AI Research at TechWolf

On top of adopting the latest advancements in AI, TechWolf actively drives innovation through focused research efforts. Our research pushes the state-of-the-art in skills technology in collaboration with respected institutions like the University of Cambridge and Ghent University. In line with our transparency principle, we are actively engaged in the academic community. We do this by publishing a selection of our research, making this work accessible to others and showing that it meets the standards set by international, peer-reviewed venues. Below, we provide an overview of recent publications.

Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder and Thomas Demeester. "Career Path Prediction using Resume Representation Learning and Skill-based Matching" International workshop on Recommender Systems for Human Resources (RecSys in HR) as part of RecSys 2023.

Jens-Joris Decorte, Severine Verlinden, Jeroen Van Hautte, Johannes Deleu, Chris Develder and Thomas Demeester. "Extreme Multi-Label Skill Extraction Training using Large Language Models" International workshop on AI for Human Resources and Public Employment Services (AI4HR&PES) as part of ECML-PKDD 2023.

Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder and Thomas Demeester. "Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction" International workshop on Recommender Systems for Human Resources (RecSys in HR) as part of RecSys 2022.

Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester, and Chris Develder. "JobBERT: Understanding Job Titles through Skills." International workshop on Fair, Effective And Sustainable Talent management using data science (FEAST) as part of ECML-PKDD 2021.

Van Hautte, Jeroen, Vincent Schelstraete, and Mikaël Wornoo. "Leveraging the Inherent Hierarchy of Vacancy Titles for Automated Job Ontology Expansion." Proceedings of the 6th International Workshop on Computational Terminology (2020).

Van Hautte, Jeroen, Guy Emerson, and Marek Rei. "Bad Form: Comparing Context-Based and Form-Based Few-Shot Learning in Distributional Semantic Models. Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019).