# UniSkill: A Dataset for Matching University Curricula to Professional Competencies

arXiv: https://arxiv.org/abs/2603.03134 · HTML: https://mlsanity.com/paper/2603.03134/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 39 references that are in the map.
- First posted on arXiv 3 Mar 2026.

## Builds on (most cited first, 13 of 13)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Extreme Multi-Label Skill Extraction Training using Large Language Models](https://mlsanity.com/paper/2307.10778/) (2023)
- [ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domain](https://mlsanity.com/paper/2305.12092/) (2023)
- [Deep Learning-based Computational Job Market Analysis: A Survey on Skill Extraction and Classification from Job Postings](https://mlsanity.com/paper/2402.05617/) (2024)
- [conSultantBERT: Fine-tuned Siamese Sentence-BERT for Matching Jobs and Job Seekers](https://mlsanity.com/paper/2109.06501/) (2021)
- [VacancySBERT: the approach for representation of titles and skills for semantic similarity search in the recruitment domain](https://mlsanity.com/paper/2307.16638/) (2023)
- [Entity Linking in the Job Market Domain](https://mlsanity.com/paper/2401.17979/) (2024)
- [Multilingual JobBERT for Cross-Lingual Job Title Matching](https://mlsanity.com/paper/2507.21609/) (2025)
- [From Course to Skill: Evaluating LLM Performance in Curricular Analytics](https://mlsanity.com/paper/2505.02324/) (2025)
- [Course-Skill Atlas: A national longitudinal dataset of skills taught in U.S. higher education curricula](https://mlsanity.com/paper/2404.13163/) (2024)
- [SkillRec: A Data-Driven Approach to Job Skill Recommendation for Career Insights](https://mlsanity.com/paper/2302.09938/) (2023)
- [Hierarchical Classification of Transversal Skills in Job Ads Based on Sentence Embeddings](https://mlsanity.com/paper/2401.05073/) (2024)
- [Quantifying the influence of Vocational Education and Training with text embedding and similarity-based networks](https://mlsanity.com/paper/2503.17931/) (2025)

## Abstract (arXiv)

Skill extraction and recommendation systems have been studied from recruiter, applicant, and education perspectives. While AI applications in job advertisements have received broad attention, deficiencies in the instructed skills side remain a challenge. In this work, we address the scarcity of publicly available datasets by releasing both manually annotated and synthetic datasets of skills from the European Skills, Competences, Qualifications and Occupations (ESCO) taxonomy and university course pairs and publishing corresponding annotation guidelines. Specifically, we match graduate-level university courses with skills from the Systems Analysts and Management and Organization Analyst ESCO occupation groups at two granularities: course title with a skill, and course sentence with a skill. We train language models on this dataset to serve as a baseline for retrieval and recommendation systems for course-to-skill and skill-to-course matching. We evaluate the models on a portion of the annotated data. Our BERT model achieves 87% F1-score, showing that course and skill matching is a feasible task.