Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations Q Chen, A Allot, R Leaman, R Islamaj, J Du, L Fang, K Wang, S Xu, ... Database 2022, baac069, 2022 | 22 | 2022 |
E8-IJS@ LT-EDI-ACL2022-BERT, AutoML and knowledge-graph backed detection of depression I Tavchioski, B Koloski, B Škrlj, S Pollak Proceedings of the second workshop on language technology for equality …, 2022 | 11 | 2022 |
Detection of depression on social networks using transformers and ensembles I Tavchioski, M Robnik-Šikonja, S Pollak arXiv preprint arXiv:2305.05325, 2023 | 3 | 2023 |
Early detection of depression with linear models using hand-crafted and contextual features. I Tavchioski, B Skrlj, S Pollak, B Koloski CLEF (Working Notes), 1005-1013, 2022 | 3 | 2022 |
Multi-label classification of COVID-19-related articles with an autoML approach I Tavchioski, B Koloski, B Škrlj, S Pollak Proceedings of the seventh BioCreative challenge evaluation workshop, 0 | 2 | |
Slovenian keyword extraction dataset from SentiNews 1.0 B Koloski, M Martinc, I Tavchioski, B Škrlj, S Pollak Jožef Stefan Institute, 2022 | 1 | 2022 |
Detecting depression from social networks using natural language processing I TAVCHIOSKI Univerza v Ljubljani, Fakulteta za računalništvo in informatiko, 2022 | | 2022 |