigger part in online recruitment, powering intelligent matchmaking and job recommendations across many of the world's largest job platforms. However…
Bad Form: Comparing Context-Based and Form-Based Few-Shot Learning in Distributional Semantic Models
Jeroen Van Hautte, Guy Emerson, Marek Rei
Word embeddings are an essential component in a wide range of natural language processing applications. However, distributional semantic models are known to struggle when only a sm…