> ## Documentation Index > Fetch the complete documentation index at: https://developers.techwolf.ai/llms.txt > Use this file to discover all available pages before exploring further. # AI Research 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. *** Luis Gasco, Hermenegildo Fabregat, Laura García-Sardiña, Paula Estrella, Warre Veys, Casimiro Pío Carrino, Matthias De Lange, Daniel Deniz Cerpa, Álvaro Rodrigo, Jens-Joris Decorte and Rabih Zbib. "Overview of the TalentCLEF 2026: Skill and Job Title Intelligence for Human Capital Management" Conference and Labs of the Evaluation Forum (CLEF) 2026. *** Matthias De Lange, Warre Veys, Federico Retyk et al., including Jens-Joris Decorte and Jeroen Van Hautte. "WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain" Preprint, arXiv:2604.13055 (2026). *** Matthias De Lange, Jens-Joris Decorte and Jeroen Van Hautte. "Unified Work Embeddings: Contrastive Learning of a Bidirectional Multi-task Ranker" Preprint, arXiv:2511.07969 (2025). *** Jens-Joris Decorte, Matthias De Lange and Jeroen Van Hautte. "Multilingual JobBERT for Cross-Lingual Job Title Matching" CLEF 2025 Working Notes, CEUR Workshop Proceedings Vol. 4038, pages 4428–4437. *** Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder and Thomas Demeester. "Efficient Text Encoders for Labor Market Analysis" IEEE Access, vol. 13, pages 133596–133608 (2025). *** Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder and Thomas Demeester. "On the Biased Assessment of Expert Finding Systems" International workshop on Recommender Systems for Human Resources (RecSys in HR) as part of RecSys 2024. *** Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester and Chris Develder. "SkillMatch: Evaluating Self-supervised Learning of Skill Relatedness" International workshop on AI for Human Resources and Public Employment Services (AI4HR\&PES) as part of ECML-PKDD 2024. *** 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). ## This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.