activity
20192025
most citedBayesian Methods for Semi-supervised Text Annotation

6 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CL2025

TT-XAI: Trustworthy Clinical Text Explanations via Keyword Distillation and LLM Reasoning

Kristian Miok, Blaz Škrlj, Daniela Zaharie +1

Clinical language models often struggle to provide trustworthy predictions and explanations when applied to lengthy, unstructured electronic health records (EHRs). This work introd…

cs.CL20206 cited

Bayesian Methods for Semi-supervised Text Annotation

Kristian Miok, Gregor Pirs, Marko Robnik-Sikonja

Human annotations are an important source of information in the development of natural language understanding approaches. As under the pressure of productivity annotators can assig…

stat.AP2020

To BAN or not to BAN: Bayesian Attention Networks for Reliable Hate Speech Detection

Kristian Miok, Blaz Skrlj, Daniela Zaharie +1

Hate speech is an important problem in the management of user-generated content. To remove offensive content or ban misbehaving users, content moderators need reliable hate speech…

cs.LG2020

Multiple Imputation for Biomedical Data using Monte Carlo Dropout Autoencoders

Kristian Miok, Dong Nguyen-Doan, Marko Robnik-Šikonja +1

Due to complex experimental settings, missing values are common in biomedical data. To handle this issue, many methods have been proposed, from ignoring incomplete instances to var…

stat.ML2019

Generating Data using Monte Carlo Dropout

Kristian Miok, Dong Nguyen-Doan, Daniela Zaharie +1

For many analytical problems the challenge is to handle huge amounts of available data. However, there are data science application areas where collecting information is difficult…

cs.CL2019

Prediction Uncertainty Estimation for Hate Speech Classification

Kristian Miok, Dong Nguyen-Doan, Blaž Škrlj +2

As a result of social network popularity, in recent years, hate speech phenomenon has significantly increased. Due to its harmful effect on minority groups as well as on large comm…