114 citations · 315 across the 19 of their papers we have counts for
7 papers · 1 filter
CoSimLex: A Resource for Evaluating Graded Word Similarity in Context
Carlos Santos Armendariz, Matthew Purver, Matej Ulčar +5
State of the art natural language processing tools are built on context-dependent word embeddings, but no direct method for evaluating these representations currently exists. Stand…
High Quality ELMo Embeddings for Seven Less-Resourced Languages
Matej Ulčar, Marko Robnik-Šikonja
Recent results show that deep neural networks using contextual embeddings significantly outperform non-contextual embeddings on a majority of text classification task. We offer pre…
Multilingual Culture-Independent Word Analogy Datasets
Matej Ulčar, Kristiina Vaik, Jessica Lindström +2
In text processing, deep neural networks mostly use word embeddings as an input. Embeddings have to ensure that relations between words are reflected through distances in a high-di…
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…
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…
Exploring the relations between net benefits of IT projects and CIOs' perception of quality of software development disciplines
Damjan Vavpotič, Marko Robnik-Šikonja, Tomaž Hovelja
Software development enterprises are under consistent pressure to improve their management techniques and development processes. These are comprised of several disciplines like req…
Supervised and Unsupervised Neural Approaches to Text Readability
Matej Martinc, Senja Pollak, Marko Robnik-Šikonja
We present a set of novel neural supervised and unsupervised approaches for determining the readability of documents. In the unsupervised setting, we leverage neural language model…