Papers by Kristian Nørgaard Jensen
Kompetencer: Fine-grained Skill Classification in Danish Job Postings via Distant Supervision and Transfer Learning (2022.lrec-1)
Copied to clipboard
| Challenge: | Several studies focus on Skill Identification, but there is little work in further categorizing the identified skills. |
| Approach: | They propose a Danish job posting dataset annotated for nested spans of competences . they use the European Skills, Competences, Qualifications and Occupations (ESCO) taxonomy API to obtain fine-grained labels via distant supervision. |
| Outcome: | The proposed dataset outperforms existing models in the Danish job postings. |
Fine-tuning vs From Scratch: Do Vision & Language Models Have Similar Capabilities on Out-of-Distribution Visual Question Answering? (2022.lrec-1)
Copied to clipboard
| Challenge: | Large general-purpose pre-trained models have become ubiquitous, but only limited research exists into their robustness. |
| Approach: | They perform a fine-grained evaluation of two models on Visual Question Answering using out-of-distribution data and a rephrasing analysis. |
| Outcome: | The proposed model is better than a previous model trained from scratch on the training data alone. |
DaN+: Danish Nested Named Entities and Lexical Normalization (2020.coling-main)
Copied to clipboard
| Challenge: | Named Entity Recognition (NER) is a task of finding entities in text, such as locations, organizations, and persons. |
| Approach: | They propose a multi-domain corpus and annotation guidelines for Danish nested named entities and lexical normalization to support research on cross-lingual cross-domain learning for a less-resourced language. |
| Outcome: | The proposed model outperforms existing models on the Danish Named Entity Recognition task and shows that it is robust to domain shifts and is highly effective on the least canonical data. |