16 citations · 38 across the 8 of their papers we have counts for
9 papers
Challenges in Explaining Pretrained Clinical Text Classifiers
Kristian Miok, Matej Klemen, Blaz Škrlj +1
Explaining the predictions of neural models in clinical NLP remains a significant challenge, especially for complex tasks involving long, unstructured medical texts. While post-hoc…
Evaluating Metalinguistic Knowledge in Large Language Models across the World's Languages
Tjaša Arčon, Matej Klemen, Marko Robnik-Šikonja +1
LLMs are routinely evaluated on language use, yet their explicit knowledge about linguistic structure remains poorly understood. Existing linguistic benchmarks focus on narrow phen…
Towards Corpus-Grounded Agentic LLMs for Multilingual Grammatical Analysis
Matej Klemen, Tjaša Arčon, Luka Terčon +2
Empirical grammar research has become increasingly data-driven, but the systematic analysis of annotated corpora still requires substantial methodological and technical effort. We…
Neural spell-checker: Beyond words with synthetic data generation
Matej Klemen, Martin Božič, Špela Arhar Holdt +1
Spell-checkers are valuable tools that enhance communication by identifying misspelled words in written texts. Recent improvements in deep learning, and in particular in large lang…
Code-mixed Sentiment and Hate-speech Prediction
Anjali Yadav, Tanya Garg, Matej Klemen +3
Code-mixed discourse combines multiple languages in a single text. It is commonly used in informal discourse in countries with several official languages, but also in many other co…
Review of Natural Language Processing in Pharmacology
Dimitar Trajanov, Vangel Trajkovski, Makedonka Dimitrieva +5
Natural language processing (NLP) is an area of artificial intelligence that applies information technologies to process the human language, understand it to a certain degree, and…
Extracting and filtering paraphrases by bridging natural language inference and paraphrasing
Matej Klemen, Marko Robnik-Šikonja
Paraphrasing is a useful natural language processing task that can contribute to more diverse generated or translated texts. Natural language inference (NLI) and paraphrasing share…
Enhancing deep neural networks with morphological information
Matej Klemen, Luka Krsnik, Marko Robnik-Šikonja
Deep learning approaches are superior in NLP due to their ability to extract informative features and patterns from languages. The two most successful neural architectures are LSTM…
Predicting kills in Game of Thrones using network properties
Jaka Stavanja, Matej Klemen, Lovro Šubelj
TV series such as HBO's Game of Thrones have seen a high number of dedicated followers, mostly due to the dramatic murders of the most important characters. In our work, we try to…