6 papers
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,…
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…
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…