jobhop-e3112556·2 events·first seen Aliases: JobHop, JobHop v2
Researchers release JobHop v2, a dataset of 355,315 career trajectories extracted from ~440,000 pseudonymized multilingual resumes provided by VDAB, the Flemish Public Employment Service. The extraction pipeline uses reasoning-controlled LLM inference with a retry mechanism achieving 100% JSON parse rate, annotating trajectories with ESCO occupational codes, temporal information, and education attainment. The work addresses a gap in publicly available, authentic (non-synthesized) career trajectory data for workforce planning and labour market analysis. Dataset and code are publicly released.
Researchers introduce STEP (Sequential Trajectory of Employment Prediction), a career-path recommendation system that extracts structured trajectory data from unstructured resumes using LLMs and models it with a time-decay GRU, FiLM conditioning on educational attainment, and attention-based pooling. They also introduce ROUTE, a two-stage contrastive pretraining procedure for multilingual occupation embeddings. STEP is evaluated on four career-trajectory datasets including an improved version of the public JobHop dataset, outperforming prior baselines on next-job prediction. Code and data are publicly released.