2 citations · 6 across the 17 of their papers we have counts for
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KARRIEREWEGE: A Large Scale Career Path Prediction Dataset
Elena Senger, Yuri Campbell, Rob van der Goot +1
Accurate career path prediction can support many stakeholders, like job seekers, recruiters, HR, and project managers. However, publicly available data and tools for career path pr…
SnakModel: Lessons Learned from Training an Open Danish Large Language Model
Mike Zhang, Max Müller-Eberstein, Elisa Bassignana +1
We present SnakModel, a Danish large language model (LLM) based on Llama2-7B, which we continuously pre-train on 13.6B Danish words, and further tune on 3.7M Danish instructions. A…
How to Encode Domain Information in Relation Classification
Elisa Bassignana, Viggo Unmack Gascou, Frida Nøhr Laustsen +4
Current language models require a lot of training data to obtain high performance. For Relation Classification (RC), many datasets are domain-specific, so combining datasets to obt…
Can Humans Identify Domains?
Maria Barrett, Max Müller-Eberstein, Elisa Bassignana +3
Textual domain is a crucial property within the Natural Language Processing (NLP) community due to its effects on downstream model performance. The concept itself is, however, loos…
Big City Bias: Evaluating the Impact of Metropolitan Size on Computational Job Market Abilities of Language Models
Charlie Campanella, Rob van der Goot
Large language models (LLMs) have emerged as a useful technology for job matching, for both candidates and employers. Job matching is often based on a particular geographic locatio…
Deep Learning-based Computational Job Market Analysis: A Survey on Skill Extraction and Classification from Job Postings
Elena Senger, Mike Zhang, Rob van der Goot +1
Recent years have brought significant advances to Natural Language Processing (NLP), which enabled fast progress in the field of computational job market analysis. Core tasks in th…