mlsanityData to 7 Oct 2026

JobBERT: Understanding Job Titles through Skills

arXiv 2109.09605 ↗First posted 20 Sep 2021cs.CLcited by 29

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Abstract (arXiv)

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 internal HR departments use them to organize and structure many of their processes. As job titles are a compact, convenient, and readily available data source, modeling them with high accuracy can greatly benefit many HR tech applications. In this paper, we propose a neural representation model for job titles, by augmenting a pre-trained language model with co-occurrence information from skill labels extracted from vacancies. Our JobBERT method leads to considerable improvements compared to using generic sentence encoders, for the task of job title normalization, for which we release a new evaluation benchmark.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 8 of its 18 references that are in the map. First posted on arXiv 20 Sep 2021.

Builds on

8 of 18 references.

References · 8

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  3. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
  4. 2016Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translationcited by 1,471
  5. 2016Bag of Tricks for Efficient Text Classificationcited by 869
  6. 2018Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondcited by 434
  7. 2016FastText.zip: Compressing text classification modelscited by 331
  8. 2020Leveraging the Inherent Hierarchy of Vacancy Titles for Automated Job Ontology Expansioncited by 2

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Citing papers per year: 2022: 3; 2023: 4; 2024: 5; 2025: 9; 2026: 8.

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  1. 2023Are Emily and Greg Still More Employable than Lakisha and Jamal? Investigating Algorithmic Hiring Bias in the Era of ChatGPTcited by 23
  2. 2022Design of Negative Sampling Strategies for Distantly Supervised Skill Extractioncited by 16
  3. 2023ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domaincited by 14
  4. 2023Large Language Models as Batteries-Included Zero-Shot ESCO Skills Matcherscited by 14
  5. 2022Learning Job Titles Similarity from Noisy Skill Labelscited by 12
  6. 2024HR-MultiWOZ: A Task Oriented Dialogue (TOD) Dataset for HR LLM Agentcited by 12
  7. 2024Natural Language Processing for Human Resources: A Surveycited by 9
  8. 2023VacancySBERT: the approach for representation of titles and skills for semantic similarity search in the recruitment domaincited by 7
  9. 2024MELO: An Evaluation Benchmark for Multilingual Entity Linking of Occupationscited by 6
  10. 2025CareerBERT: Matching Resumes to ESCO Jobs in a Shared Embedding Space for Generic Job Recommendationscited by 5
  11. 2025Efficient Text Encoders for Labor Market Analysiscited by 5
  12. 2024Learning Job Title Representation from Job Description Aggregation Networkcited by 3
17 more
  1. 2025Overview of the TalentCLEF 2025: Skill and Job Title Intelligence for Human Capital Managementcited by 3
  2. 2022Is it Required? Ranking the Skills Required for a Job-Titlecited by 2
  3. 2025Synthetic CVs To Build and Test Fairness-Aware Hiring Toolscited by 2
  4. 2025Measuring Gender Bias in Job Title Matching for Grammatical Gender Languagescited by 2
  5. 2024Course Recommender Systems Need to Consider the Job Marketcited by 1
  6. 2025Unified Work Embeddings: Contrastive Learning of a Bidirectional Multi-task Rankercited by 1
  7. 2026Noise-Aware Named Entity Recognition for Historical VET Documentscited by 1
  8. 2026WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domaincited by 1
  9. 2025NLPnorth @ TalentCLEF 2025: Comparing Discriminative, Contrastive, and Prompt-Based Methods for Job Title and Skill Matchingcited by 0
  10. 2025Ontology-Aligned Embeddings for Data-Driven Labour Market Analyticscited by 0
  11. 2025Towards Explainable Job Title Matching: Leveraging Semantic Textual Relatedness and Knowledge Graphscited by 0
  12. 2026Contrastive Bi-Encoder Models for Multi-Label Skill Extraction: Enhancing ESCO Ontology Matching with BERT and Attention Mechanismscited by 0
  13. 2026Overview of the TalentCLEF 2026: Skill and Job Title Intelligence for Human Capital Managementcited by 0
  14. 2026TalentCLEF at CLEF2026: Skill and Job Title Intelligence for Human Capital Managementcited by 0
  15. 2026Two-Step Occupation Codingcited by 0
  16. 2026Unified Semantic Modeling Framework for Large-Scale Job Understanding at LinkedIncited by 0
  17. 2026An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generationcited by 0