57 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Brno University of TechnologyCZ13 papers
- Slovak University of Technology in BratislavaSK6 papers
- Adobe Systems (United States)US3 papers
- Comenius University BratislavaSK3 papers
- Amazon (Germany)DE2 papers
- University of SheffieldGB2 papers
- Agence France-PresseFR1 paper
- Amazon (United Kingdom)GB1 paper
- Amazon (United States)US1 paper
- Amsterdam University of the ArtsNL1 paper
- Central European UniversityAT1 paper
- Fondazione Bruno KesslerIT1 paper
9 papers · 1 filter
The Brittle Compass: Navigating LLM Prompt Sensitivity in Slovak Migration Media Discourse
Samuel Harvan, Jaroslav Kopčan, Marek Šuppa +1
In this work, we present a case study that explores various tasks centered around the topic of migration in Slovak, a low-resource language, such as topic relevance and geographica…
Political Leaning and Politicalness Classification of Texts
Matous Volf, Jakub Simko
This paper addresses the challenge of automatically classifying text according to political leaning and politicalness using transformer models. We compose a comprehensive overview…
Beyond speculation: Measuring the growing presence of LLM-generated texts in multilingual disinformation
Dominik Macko, Aashish Anantha Ramakrishnan, Jason Samuel Lucas +4
Increased sophistication of large language models (LLMs) and the consequent quality of generated multilingual text raises concerns about potential disinformation misuse. While huma…
A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Models
Ivan Srba, Olesya Razuvayevskaya, João A. Leite +10
In the age of social media and generative AI, the ability to automatically assess the credibility of online content has become increasingly critical, complementing traditional appr…
Task Prompt Vectors: Effective Initialization through Multi-Task Soft-Prompt Transfer
Robert Belanec, Simon Ostermann, Ivan Srba +1
Prompt tuning is an efficient solution for training large language models (LLMs). However, current soft-prompt-based methods often sacrifice multi-task modularity, requiring the tr…
Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classification
Olesya Razuvayevskaya, Ben Wu, Joao A. Leite +5
Adapters and Low-Rank Adaptation (LoRA) are parameter-efficient fine-tuning techniques designed to make the training of language models more efficient. Previous results demonstrate…
KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection
Timo Hromadka, Timotej Smolen, Tomas Remis +2
This paper presents the best-performing solution to the SemEval 2023 Task 3 on the subtask 3 dedicated to persuasion techniques detection. Due to a high multilingual character of t…
Automatic question generation based on sentence structure analysis using machine learning approach
Miroslav Blšták, Viera Rozinajová
Automatic question generation is one of the most challenging tasks of Natural Language Processing. It requires "bidirectional" language processing: firstly, the system has to under…
Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims
Ivan Srba, Branislav Pecher, Matus Tomlein +4
False information has a significant negative influence on individuals as well as on the whole society. Especially in the current COVID-19 era, we witness an unprecedented growth of…